KR20230148084A - Method and cordless vacuum cleaner for automatically adjusting suction power strength of suction motor - Google Patents

Abstract

A method for a wireless vacuum cleaner to automatically adjust the suction force intensity of a suction motor may be disclosed. Specifically, acquiring data on flow path pressure measured by a pressure sensor; Obtaining data related to the load of the brush device through a load detection sensor; Identifying the current usage environment state of the brush device by applying data related to flow path pressure and data related to the load of the brush device to a previously learned AI model; and adjusting the intensity of suction force of the suction motor based on the current usage environment state of the identified brush device.

Description

Method for automatically adjusting the suction power of a suction motor and a cordless vacuum cleaner for the same {METHOD AND CORDLESS VACUUM CLEANER FOR AUTOMATICALLY ADJUSTING SUCTION POWER STRENGTH OF SUCTION MOTOR}

One embodiment of the present disclosure relates to a method for a wireless vacuum cleaner to automatically adjust the intensity of suction force of a suction motor.

A cordless vacuum cleaner is a type of vacuum cleaner that charges the battery built into the vacuum cleaner itself without the need to connect a wire to an outlet. The cordless vacuum cleaner includes a suction motor that generates suction force, and can suck foreign substances such as dust along with air from the cleaner head (brush) through the suction power generated by the suction motor, and separate the sucked foreign substances from the air to collect dust.

Recently, the types of vacuum cleaner heads (brushes) connected to the main body of a cordless vacuum cleaner are becoming more diverse. The brushes of a cordless vacuum cleaner can be divided into a main brush, which is generally used to clean the floor, and an auxiliary brush, which is used for special purposes. In order to be applicable to various cleaning environments, the types of auxiliary brushes used for special purposes are being further subdivided. However, there is an inconvenience in that the consumer must have a separate brush suited to the floor condition and must replace the brush himself.

A cordless vacuum cleaner according to an embodiment of the present disclosure includes a suction motor that creates a vacuum inside the cordless cleaner; A pressure sensor that measures the pressure of the flow path inside the cordless vacuum cleaner; A load detection sensor for measuring the load on the brush device; Memory to store an AI model trained to infer the state of the brush device's usage environment; And it may include at least one processor. At least one processor may obtain data about the flow path pressure measured by the pressure sensor from the pressure sensor. At least one processor may obtain data related to the load of the brush device through a load detection sensor. At least one processor may identify the current usage environment state of the brush device by applying data related to flow path pressure and data related to the load of the brush device to the AI model stored in the memory. At least one processor may adjust the intensity of suction force of the suction motor based on the current usage environment state of the identified brush device.

A method for a wireless vacuum cleaner to automatically adjust the suction force intensity of a suction motor of a cordless vacuum cleaner according to an embodiment of the present disclosure includes the steps of acquiring data on flow path pressure measured by a pressure sensor of the cordless vacuum cleaner; Obtaining data related to the load of the brush device through a load detection sensor of the wireless vacuum cleaner; Applying data related to flow path pressure and data related to the load of the brush device 2000 to an AI model stored in the memory of the wireless vacuum cleaner to identify the current usage environment state of the brush device; and adjusting the suction force intensity of the suction motor 1110 based on the current usage environment state of the identified brush device.

1 is a diagram for explaining a cleaning system according to an embodiment of the present disclosure.
Figure 2 is a diagram for explaining a wireless vacuum cleaner according to an embodiment of the present disclosure.
3 is a diagram for explaining the main body of a vacuum cleaner according to an embodiment of the present disclosure.
FIG. 4 is a diagram for explaining the operation of processors of a cordless vacuum cleaner according to an embodiment of the present disclosure.
Figure 5 is a diagram for explaining a brush device according to an embodiment of the present disclosure.
Figure 6 is a diagram for explaining an operation of identifying the type of brush device in the cleaner main body according to an embodiment of the present disclosure.
Figure 7 is a diagram for explaining the identification resistance (ID resistance) of the brush device according to an embodiment of the present disclosure.
FIG. 8 is a flowchart illustrating a method of controlling the intensity of suction force of a suction motor in a wireless vacuum cleaner according to an embodiment of the present disclosure.
FIG. 9 is a diagram illustrating an AI model for inferring the usage environment state of a brush device according to an embodiment of the present disclosure.
FIG. 10 is a diagram illustrating an operation of the cleaner main body identifying the usage environment state of the brush device using an SVM model according to an embodiment of the present disclosure.
FIG. 11 is a diagram illustrating an operation in which the vacuum cleaner main body identifies the use environment state of the brush device using a neural network model according to an embodiment of the present disclosure.
FIG. 12 is a diagram illustrating an operation in which the vacuum cleaner main body identifies the usage environment state of the brush device using a random forest model according to an embodiment of the present disclosure.
Figure 13 is a diagram for explaining an AI mode according to an embodiment of the present disclosure.
FIG. 14 is a diagram illustrating a method for a wireless vacuum cleaner to select an AI model according to the type of brush device according to an embodiment of the present disclosure.
FIG. 15A is a diagram for explaining a first SVM model corresponding to a multi-brush according to an embodiment of the present disclosure.
Figure 15b is a diagram for explaining an operation in which the parameter values of the first SVM model corresponding to the multi-brush are modified according to the change in power consumption of the suction motor.
Figure 15c is a diagram for explaining an operation in which the parameter values of the first SVM model corresponding to the multi-brush are modified according to the change in power consumption of the suction motor.
FIG. 16A is a diagram for explaining a second SVM model corresponding to a floor brush according to an embodiment of the present disclosure.
Figure 16b is a diagram for explaining an operation in which parameter values of the second SVM model corresponding to the floor brush are modified according to changes in power consumption of the suction motor.
Figure 16c is a diagram for explaining an operation in which the parameter values of the second SVM model corresponding to the floor brush are modified according to the change in power consumption of the suction motor.
FIG. 17 is a flowchart illustrating a method by which a wireless vacuum cleaner identifies a state transition of a usage environment of a brush device according to an embodiment of the present disclosure.
FIG. 18 is a flowchart illustrating an operation of a wireless vacuum cleaner using an SVM model to identify a usage environment state transition of a brush device according to an embodiment of the present disclosure.
FIG. 19 is a diagram illustrating an operation in which a main processor communicates with a second processor through a first processor according to an embodiment of the present disclosure.
Figure 20 is a diagram for explaining a circuit for signal line communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
FIG. 21 is a diagram for explaining a data format included in a signal transmitted between a cleaner main body and a brush device according to an embodiment of the present disclosure.
Figure 22 is a diagram for explaining an operation of transmitting a signal from the cleaner main body to the brush device according to an embodiment of the present disclosure.
Figure 23 is a diagram for explaining an operation of transmitting a signal from the brush device to the cleaner main body according to an embodiment of the present disclosure.
Figure 24 is a flowchart for explaining the operation of mutually transmitting signals between the cleaner main body and the brush device according to an embodiment of the present disclosure.
FIG. 25 is a diagram illustrating an operation of a cleaner main body identifying the type of a brush device based on a signal received from the brush device according to an embodiment of the present disclosure.
FIG. 26 is a diagram for explaining an operation in which a lighting device is controlled according to a usage environment state of a brush device according to an embodiment of the present disclosure.
Figure 27 is a diagram for explaining a circuit for signal line communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 28 is a diagram for explaining a circuit for I2C communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 29 is a diagram for explaining a circuit for UART full-duplex communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 30 is a diagram for explaining a circuit for UART half-duplex communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 31 is a diagram for explaining a circuit for I2C communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 32 is a diagram for explaining a circuit for UART communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 33 is a diagram for explaining a circuit for UART full-duplex communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 34 is a diagram for explaining a circuit for I2C communication of a wireless vacuum cleaner according to an embodiment of the present disclosure.
Figure 35 is a diagram for explaining an operation of a wireless vacuum cleaner outputting an operation status notification according to an embodiment of the present disclosure.
Figure 36 is a diagram for explaining the GUI of a wireless vacuum cleaner according to an embodiment of the present disclosure.

Terms used in the present disclosure will be briefly described, and an embodiment of the present disclosure will be described in detail.

The terms used in the present disclosure have selected general terms that are currently widely used as much as possible while considering the function in an embodiment of the present disclosure, but this may vary depending on the intention or precedent of a person working in the art, the emergence of new technology, etc. there is. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the corresponding embodiment of the present disclosure. Therefore, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of this disclosure, rather than simply the name of the term.

In the present disclosure, the expression “at least one of a, b, or c” refers to “a”, “b”, “c”, “a and b”, “a and c”, “b and c”, “a, b and c", or variations thereof.

Throughout the present disclosure, when a part “includes” a certain element, this means that it may further include other elements rather than excluding other elements, unless specifically stated to the contrary. In addition, terms such as "...unit" and "module" described in the present disclosure refer to a unit that processes at least one function or operation, and "...unit" and "module" are implemented in hardware or software. Alternatively, it can be implemented through a combination of hardware and software.

Below, with reference to the attached drawings, embodiments of the present disclosure will be described in detail so that those skilled in the art can easily practice them. However, an embodiment of the present disclosure may be implemented in various different forms and is not limited to the embodiment described herein. In order to clearly describe an embodiment of the present disclosure in the drawings, parts that are not related to the description are omitted, and similar parts are assigned similar reference numerals throughout the present disclosure.

1 is a diagram for explaining a cleaning system according to an embodiment of the present disclosure.

Referring to FIG. 1, a cleaning system according to an embodiment of the present disclosure may include a wireless cleaner 100. The wireless cleaner 100 may refer to a vacuum cleaner that has a built-in rechargeable battery and does not need to connect a power cord to an outlet during cleaning. The user can move the cordless vacuum cleaner 100 back and forth using the handle mounted on the vacuum cleaner body and allow the brush device (vacuum cleaner head) to suck in dust or trash from the surface being cleaned.

According to an embodiment of the present disclosure, the wireless vacuum cleaner 100 may provide a normal mode and an AI mode. The normal mode may be a manual mode in which the intensity of the suction force of the suction motor is adjusted according to the intensity (e.g., strong, medium, weak, etc.) selected by the user. In AI mode, the suction power of the suction motor or the number of revolutions per minute (hereinafter referred to as drum RPM) of the brush device varies depending on the usage environment of the brush device (e.g., the condition of the surface to be cleaned (floor, carpet, mat, corner, etc.)). It may be an automatic mode that is automatically adjusted. The suction power is the electrical power (Input Power) consumed to operate the wireless vacuum cleaner 100, and the suction power strength of the suction motor 1110 is the power consumption of the suction motor 1110. It can also be expressed.

Referring to 110 of FIG. 1, when the wireless cleaner 100 operates in normal mode, the user must replace the brush device or manually adjust the suction force strength of the suction motor depending on the condition of the surface being cleaned. For example, to increase cleaning efficiency, when the user cleans on a carpet, the brush device suitable for the carpet must be connected to the cleaner body, and when the user cleans the hard floor, the brush device suitable for the floor must be connected to the cleaner body. do. In addition, the user must directly increase the suction power of the cordless vacuum cleaner 100 when cleaning a rug or a wall corner, and when cleaning a mat, the suction power of the cordless vacuum cleaner 100 is lowered because the cordless vacuum cleaner 100 adheres too closely to the mat. The intensity must be lowered.

Meanwhile, when the wireless vacuum cleaner 100 operates in the normal mode, the user may maintain the suction force intensity at the maximum intensity without appropriately adjusting the suction force intensity depending on the situation. In this case, battery usage time may be significantly reduced, and when cleaning on a mat, the brush device may be in too close contact with the mat, making it difficult for the user to push the cordless vacuum cleaner 100 back and forth.

Additionally, when the wireless cleaner 100 operates in a normal mode, the motor rotation speed (eg, drum RPM) of the brush device or the trip level of the brush device cannot be appropriately adjusted depending on the situation. The trip level is used to prevent overload of the brush device and may mean a reference load value (e.g., reference current value) for stopping the operation of the brush device.

Referring to 120 in FIG. 1, when the wireless cleaner 100 operates in AI mode, the wireless cleaner 100 uses an AI model learned to infer the usage environment state of the brush device to determine the current usage environment state of the brush device. can be deduced, and the suction force strength of the suction motor can be automatically adjusted according to the current usage environment status of the brush device. For example, when the state of the surface to be cleaned changes from hard floor to carpet, the wireless cleaner 100 may increase the suction power of the suction motor to improve cleaning performance. On the other hand, when the state of the surface to be cleaned changes from carpet to floor again, the wireless cleaner 100 is used to increase the usage time of the battery (or to increase operation noise (e.g., drum friction noise of the brush device, suction motor operation noise of the cleaner body). etc.), or to reduce damage (e.g. scratches, nicks, abrasions, etc.) caused by friction on the surface being cleaned due to the drum rotation of the brush device, the suction power of the suction motor can be lowered again. When the condition of the surface to be cleaned changes from floor to mat, to increase the convenience of operation (or to reduce operation noise (e.g., friction noise of the drum of the brush unit, operation noise of the suction motor of the cleaner body, etc.), or to reduce the operation noise of the drum of the brush unit In order to reduce damage (e.g., scratches, scuffs, abrasion, etc.) caused by friction of the surface being cleaned due to rotation), the wireless cleaner 100 can automatically lower the suction power of the suction motor, and the brush device can automatically lower the suction power of the surface being cleaned. When lifted from the cordless vacuum cleaner (idle state), to extend the battery usage time (or to reduce operation noise (e.g., drum friction noise of the brush unit, suction motor operation noise of the vacuum cleaner body, etc.)) (100) can lower the suction force intensity of the suction motor as much as possible.

According to an embodiment of the present disclosure, when the wireless cleaner 100 operates in AI mode, the wireless cleaner 100 may control the operation of the brush device through communication between the cleaner main body and the brush device. The wireless cleaner 100 can adjust the motor rotation speed (e.g., drum RPM), trip level, and operation of the lighting device (e.g., color, brightness) of the brush device according to the current usage environment status of the brush device. there is.

For example, when the state of the surface to be cleaned changes from hard floor to carpet, the wireless cleaner 100 may increase the motor rotation speed (eg, drum RPM) of the brush device to increase cleaning performance. On the other hand, when the state of the surface to be cleaned changes from carpet to floor again, the wireless cleaner 100 is used to increase the usage time of the battery (or to increase operation noise (e.g., drum friction noise of the brush device, suction motor operation noise of the cleaner body). etc.), or to reduce damage (e.g. scratches, scratches, nicks, abrasions, etc.) caused by friction on the surface being cleaned by the drum rotation of the brush device, the motor rotation speed of the brush device (e.g. drum RPM) can be lowered again. In addition, when the brush device is lifted from the surface being cleaned (e.g., idle), in order to extend the battery usage time (or to increase operating noise (e.g., drum friction noise of the brush device, suction motor operation noise of the cleaner body), etc.), the wireless cleaner 100 may lower the motor rotation speed (e.g., drum RPM) of the brush device to the maximum.

Therefore, when the wireless cleaner 100 operates in AI mode, the wireless cleaner 100 automatically adjusts the suction force intensity of the suction motor or the motor rotation speed of the brush device according to the current usage environment status of the brush device inferred by the AI model. By adjusting the cleaning performance, user convenience, battery usage time, operation noise (e.g., drum friction noise of the brush device, suction motor operation noise of the cleaner body, etc.), the surface to be cleaned due to the drum rotation of the brush device Damage caused by friction (e.g. scratches, scratches, nicks, wear, etc.) can be efficiently improved. Additionally, the wireless vacuum cleaner 100 can provide optimal control suited to the various living environments of each user by using an AI model.

The operation of the wireless vacuum cleaner 100 providing optimal control using the AI model will be examined in detail later with reference to FIG. 8, and hereinafter, with reference to FIG. 2, the wireless vacuum cleaner 100 according to an embodiment of the present disclosure will be described. Let us look at the composition of (100).

FIG. 2 is a diagram for explaining a wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 2, the wireless cleaner 100 according to an embodiment of the present disclosure may be a stick-type cleaner including a cleaner main body 1000, a brush device 2000, and an extension tube 3000. However, not all of the components shown in FIG. 2 are essential components. The wireless cleaner 100 may be implemented with more components than those shown in FIG. 2, or the wireless cleaner 100 may be implemented with fewer components. For example, the wireless cleaner 100 may be implemented as a cleaner body 1000 and a brush device 2000, excluding the extension tube 3000. Additionally, the wireless cleaner 100 may further include a cleaning station (not shown) for discharging dust from the cleaner main body 1000 and charging the battery. Let's look at each configuration below.

The cleaner main body 1000 is a part that the user can hold and move when cleaning, and may include a suction motor 1110 that creates a vacuum inside the wireless cleaner 100. The suction motor 1110 may be located in a dust container (dust container) that accommodates foreign substances sucked from the surface to be cleaned (e.g., floor, bedding, sofa, etc.). The cleaner main body 1000 may further include at least one processor 1001, a load detection sensor 1134, a pressure sensor 1400, and a memory 1900 in addition to the suction motor 1110, but is not limited thereto. no.

The load detection sensor 1134 may be a sensor for measuring the load of the brush device 2000 or a load detection (sensing) circuit, but is not limited thereto. The pressure sensor 1400 may be a sensor that measures pressure in the flow path inside the wireless vacuum cleaner 100. The memory 1900 may store an AI model learned to infer the usage environment state of the brush device. In addition, at least one processor 1001 obtains data about the flow path pressure measured by the pressure sensor 1400 from the pressure sensor 1400 and detects the load of the brush device 2000 through the load detection sensor 1134. You can obtain data related to . And the at least one processor 1001 applies data related to flow path pressure and data related to the load of the brush device 2000 to the AI model stored in the memory 1900 to determine the current usage environment state of the brush device 2000. can be identified. At least one processor 1001 may adjust the intensity of suction force of the suction motor 1110 based on the current usage environment state of the brush device 2000. The vacuum cleaner body 1000 will be examined in detail later with reference to FIG. 3 .

The brush device 2000 is a device that is in close contact with the surface to be cleaned and can suck air and foreign substances from the surface to be cleaned. The brush device 2000 may also be represented as a vacuum cleaner head. The brush device 2000 may be rotatably coupled to the extension pipe 3000. The brush device 2000 may include a motor, a drum with a rotating brush attached thereto, but is not limited thereto. According to one embodiment of the present disclosure, the brush device 2000 may further include at least one processor for controlling communication with the cleaner main body 1000. There may be various types of brush device 2000, and the types of brush device 2000 will be discussed in detail later with reference to FIG. 5.

The extension pipe 3000 may be formed of a pipe or flexible hose with a certain rigidity. The extension tube 3000 transmits the suction force generated through the suction motor 1110 of the cleaner main body 1000 to the brush device 2000, and transfers air and foreign substances sucked through the brush device 2000 to the cleaner main body 1000. It can be moved. The extension tube 3000 may be separably connected to the brush device 2000. The extension tube 3000 may be formed in multiple stages between the cleaner main body 1000 and the brush device 2000. There may be two or more extension tubes 3000.

According to an embodiment of the present disclosure, the cleaner main body 1000, brush device 2000, and extension tube 3000 included in the wireless cleaner 100 each have a power line (for example, a +power line, a -power line). and signal lines.

The power line may be a line for transmitting power supplied from the battery 1500 to the cleaner main body 1000 and the brush device 2000 connected to the cleaner main body 1000. The signal line is different from the power line and may be a line for transmitting and receiving signals between the cleaner main body 1000 and the brush device 2000. The signal line may be implemented to be connected to a power line within the brush device 2000.

According to an embodiment of the present disclosure, each of the at least one processor 1001 of the vacuum cleaner body 1000 and the processor of the brush device 2000 controls the operation of a switch element connected to a signal line, thereby controlling the vacuum cleaner body 1000 and the brush. Two-way communication between devices 2000 can be performed. Hereinafter, when the cleaner main body 1000 and the brush device 2000 communicate through a signal line, communication between the cleaner main body 1000 and the brush device 2000 may be defined as 'signal line communication.' Signal line communication will be examined in detail later with reference to FIGS. 20 to 24.

Meanwhile, the cleaner main body 1000 and the brush device 2000 may communicate using I2C (Inter Integrated Circuit) or UART (Universal asynchronous receiver/transmitter). The operation in which the cleaner main body 1000 and the brush device 2000 communicate using I2C or UART will be examined in detail later with reference to FIGS. 32 to 38.

According to an embodiment of the present disclosure, the cleaner main body 1000 goes beyond detecting whether the brush device 2000 is attached or detachable to identifying the type of the brush device 2000 and determining the use environment status of the brush device 2000 (e.g. : The operation (e.g., drum RPM) of the brush device 2000 may be adaptively controlled depending on the condition (hard floor, carpet, mat, corner, lifted state from the surface to be cleaned, etc.). For example, the cleaner main body 1000 may transmit a signal for controlling the operation of the brush device 2000 to the brush device 2000 by periodically communicating with the brush device 2000. The method by which the cleaner main body 1000 adaptively controls the operation (e.g., drum RPM) of the brush device 2000 will be discussed in detail later with reference to FIG. 23. Hereinafter, the cleaner main body 1000 will be described with reference to FIG. 3. ) Let's take a closer look at the composition.

FIG. 3 is a diagram for explaining the cleaner main body 1000 according to an embodiment of the present disclosure.

The cleaner body 1000 may include a handle that can be held by a user. Accordingly, the vacuum cleaner body 1000 may be expressed as a handy body. The user can hold the handle and move the cleaner body 1000 and the brush device 2000 in the forward and backward directions.

Referring to FIG. 3, the cleaner main body 1000 includes a suction force generating device (hereinafter referred to as the motor assembly 1100) that generates the suction force necessary to suck in foreign substances on the surface to be cleaned, and a dust collection container that accommodates foreign substances sucked from the surface to be cleaned. (1200, also known as a dust bin), a filter unit 1300, a pressure sensor 1400, a battery 1500 capable of supplying power to the motor assembly 1100, a communication interface 1600, a user interface 1700, at least one may include a processor 1001 (e.g., main processor 1800) and a memory 1900. However, not all of the components shown in FIG. 3 are essential components. The cleaner main body 1000 may be implemented with more components than those shown in FIG. 3, or the cleaner main body 1000 may be implemented with fewer components.

Below, we will look at each configuration.

The motor assembly 1100 includes a suction motor 1110 that converts electrical force into mechanical rotational force, a fan 1120 that is connected to the suction motor 1110 and rotates, and a drive circuit (PCB: Printed) connected to the suction motor 1110. Circuit　Board) (1130) may be included. The suction motor 1110 can form a vacuum inside the wireless cleaner 100. Here, vacuum means a state lower than atmospheric pressure. The suction motor 1110 may include a brushless motor (hereinafter referred to as a brushless direct current (BLDC) motor), but is not limited thereto.

The driving circuit 1130 controls the suction motor 1110, a processor (hereinafter referred to as the first processor 1131) that controls communication with the brush device 2000, and a first switch element 1132 connected to a signal line. , a switch element (hereinafter referred to as the PWM control switch element 1133) for controlling the power supply to the brush device 2000 (e.g. FET, Transistor, IGBT, etc.), a load that senses the load of the brush device 2000 It may include a detection sensor 1134 (e.g., a shunt resistor, a shunt resistor and amplification circuit (OP-AMP), a current detection sensor, a magnetic field detection sensor (non-contact type), etc.), but is not limited thereto. Hereinafter, for convenience of explanation, the FET will be described as an example of the PWM control switch element 1133, and the shunt resistance will be described as an example of the load detection sensor 1134.

The first processor 1131 may obtain data related to the state of the suction motor 1110 (hereinafter referred to as state data) and transmit the state data of the suction motor 1110 to the main processor 1800. In addition, the first processor 1131 controls (e.g., turns on or turns off) the operation of the first switch element 1132 connected to the signal line and sends a signal (hereinafter referred to as the first signal) to the brush device 2000 through the signal line. ) can be transmitted. The first switch element 1132 is an element that can set the signal line to Low. For example, the first switch element 1132 is an element that can cause the voltage of the signal line to be 0V. The first signal is the target rotation per minute (hereinafter also referred to as target drum RPM) of the rotating brush of the brush device 2000, the target trip level of the brush device 2000, or the consumption of the suction motor 1110. It may include data representing at least one of power, but is not limited thereto. For example, the first signal may include data for controlling a lighting device included in the brush device 2000. The first signal may be implemented with a preset number of bits. For example, the first signal may be implemented with 5 bits or 8 bits, and may have a transmission period of 10 ms per bit, but is not limited thereto.

The first processor 1131 may detect a signal (hereinafter referred to as a second signal) transmitted from the brush device 2000 through a signal line. The second signal may include data indicating the current state of the brush device 2000, but is not limited thereto. For example, the second signal may include data regarding current operating conditions (e.g., current drum RPM, current restraint level, current lighting device setting value, etc.). Additionally, the second signal may further include data indicating the type of brush device 2000. The first processor 1311 may transmit data indicating the current state of the brush device 2000 or data indicating the type of the brush device 2000 included in the second signal to the main processor 1800. The driving circuit 1130 of the motor assembly 1100 will be examined in more detail later with reference to FIG. 20.

The motor assembly 1100 may be located within the dust collection container 1200. The dust collection container 1200 may be configured to filter and collect dust or dirt in the air flowing in through the brush device 2000. The dust collection box 1200 may be provided to be detachable from the cleaner main body 1000.

The dust collection container 1200 can collect foreign substances through a cyclone method that separates foreign substances using centrifugal force. Air from which foreign substances have been removed through the cyclone method may be discharged to the outside of the cleaner main body 1000, and the foreign substances may be stored in the dust collection container 1200. A multi-cyclone may be placed inside the dust collection container 1200. The dust collection container 1200 may be provided to collect foreign substances on the lower side of the multi-cyclone. The dust collection container 1200 may include a dust collection container door that is provided to open the dust collection container when connected to the cleaning station. The dust collection box 1200 may include a first dust collection unit in which relatively large foreign substances are primarily collected and a second dust collection unit in which relatively small foreign substances are collected by a multi-cyclone. Both the first dust collection unit and the second dust collection unit may be arranged to be open to the outside when the dust collection container door is opened.

The filter unit 1300 can filter ultrafine dust that is not filtered in the dust collection container 1200. The filter unit 1300 may include an outlet that allows air that has passed through the filter to be discharged to the outside of the wireless cleaner 100. The filter unit 1300 may include a motor filter, a HEPA filter, etc., but is not limited thereto.

The pressure sensor 1400 can measure the pressure inside the flow path (hereinafter also referred to as flow path pressure). In the case of the pressure sensor 1400 provided at the suction end (e.g., suction duct 40), the change in flow rate at the corresponding location can be measured by measuring the static pressure. The pressure sensor 1400 may be an absolute pressure sensor or a relative pressure sensor. When the pressure sensor 1400 is an absolute pressure sensor, the main processor 1800 can use the pressure sensor 1400 to sense the first pressure value before operating the suction motor 1110. Additionally, the main processor 1800 may sense the second pressure value after driving the suction motor 1110 at the target RPM, and use the difference between the first pressure value and the second pressure value as the pressure value inside the flow path. At this time, the first pressure value may be a pressure value due to internal/external influences such as weather, altitude, status of the wireless vacuum cleaner 100, and dust inflow, and the second pressure value may be a pressure value due to altitude, status of the wireless vacuum cleaner 100, and dust inflow. It may be a pressure value due to internal/external influences such as the inflow amount and a pressure value due to driving the suction motor 1110, and the difference between the first pressure value and the second pressure value may be a pressure value due to driving the suction motor 1110. Therefore, when the difference between the first pressure value and the second pressure value is used as the pressure value inside the flow path, internal/external influences other than those of the suction motor 1110 can be minimized.

The flow path pressure measured by the pressure sensor 1400 identifies the current use environment state of the brush device 2000 (e.g., the state of the surface to be cleaned (floor, carpet, mat, corner, etc.), the state lifted from the surface to be cleaned, etc.) It may be used to measure suction power that changes depending on the degree of contamination of the dust collection container 1200 or the degree of dust collection.

The pressure sensor 1400 may be located at the suction end (eg, suction duct 40). The suction duct 40 is a structure that connects the dust collection container 1200 and the extension pipe 3000 or the dust collection container 1200 and the brush device 2000 to allow fluid containing foreign substances to move to the dust collection container 1200. It can be. The pressure sensor 1400 may be located at the end of a straight section (or an inflection point between a straight section and a curved section) of the suction duct 40 in consideration of contamination by foreign substances/dust, but is not limited thereto. The pressure sensor 1400 may be located in the middle of the straight portion of the suction duct 40. Meanwhile, when the pressure sensor 1400 is located in the suction duct 40, the pressure sensor 1400 is located in front of the suction motor 1110 that generates suction force, so the pressure sensor 1400 is a negative pressure sensor. sensor).

In the present disclosure, the case where the pressure sensor 1400 is located in the suction duct 40 is described as an example, but is not limited thereto. The pressure sensor 1400 may be located at the discharge end (eg, within the motor assembly 1100). When the pressure sensor 1400 is located at the discharge end, the pressure sensor 1400 is located at the rear end of the suction motor 1110, so it can be implemented as a positive pressure sensor. Additionally, a plurality of pressure sensors 1000 may be provided in the wireless vacuum cleaner 100.

The battery 1500 may be detachably mounted on the cleaner body 1000. The battery 1500 may be electrically connected to a charging terminal provided in a clean station (not shown). The battery 1500 can be charged by receiving power from a charging terminal. The clean station may be a device for discharging dust of the wireless cleaner 100 and charging the battery 1500. The wireless cleaner 100 can be mounted (docked) at a cleaning station to discharge dust, charge the battery 1500, or be stored.

The cleaner main body 1000 may include a communication interface 1600 for communicating with an external device. For example, the cleaner main body 1000 may communicate with a cleaning station (or server device) through the communication interface 1600. The communication interface 1600 may include a short-range communication unit and a long-distance communication unit. The short-range wireless communication interface includes a Bluetooth communication unit, BLE (Bluetooth Low Energy) communication unit, NFC (Near Field Communication interface), WLAN (Wi-Fi) communication unit, Zigbee communication unit, and infrared (IrDA) communication unit. , Infrared Data Association) communication department, WFD (Wi-Fi Direct) communication department, UWB (ultra wideband) communication department, Ant+ communication department, etc., but is not limited thereto.

The user interface 1700 may be provided on the handle. The user interface 1700 may include an input interface and an output interface. The cleaner main body 1000 may receive user input related to the operation of the wireless cleaner 100 through the user interface 1700, and may output information related to the operation of the wireless cleaner 100. The input interface may include a power button, a suction power intensity control button, etc. The output interface may include, but is not limited to, an LED display, LCD, touch screen, etc.

The cleaner main body 1000 may include at least one processor 1001. The cleaner main body 1000 may include one processor or may include a plurality of processors. For example, the cleaner body 1000 may include a main processor 1800 connected to the user interface 1700 and a first processor 1131 connected to the suction motor 1110. At least one processor 1001 may control the overall operation of the wireless vacuum cleaner 100. For example, the at least one processor 1001 determines the power consumption (suction force intensity) of the suction motor 1110, the drum RPM of the brush device 2000, the trip level of the brush device 2000, etc. You can.

At least one processor 1001 according to the present disclosure includes a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Accelerated Processing Unit (APU), Many Integrated Core (MIC), Digital Signal Processor (DSP), and NPU ( Neural Processing Unit) may be included. At least one processor 1001 may be implemented in the form of an integrated system-on-chip (SoC) including one or more electronic components. Each of the at least one processor 1001 may be implemented as separate hardware (H/W). At least one processor may be expressed as a Microprocessor controller (MICOM), Micro Processor unit (MPU), or Micro Controller Unit (MCU).

At least one processor 1001 according to the present disclosure may be implemented as a single core processor or a multicore processor.

The memory 1900 may store programs for processing and control of at least one processor 1001, and may also store input/output data. For example, the memory 1900 includes a pre-learned AI model (e.g., SVM (Support Vector Machine) algorithm, etc.), state data of the suction motor 1110, measured values of the pressure sensor 1400, and the battery 1500. Status data, status data of the brush device 2000, error occurrence data, power consumption of the suction motor 1110 corresponding to the operating conditions, RPM of the drum with the rotating brush, restraint level, etc. can be stored. The trip level is used to prevent overload of the brush device 2000 and may mean a reference load value (eg, a reference current value) for stopping the operation of the brush device 2000.

Hereinafter, the operation of the processors of the wireless vacuum cleaner 100 will be looked at in detail with reference to FIG. 4.

FIG. 4 is a diagram for explaining the operation of processors of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 4, the main processor 1800 communicates with the battery 1500, the pressure sensor 1400, and the first processor 1131 in the motor assembly 1100 to check the status of parts in the cordless vacuum cleaner 100. You can. At this time, the main processor 1800 may communicate with each component using a universal asynchronous receiver/transmitter (UART) or an inter integrated circuit (I2C), but is not limited to this. For example, the main processor 1800 may obtain data about the voltage status (e.g., normal, abnormal, fully charged, fully discharged, etc.) of the battery 1500 from the battery 1500 using the UART. The main processor 1800 may obtain data about flow path pressure from the pressure sensor 1400 using I2C.

In addition, the main processor 1800 uses the UART from the first processor 1131 connected to the suction motor 1110 to determine the suction force intensity, RPM of the suction motor 1110, and the status of the suction motor 1110 (e.g., normal , abnormalities, etc.) can be obtained. Suction power is the electrical power consumed to operate the wireless vacuum cleaner 100, and may be expressed as power consumption. The main processor 1800 may obtain data related to the load of the brush device 2000 and data related to the type of the brush device 2000 from the first processor 1131.

Meanwhile, the first processor 1131 provides status data (e.g., drum RPM, trip level, normal, abnormal) of the brush device 2000 through signal line communication with the second processor 2410 of the brush device 2000. etc.) can also be obtained from the brush device 2000. At this time, the first processor 1131 may transmit status data of the brush device 2000 to the main processor 1800 through UART. According to an embodiment of the present disclosure, the first processor 1131 may transmit state data of the suction motor 1110 and state data of the brush device 2000 to the main processor 1800 at different cycles. For example, the first processor 1131 transmits the status data of the suction motor 1110 to the main processor 1800 once every 0.02 seconds, and transmits the status data of the brush device 2000 to the main processor 1800 once every 0.2 seconds. ), but is not limited to this.

When connecting the first processor 1131 of the cleaner main body 1000 and the second processor 2410 of the brush device 2000 via UART or I2C, high impedance effects due to internal lines of the extension tube 3000, etc. and electrostatic discharge (ESD) : Electro static discharge) and/or damage to circuit elements due to overvoltage (e.g. exceeding the maximum voltage of the Micom AD port) may be a problem. Therefore, according to an embodiment of the present disclosure, the first processor 1131 of the cleaner main body 1000 and the second processor 2410 of the brush device 2000 communicate through signal line communication instead of UART or I2C. At this time, the circuit for signal line communication is a voltage distribution circuit (hereinafter referred to as voltage distribution circuit) to prevent damage to circuit elements due to overvoltage, power noise, surge, ESD (Electrical Overstress), and EOS (Electrical Discharge). (referred to as a distributor). However, communication between the first processor 1131 of the cleaner main body 1000 and the second processor 2410 of the brush device 2000 is not limited to signal line communication.

According to an embodiment of the present disclosure, when the noise reduction circuit is applied to the cleaner main body 1000 and the brush device 2000, the first processor 1131 of the cleaner main body 1000 and the second processor 1131 of the brush device 2000 The processor 2410 may also communicate using UART or I2C. The noise reduction circuit may include at least one of a low pass filter, a high pass filter, a band pass filter, a damping resistor, and a distribution resistor. It is not limited to this. According to an embodiment of the present disclosure, when the level shifter circuit is applied to the cleaner main body 1000 or the brush device 2000, the first processor 1131 of the cleaner main body 1000 and the second processor 1131 of the brush device 2000 The processor 2410 may also communicate using UART or I2C. Various communication methods between the cleaner main body 1000 and the brush device 2000 will be discussed in detail later with reference to FIGS. 20 and 27 to 34. Hereinafter, for convenience of explanation, the case where the cleaner main body 1000 and the brush device 2000 communicate through signal line communication will be described as a main example.

Meanwhile, the main processor 1800 may receive user input for setting buttons (e.g., ON/OFF button, +/- setting button) included in the user interface 1700, and may control the output of the LCD. . The main processor 1800 uses a previously learned AI model (e.g., SVM algorithm) to determine the usage environment status of the brush device 2000 (e.g., the state of the surface to be cleaned (floor, carpet, mat, corner, etc.), the surface to be cleaned, (e.g. lifted state, etc.), and operation information of the wireless cleaner 100 (e.g., power consumption of the suction motor 1110, drum RPM, trip level, etc.) that matches the usage environment condition of the brush device 2000. ) can also be determined. At this time, the main processor 1800 may transmit operation information of the wireless vacuum cleaner 100 that matches the usage environment state of the brush device 2000 to the first processor 1131. The first processor 1131 can adjust the strength of the suction force (power consumption, RPM) of the suction motor 1110 according to the operation information of the wireless cleaner 100, and generate a wireless cleaner suitable for the usage environment of the brush device 2000. The operation information of 100 may be transmitted to the second processor 2410 through signal line communication. In this case, the second processor 2410 may adjust the drum RPM, restraint level, lighting device (eg, LED display), etc. according to the operation information of the wireless cleaner 100. The main processor 1800 uses a pre-learned AI model (e.g., SVM algorithm) to identify the usage environment state of the brush device 2000, and creates a wireless vacuum cleaner 100 that matches the usage environment state of the brush device 2000. The operation of determining the operation information will be looked at in detail later with reference to FIG. 14, and hereinafter, the brush device 2000 will be looked at in more detail with reference to FIG. 5.

FIG. 5 is a diagram for explaining a brush device 2000 according to an embodiment of the present disclosure.

Referring to FIG. 5, the brush device 2000 may include a motor 2100, a drum 2200 with a rotating brush attached thereto, a lighting device 2300, etc., but is not limited thereto. The motor 2100 of the brush device 2000 may be provided inside the drum 2200 or may be provided outside the drum 2200. When the motor 2100 is provided outside the drum 2200, the drum 2200 can receive power from the motor 2100 through a belt.

Referring to 510 in FIG. 5, the motor 2100 may be a planetary geared motor. A planetary geared motor may be a combination of a DC motor and a planetary gear. The planetary gear is used to adjust the RPM of the drum 2200 according to the gear ratio. In the case of a planetary geared motor, the RPM of the motor 2100 and the RPM of the drum 2200 may have a constant ratio. Referring to 520 in FIG. 5, the motor 2100 may be a BLDC (Brushless Direct Current) motor, but is not limited thereto. When the motor 2100 is a BLDC motor, the RPM of the motor 2100 and the RPM of the drum 2200 may be the same.

The lighting device 2300 is used to illuminate the dark surface to be cleaned, to facilitate identification of dust or foreign matter on the surface to be cleaned, or to indicate the status of the brush device 2000, and is located on the front or top of the brush device 2300. It can be provided. The lighting device 2300 may include, but is not limited to, an LED display. For example, the lighting device 2300 may be a laser. The lighting device 2300 may operate automatically as the motor 2100 is driven, or may operate under the control of the second processor 2410. According to an embodiment of the present disclosure, the lighting device 2300 may change color or brightness under control of the second processor 2410.

Referring to 520 of FIG. 5, the brush device 2000 may further include a driving circuit (PCB) 2400. The driving circuit 2400 may include a circuit for signal line communication with the cleaner main body 1000. For example, the driving circuit 2400 includes a second processor 2410, a switch element (hereinafter also referred to as a second switch element) (not shown) connected to the signal line, and an identification resistor indicating the type of the brush device 2000 ( (not shown), etc., but is not limited thereto. The driving circuit 2400 will be examined in detail later with reference to FIG. 20.

Meanwhile, types of brush device 2000 may vary. For example, the brush device 2000 includes a multi brush 501, a floor brush 502, a mop brush 503, a turbo (carpet) brush 504, a bedding brush 505, and a brush brush (not shown). , gap brush (not shown), pet brush (not shown), etc., but is not limited thereto.

According to an embodiment of the present disclosure, the type of brush device 2000 may be distinguished by an identification resistor included in the brush device 2000. An operation in which the cleaner body 1000 identifies the type of brush device 2000 coupled to the wireless cleaner 100 will be described with reference to FIG. 6 .

FIG. 6 is a diagram for explaining an operation of identifying the type of brush device 2000 in the cleaner main body 1000 according to an embodiment of the present disclosure.

Referring to FIG. 6, the motor assembly 1100 of the cleaner main body 1000 may include a first processor 1131 and a load detection sensor 1134 (e.g., shunt resistor), and the brush device 2000 An identification resistor 2500 may be included. The identification resistor 2500 may be located between the power lines 10 and 20 and the signal line 30. The identification resistor 2500 represents the type of brush device 2000 and may be different for each type of brush device 2000. For example, the discrimination resistance 2500 of the multi brush 501 is 330KΩ, the discrimination resistance 2500 of the floor brush 502 is 2.2MΩ, and the discrimination resistance 2500 of the turbo (carpet) brush 504 is It may be 910KΩ, but is not limited thereto.

The first processor 1131 can detect whether the brush device 200 is attached or detached using the load detection sensor 1134. For example, when the brush device 2000 is not coupled to the wireless cleaner 100 (e.g., handy mode), the operating current of the brush device 2000 detected by the load detection sensor 1134 is “0” (zero). ) can be. On the other hand, when the brush device 2000 is coupled to the wireless cleaner 100 (e.g., brush mode), the operating current of the brush device 2000 detected by the load detection sensor 1134 may be 50 mA or more. Accordingly, the first processor 1131 determines that the brush device 2000 is detached when the operating current of the brush device 2000 detected by the load detection sensor 1134 is 0, and the load detection sensor 1134 determines that the brush device 2000 is detached. If the detected operating current of the brush device 2000 is 50 mA or more, it may be determined that the brush device 2000 is coupled. Meanwhile, the reference operating current value for determining that the brush device 2000 is coupled is not limited to 50 mA and may be changed.

When it is determined that the brush device 2000 is coupled to the wireless cleaner 100, the first processor 1131 operates the brush device 2000 based on the voltage value input to the input port of the first processor 1131. type can be identified. For example, if the brush device 2000 includes an identification resistor A, and the driving circuit 1130 of the cleaner body 1000 includes a voltage divider (resistor B and resistor C) connected to the signal line 30, The voltage input to the input port of the first processor 1131 may be as follows.

The voltage value input to the input port of the first processor 1131 may decrease as the value of the identification resistor 2500 increases. When resistance B and resistance C are constant, the voltage value input to the input port varies depending on the value of identification resistor A, so the first processor 1131 sets the identification resistor 2500 based on the voltage value input to the input port. The type of corresponding brush device 2000 can be identified. Please refer to FIG. 7.

FIG. 7 is a diagram for explaining the identification resistance (ID resistance) of the brush device 2000 according to an embodiment of the present disclosure.

Referring to the table 700 in FIG. 7, the identification resistance of the multi brush 501 is 330KΩ, the identification resistance of the floor brush 502 is 2.2MΩ, and the identification resistance of the turbo (carpet) brush 504 is 910KΩ. You can. If the voltage of the battery 1500 is 25.2V, the voltage value input to the input port of the first processor 1131 when the multi brush 501 is coupled to the wireless cleaner 100 is 2.785V, and the voltage value input to the input port of the wireless cleaner 100 is 2.785V. When the floor brush 502 is coupled to the 100, the voltage value input to the input port of the first processor 1131 is 0.791V, and when the turbo (carpet) brush 504 is coupled to the wireless vacuum cleaner 100 The voltage value input to the input port of the first processor 1131 may be 1.563V. Accordingly, the first processor 1131 determines that the brush device 2000 is coupled to the wireless cleaner 100, and in a situation where the voltage of the battery 1500 is 25.2V, the voltage value input to the input port is 2.785V. If , the multi brush 501 is identified as being combined, and if the voltage value input to the input port is 0.791V, the floor brush 502 is identified as being combined, and if the voltage value input to the input port is 1.563V. It can be identified that the turbo (carpet) brush 504 is combined.

Hereinafter, the operation of the wireless cleaner 100 to automatically adjust the suction force intensity of the suction motor 1110 according to the usage environment of the brush device 2000 will be examined in detail with reference to FIG. 8.

FIG. 8 is a flowchart illustrating a method by which the wireless vacuum cleaner 100 adjusts the suction force intensity of the suction motor 1110 according to an embodiment of the present disclosure.

In step S810, the wireless cleaner 100 may obtain data about the flow path pressure measured by the pressure sensor 1400.

According to an embodiment of the present disclosure, at least one processor 1001 of the cleaner main body 1000 may acquire the pressure value measured by the pressure sensor 1400. For example, the main processor 1800 may receive the pressure value measured by the pressure sensor 1400 from the pressure sensor 1400 through I2C communication. The pressure sensor 1400 is located within the flow path and can measure the pressure inside the flow path (flow path pressure). For example, the pressure sensor 1400 may be located within the suction duct 40 or the motor assembly 1100, but is not limited thereto.

The pressure sensor 1400 may be an absolute pressure sensor or a relative pressure sensor. When the pressure sensor 1400 is an absolute pressure sensor, the main processor 1800 uses the pressure sensor 1400 to determine the first pressure value before operating the suction motor 1110 and drives the suction motor 1110 at the target RPM. The second pressure value can be sensed, and the difference between the first pressure value and the second pressure value can be used as the pressure value inside the flow path. When the difference between the first pressure value and the second pressure value is used as the pressure value inside the flow path, internal/external influences other than those of the suction motor 1110 can be minimized.

In step S820, the wireless cleaner 100 may obtain data related to the load of the brush device 2000 through the load detection sensor 1134.

According to an embodiment of the present disclosure, the load detection sensor 1134 is located in the driving circuit 1130 of the motor assembly 1100 and may include, but is limited to, a shunt resistor, a current detection circuit, a load detection circuit, etc. It doesn't work. The main processor 1800 of the cleaner main body 1000 may receive data related to the load of the brush device 2000 from the first processor 1131 in the motor assembly 1100.

According to an embodiment of the present disclosure, the data related to the load of the brush device 2000 is one of the operating current of the brush device 2000, the voltage applied to the brush device 2000, or the power consumption of the brush device 2000. It may include at least one, but is not limited to this. The power consumption of the brush device 2000 may be the power consumption of the motor 2100, and may be calculated as the product of the operating current of the brush device 2000 and the voltage applied to the brush device 2000. If the brush device 2000 includes a lighting device 2300 (e.g., an LED display), the load of the brush device 2000 can be calculated as the sum of the load of the motor 2100 and the load of the lighting device 2300. there is.

In step S830, the cleaner main body 1000 can identify the current usage environment state of the brush device 2000 by applying data related to the flow path pressure and data related to the load of the brush device 2000 to the already learned AI model. there is.

According to one embodiment of the present disclosure, the AI model may be a machine learning algorithm learned to infer the usage status of the brush device 2000. The AI model may be trained or updated (renew, refined) in an external device (eg, a server device, external computing device), or may be trained or updated in the vacuum cleaner main body 1000. For example, the cleaner body 1000 may receive an AI model learned from an external device and store it in the memory 1900, and at least one processor 1001 of the cleaner body 1000 may use the brush device 2000. An AI model for inferring environmental conditions can also be created through learning.

According to an embodiment of the present disclosure, the AI model may include at least one of a Support Vector Machine (SVM) model, a Neural Networks model, a Random Forest model, or a Graphical Model. , but is not limited to this.

The SVM model may be an algorithm that creates a hyper plane with the maximum margin that can classify data in three-dimensional space using a kernel function of the characteristics in the data. The Random Forest model may be an ensemble algorithm that trains multiple decision trees and predicts by combining the results of multiple decision trees. A neural network model may be an algorithm that derives an output by combining weights and transformation functions for each input value. A graphical model may be an algorithm that represents the independence between random variables as a graph. At this time, random variables can be expressed as nodes, and conditional independence between random variables can be expressed as edges.

In the case of the SVM model, the accuracy is relatively high and the response speed is fast, so the operation of the wireless vacuum cleaner 100 can be quickly converted to optimal specifications. Therefore, the case where the AI model is the SVM model will be described below as a main example.

According to an embodiment of the present disclosure, the usage environment state of the brush device 2000 may be related to the environment in which the brush device 2000 is being used during cleaning. For example, the state of the use environment of the brush device 2000 may be the state of the surface to be cleaned on which the brush device 2000 is located, the relative position of the brush device 2000 within the surface to be cleaned, or the state of the surface to be cleaned when the brush device 2000 is It may include at least one of the states mentioned in, but is not limited to this. Here, the surface to be cleaned may refer to a surface that comes into contact with the brush device 2000 during cleaning, such as a floor, bedding, or sofa. The condition of the surface to be cleaned may refer to the material of the surface to be cleaned, and may include, for example, a floor, a general carpet (normal load), a high-density carpet (overload), a mat, etc. The relative position state may include, but is not limited to, the center of the floor, the side of the floor (wall surface), a corner, etc. Hereinafter, for convenience of explanation, the mat state, floor state, carpet state, and lifting state will be described as examples among various usage environment states.

According to an embodiment of the present disclosure, the main processor 1800 of the vacuum cleaner main body 1000 stores data on the flow path pressure obtained from the pressure sensor 1400 and the data obtained from the first processor 1131 in a pre-stored AI model. Data related to the load of the brush device 2000 may be input, and the current usage environment state of the brush device 2000 may be obtained as a result of inference of the AI model.

According to an embodiment of the present disclosure, the load value of the brush device 2000 used as an input value of the AI model may vary depending on the type of the brush device 2000. For example, when the brush device 2000 is the floor brush 502, the main processor 1800 may input operating current data of the floor brush 502 into the AI model corresponding to the floor brush 502. On the other hand, when the brush device 2000 is a multi-brush 501, the power consumption (or operating current and applied voltage) of the multi-brush 501 can be input into the AI model corresponding to the multi-brush 501.

When cleaning a hard floor, the channel pressure and the load of the brush device 2000 are normal, but when cleaning a mat, the channel pressure and the load of the brush device 2000 can increase significantly, and when cleaning a carpet, the channel pressure is Normally, the load on the brush device 2000 may greatly increase, and when the brush device 2000 is in a lifted state, the flow path pressure and the load on the brush device 2000 may be significantly reduced. Accordingly, the cleaner main body 1000 can identify the current usage environment state of the brush device 2000 by applying data related to flow path pressure and data related to the load of the brush device 2000 to a previously learned AI model. For example, when a normal first flow path pressure value and a normal first load value are applied to the AI model, the AI model may output 'hard floor' as the use environment state of the brush device 2000. And, when a high second flow path pressure value and a high second load value are applied to the AI model, the AI model may output 'mat' as the usage environment state of the brush device 2000.

Meanwhile, since the usage environment status of the brush device 2000 may change at any time, the cleaner main body 1000 transmits data related to the flow path pressure and data related to the load of the brush device 2000 at a predetermined period to the previously learned AI model. By applying this, it is possible to continuously monitor the usage environment status of the brush device 2000.

In step S840, the cleaner main body 1000 may adjust the suction force intensity of the suction motor 1110 based on the current usage environment state of the brush device 2000.

Suction power is the electrical power (Input Power) consumed to operate the wireless vacuum cleaner 100, and the strength of the suction power of the suction motor 1110 may be expressed as the power consumption of the suction motor 1110.

According to an embodiment of the present disclosure, when the current use environment of the brush device 2000 is to clean a hard floor, the cleaner main body 1000 adjusts the suction force of the suction motor 2000 to a medium intensity. It can be determined as the 1st century. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 70W.

If the current usage environment state of the brush device 2000 is to clean a mat (or high-density carpet), the cleaner main body 1000 determines the suction power intensity of the suction motor 1110 to be a second intensity lower than the first intensity. You can. When a user cleans a mat or high-density carpet, the brush device 2000 adheres too closely to the surface being cleaned, making it difficult for the user to move the wireless cleaner 100. Accordingly, the cleaner main body 1000 may determine the suction force intensity to be lower when cleaning a mat or high-density carpet than when cleaning a floor. For example, the vacuum cleaner body 1000 may determine the power consumption of the suction motor 1110 to be 58W when cleaning a mat, and may determine the power consumption of the suction motor 1110 to be 40W when cleaning a high-density carpet. According to an embodiment of the present disclosure, the cleaner main body 1000 improves the user's convenience of use by automatically reducing the suction power of the suction motor 1110 when the user moves the brush device 2000 onto a mat or high-density carpet. can do.

When the current usage environment of the brush device 2000 is for cleaning a general carpet, the cleaner main body 1000 may determine the suction power intensity of the suction motor 1110 to be a third intensity higher than the first intensity. It may require greater suction power to pick up dust or debris from a regular carpet than from a hard floor. Accordingly, the vacuum cleaner main body 1000 can determine the suction strength to be higher when cleaning a general carpet than when cleaning a floor. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 115W. According to an embodiment of the present disclosure, the cleaner main body 1000 can improve cleaning performance on carpets by automatically increasing the suction power of the suction motor 1110 when the user moves the brush device 2000 on the carpet. .

According to an embodiment of the present disclosure, the cleaner main body 1000 uses the suction motor 1110 when the current usage environment state of the brush device 2000 is a state in which the brush device 2000 is lifted a certain distance or more from the surface to be cleaned (hereinafter, a lifted state). The suction power intensity can be determined as the minimum intensity. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 40W. When the brush device 2000 is in the lifted state (or idle state), the cleaner body 1000 can extend the use time of the battery 1500 by minimizing the power consumption of the suction motor 1110.

Meanwhile, according to an embodiment of the present disclosure, when the current use environment state of the brush device 2000 is to clean the corner of the wall, the cleaner main body 1000 increases the suction force of the suction motor 1110 to the maximum intensity. You can decide. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 200W. Accordingly, the cleaner body 1000 can improve the cleaning performance at the wall corner by automatically increasing the suction power of the suction motor 1110 when the user cleans the wall corner.

The wireless cleaner 100 according to an embodiment of the present disclosure identifies the current usage environment state of the brush device 2000 using an AI model, and uses the suction motor 1110 according to the usage environment state of the brush device 2000. Since the intensity of suction power is automatically adjusted, the user does not need to replace the brush according to the floor condition when cleaning, the usage time of the battery 1500 can be extended, and cleaning performance and efficiency can be improved. Additionally, the wireless vacuum cleaner 100 can finely adjust the intensity of suction force. For example, in the normal mode, the wireless vacuum cleaner 100 can only select one of 40W, 75W, and 115W for the power consumption of the suction motor 1110 depending on the intensity selected by the user (e.g., weak, medium, strong), but in AI mode In addition to 40W, 75W, and 115W, you can also select intermediate values (e.g. 50W, 60W, 80W, 95W, 130W, 200W), allowing you to finely adjust the suction power strength.

Hereinafter, with reference to FIG. 9, we will look at the SVM model as an example of an AI model for inferring the usage environment state of the brush device 2000.

FIG. 9 is a diagram illustrating an SVM model for inferring the usage environment state of the brush device 2000 according to an embodiment of the present disclosure.

Referring to 910 in FIG. 9, the SVM model can be created through supervised learning. The SVM model is a model that learns with labeled training data and then finds out which group the newly input data belongs to among the groups it was trained on. According to an embodiment of the present disclosure, the SVM model may be learned using the load value of the brush device 2000 and the pressure value of the suction motor 2000 in a specific usage environment state as learning data.

For example, the first flow path pressure value and the first load value of the brush device 2000 obtained when cleaning the floor, the second flow path pressure value and the second load value of the brush device 2000 obtained when cleaning the carpet, The third flow path pressure value and the third load value of the brush device 2000 obtained when cleaning the mat, the fourth flow path pressure value obtained when the brush device 2000 is lifted from the floor, and the fourth load value of the brush device 2000 The load value can be used as learning data. In addition, the SVM model uses the usage environment status (e.g. floor, carpet, mat, lifting, etc.) when the flow path pressure value and the load value of the brush device (2000) are obtained as a label (ground-truth). This can be learned.

According to an embodiment of the present disclosure, the SVM model may be trained in an external device (eg, a server device, an external computing device) or in the vacuum cleaner main body 1000.

Referring to 920 of FIG. 9, the learned SVM model may be composed of at least one hyperplane for classifying the usage environment state. For example, an SVM model for predicting the state of the use environment may be composed of a hyperplane to distinguish between floors and carpets, a hyperplane to distinguish between floors and mats, and a hyperplane to distinguish between carpets and lifts. . Each hyperplane can be expressed by a straight line equation (y = ax + b). In the linear equation, a and b may be parameters, and the parameters may vary depending on the suction force strength of the suction motor 1110, the type of brush device 2000, the state of the cleaner 100 (e.g., amount of dust, etc.), etc. It can be modified. Additionally, the equations of the hyperplane may be higher-order equations (e.g. y = ax ² + b, y = ax ³ + b, etc.).

FIG. 10 is a diagram illustrating an operation of the cleaner main body 1000 to identify the usage environment state of the brush device 2000 using an SVM model according to an embodiment of the present disclosure.

In Figure 10, the usage environment of the brush device 2000 is divided into four types: floor (1011, hf: hard floor), carpet (1012, carpet), mat (1013, mat), and lift (1014, lift). Let's explain this using an example.

When cleaning the floor 1011, the flow path pressure and the load on the brush device 2000 are normal, but when cleaning the mat 1013, the flow path pressure and the load on the brush device 2000 can greatly increase, and the carpet 1012 When cleaning, the flow path pressure is normal, but the load on the brush device 2000 may greatly increase, and when the brush device 2000 is in a lifted state, the flow path pressure and the load on the brush device 2000 may be greatly reduced. Therefore, when a normal flow path pressure value and a normal load value are input to the SVM model, the SVM model may output 'floor 1011' as the usage environment state of the brush device 2000. When a high flow path pressure value and a high load value are input to the SVM model, the SVM model may output 'mat 1013' as the usage environment state of the brush device 2000. When a normal flow path pressure value and a high load value are input to the SVM model, the SVM model may output 'carpet 1012' as the usage environment state of the brush device 2000. When a low flow path pressure value and a low load value are input to the SVM model, the SVM model may output 'lifting 1014' as the usage environment state of the brush device 2000. At this time, the floor 1011 is mapped to the first operating condition, the carpet 1012 is mapped to the second operating condition, the mat 1013 is mapped to the third operating condition, and the lift 1014 is mapped to the fourth operating condition. can be mapped to

According to an embodiment of the present disclosure, the main processor 1800 of the cleaner main body 1000 operates the suction motor 1110 or the brush device 2000 according to the usage environment state of the brush device 2000 identified through the SVM model. Movement can be controlled. For example, when the use environment state of the brush device 2000 is identified as 'Maru 1011', the main processor 1800 of the cleaner main body 1000 sets the operating condition corresponding to the first operating condition (Maru 1011). The suction motor 1110 and the brush device 2000 can be controlled to operate based on the first operation information.

In Figure 10, the SVM model is explained as an example of an AI model for inferring the usage environment state of the brush device 2000, but it is not limited thereto. The vacuum cleaner main body 1000 can receive or learn various types of artificial intelligence models (AI models) from the outside. Hereinafter, a neural network model as an example of an AI model for inferring the usage environment state of the brush device 2000 will be examined with reference to FIG. 11.

FIG. 11 is a diagram illustrating an operation of the cleaner main body 1000 identifying the usage environment state of the brush device 2000 using a neural network model according to an embodiment of the present disclosure.

A neural network model may be composed of multiple neural network layers (e.g., input layer, middle layer (hidden layer), output layer). Each of the plurality of neural network layers has a plurality of weight values, and neural network calculation is performed through calculation between the calculation result of the previous layer and the plurality of weights. The plurality of weights possessed by the plurality of neural network layers can be optimized based on the learning results of the neural network model. For example, a plurality of weights may be updated so that loss or cost values obtained from the neural network model are reduced or minimized during the learning process. Neural networks may include deep neural networks (DNNs), such as Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Restricted Boltzmann Machines (RBMs), and DBNs. (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), or deep Q-Networks (Deep Q-Networks), etc., but are not limited to the above examples.

The neural network model according to an embodiment of the present disclosure may be a model for inferring the use environment state of the brush device 2000. Inference prediction is a technology that judges information and makes logical inferences and predictions, including knowledge/probability-based reasoning, optimization prediction, preference-based planning, and recommendation. Includes.

Functions related to artificial intelligence according to the present disclosure are operated through at least one processor 1001 and memory 1900. At least one processor 1001 may be comprised of one or multiple processors. At this time, at least one processor 1001 may be a general-purpose processor such as a CPU, AP, or DSP (Digital Signal Processor), a graphics-specific processor such as a GPU or VPU (Vision Processing Unit), or an artificial intelligence-specific processor such as an NPU. At least one processor 1001 controls input data to be processed according to predefined operation rules or an artificial intelligence model (eg, neural network model) stored in the memory 1900. Alternatively, when at least one processor 1001 is an artificial intelligence-specific processor, the artificial intelligence-specific processor may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

Predefined operation rules or artificial intelligence models (e.g., neural network models) are characterized by being created through learning. Here, being created through learning means that the basic artificial intelligence model is learned using a large number of learning data by a learning algorithm, thereby creating a predefined operation rule or artificial intelligence model set to perform the desired characteristics (or purpose). It means burden. This learning may be performed in the device itself (e.g., the vacuum cleaner body 1000) on which the artificial intelligence according to the present disclosure is performed, or may be performed through a separate server and/or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

For example, the neural network model according to an embodiment of the present disclosure determines the flow path pressure value, the load value of the brush device 2000, and the usage environment state when the flow path pressure value and the load value of the brush device 2000 are obtained. It can be learned using learning data. For example, the first flow path pressure value and the first load value of the brush device 2000 obtained when cleaning the floor, the second flow path pressure value and the second load value of the brush device 2000 obtained when cleaning the carpet, The third flow path pressure value and the third load value of the brush device 2000 obtained when cleaning the mat, the fourth flow path pressure value obtained when the brush device 2000 is lifted from the floor, and the fourth load value of the brush device 2000 The load value can be used as learning data. In addition, the neural network model uses the state of the usage environment (e.g. floor, carpet, mat, lifting, etc.) when the flow path pressure value and the load value of the brush device (2000) are obtained as a label (ground-truth). This can be learned.

According to an embodiment of the present disclosure, when at least one processor 1001 inputs the flow path pressure value and the load value of the brush device 2000 to the neural network model, the neural network model determines the current usage environment state of the brush device 2000. can be output.

Hereinafter, with reference to FIG. 12, we will look at the random forest model as an example of an AI model for inferring the usage environment state of the brush device 2000.

FIG. 12 is a diagram illustrating an operation of the cleaner main body 1000 to identify the usage environment state of the brush device 2000 using a random forest model according to an embodiment of the present disclosure.

The random forest model may be an ensemble algorithm that trains multiple decision trees and predicts by combining the results of the multiple decision trees. The biggest feature of the random forest model is that decision trees have slightly different characteristics due to randomness. Randomization occurs during the training process of each tree, and bagging and randomized node optimization, an ensemble learning method using random learning data extraction methods, are often used. Bagging is an abbreviation for bootstrap aggregating, and is a method of combining base learners trained on slightly different training data through bootstrapping. Bootstrapping refers to the process of creating a data set of the same size as the original data set by allowing overlap in the given training data.

The random forest model according to an embodiment of the present disclosure uses the flow path pressure value, the load value of the brush device 2000, and the usage environment state when the flow path pressure value and the load value of the brush device 2000 are obtained as learning data. It can be learned using According to an embodiment of the present disclosure, when at least one processor 1001 inputs the current flow path pressure value and the current load value of the brush device 2000 to the random forest model, the random forest model is the current load value of the brush device 2000. You can output the current usage environment status.

Hereinafter, when the wireless cleaner 10 operates in AI mode, the wireless cleaner 10 operates the suction motor 1110 and the brush device 2000 according to the usage environment state of the brush device 2000 deduced by the AI model. The control operation will be examined with reference to FIG. 13.

FIG. 13 is a diagram for explaining AI mode 1302 according to an embodiment of the present disclosure.

Referring to FIG. 13, in the normal mode 1301, the power consumption of the suction motor 1110 and the drum RPM of the brush device 2000 are not automatically adjusted according to the usage environment of the brush device 2000. For example, when the wireless vacuum cleaner 100 operates in the normal mode 1301, if the currently set intensity is 'strong', the usage environment state of the brush device 2000 is either floor (first condition) or general carpet (first condition). 2 condition), overdense carpet (3rd condition), mat (4th condition), lifting (5th condition), or corner (6th condition), the power consumption of the suction motor 1110 is 115W. and the drum RPM can be maintained at 3800rpm. However, depending on the load (friction load on the drum 2200 of the brush device 2000, flow path resistance load due to foreign substances/dust, etc.), the power consumption of the suction motor 1110 and the drum RPM of the brush device 2000 are slightly changed. can be

Referring to FIG. 13, in the AI mode 1302, the power consumption of the suction motor 1110 and the drum RPM of the brush device 2000 may be automatically adjusted according to the usage environment state of the brush device 2000. For example, when the wireless cleaner 100 operates in the AI mode 1302, the wireless cleaner 100 uses the current flow path pressure value and the current load value of the brush device 2000 using an AI model (e.g., SVM model, neural network). model, random forest model, etc.), the current usage environment state of the brush device 2000 can be identified. In addition, the wireless cleaner 100 may determine the drum RPM of the brush device 2000 in addition to the suction force strength of the suction motor 1110 according to the current usage environment status of the brush device 2000.

According to an embodiment of the present disclosure, when the wireless cleaner 100 determines that the use environment state of the brush device 2000 is a floor (first condition), the power consumption of the suction motor 1110 is determined to be 70W, The drum RPM of the brush device 2000 may be determined to be 2000 rpm. When the wireless cleaner 100 determines that the usage environment of the brush device 2000 is a general carpet (second condition), the wireless cleaner 100 determines the power consumption of the suction motor 1110 to be 115W and sets the drum RPM of the brush device 2000 to 115W. can be determined as 3800rpm. When the wireless cleaner 100 determines that the usage environment of the brush device 2000 is a high-density carpet (third condition), the wireless cleaner 100 determines the power consumption of the suction motor 1110 to be 40W and sets the drum RPM of the brush device 2000 to 40W. can be determined as 2000rpm. When the wireless cleaner 100 determines that the usage environment of the brush device 2000 is a mat (fourth condition), the wireless cleaner 100 determines the power consumption of the suction motor 1110 to be 58W and sets the drum RPM of the brush device 2000 to 58W. It can be determined at 1500rpm. When the wireless cleaner 100 determines that the usage environment state of the brush device 2000 is audible (fifth condition), the wireless cleaner 100 determines the power consumption of the suction motor 1110 to be 40W and sets the drum RPM of the brush device 2000 to 40W. It can be determined at 1500rpm. When the wireless cleaner 100 determines that the usage environment of the brush device 2000 is a corner (sixth condition), the wireless cleaner 100 determines the power consumption of the suction motor 1110 to be 115W and sets the drum RPM of the brush device 2000 to 115W. It can be determined at 3800rpm.

According to an embodiment of the present disclosure, when the wireless cleaner 100 operates in the AI mode 1302, cleaning efficiency, usability (operability, noise), damage to the surface to be cleaned (e.g., the drum of the brush device 2000 ( Scratches, scratches, nicks, wear, etc. due to frictional load of the battery 2200) and the usage time of the battery 1500 can be improved. For example, when the wireless vacuum cleaner 100 is not in a cleaning environment that requires strong suction power (e.g., floor, lift), the battery usage time can be increased by lowering the suction power intensity and drum RPM. The wireless cleaner 100 lowers the suction power intensity and drum RPM in a cleaning environment where the brush device 2000 is in too close contact with the surface being cleaned, making it difficult for the user to operate the wireless cleaner 100 (e.g., mat, high-density carpet). By adjusting it, usability (operability) can be improved. When the wireless cleaner 100 is in a cleaning environment that requires strong suction power (e.g., general carpet, corner), the cleaning efficiency (cleaning performance) can be increased by adjusting the suction power intensity to high.

FIG. 14 is a diagram illustrating a method by which the wireless cleaner 100 selects an AI model according to the type of the brush device 2000 according to an embodiment of the present disclosure.

In step S1410, the wireless cleaner 100 may identify the first type of brush device 2000 connected to the cleaner main body 1000.

According to an embodiment of the present disclosure, when the brush device 2000 includes an identification resistor 2500 (see FIG. 6), the wireless cleaner 100 uses the identification resistor 2500 of the brush device 2000, A first type of brush device 2000 can be identified.

For example, when the first processor 1131 of the cleaner main body 1000 determines that the brush device 2000 is coupled to the wireless cleaner 100, the voltage input to the input port of the first processor 1131 Based on the value, the type of brush device 2000 can be identified. Since the operation of the wireless cleaner 100 to identify the type of the brush device 2000 using the identification resistor 2500 of the brush device 2000 has been described above with reference to FIG. 6, redundant description will be omitted.

According to an embodiment of the present disclosure, the first processor 1131 or the main processor 1800 of the cleaner main body 1000 operates the brush device 2000 based on a signal received from the brush device 2000 through signal line communication. The first type can be identified. For example, the brush device 2000 may insert a bit indicating the first type of the brush device 2000 into a data signal transmitted during signal line communication. The operation of the cleaner body 1000 identifying the type of the brush device 2000 based on the signal received from the brush device 2000 will be discussed in more detail later with reference to FIG. 29 .

According to an embodiment of the present disclosure, when the first processor 1131 of the cleaner main body 1000 identifies the first type of the brush device 2000, the first processor 1131 determines the first type of the brush device 2000. 1 Information about the type can be transmitted to the main processor 1800.

In step S1420, the wireless cleaner 100 may select a first AI model corresponding to the first type of the brush device 2000 from among a plurality of AI models.

According to an embodiment of the present disclosure, an AI model for inferring the use environment state of the brush device 2000 may vary depending on the type of the brush device 2000. Accordingly, the cleaner main body 1000 stores a plurality of AI models for each type of brush device 2000 in the memory 1900, and as the type of brush device 2000 is identified as the first type, the type of brush device 2000 A first AI model corresponding to the first type may be selected.

For example, referring to FIG. 15A, when the brush device 2000 is a multi-brush 501, the at least one processor 1001 of the wireless vacuum cleaner 100 generates a first SVM model corresponding to the multi-brush 501. (1510) can be selected. Referring to FIG. 16A, when the brush device 2000 is the floor brush 502, at least one processor 1001 of the wireless cleaner 100 creates a second SVM model 1610 corresponding to the floor brush 502. You can choose. The shape of the hyperplanes 1511, 1512, and 1513 of the first SVM model 1510 corresponding to the multi brush 501 and the hyperplanes 1611 of the second SVM model 1610 corresponding to the ridge brush 502. , 1612, 1613) may have different forms.

In step S1430, the wireless cleaner 100 may apply the suction force intensity of the suction motor 1110 to the selected first AI model to modify the parameter values of the first AI model.

According to an embodiment of the present disclosure, the parameter values of the first AI model may vary depending on the suction force intensity (power consumption) of the suction motor 1110. Accordingly, the main processor 1800 of the cleaner main body 1000, before inputting data related to the flow path pressure and data related to the load of the brush device 2000, to the first AI model, the strength of the suction force of the suction motor 1110 You can modify the parameter values of the first AI model by applying .

According to an embodiment of the present disclosure, when the suction power intensity (power consumption) of the suction motor 1110 changes as the usage environment of the brush device 2000 changes, the main processor 1800 of the cleaner main body 1000 The parameter values of the first AI model may be modified again by applying the changed suction force intensity to the first AI model.

In step S1440, the wireless cleaner 100 applies data related to flow path pressure and data related to the load of the brush device 2000 to the first AI model whose parameter values have been modified to determine the current usage environment status of the brush device 2000. can be identified.

According to an embodiment of the present disclosure, the main processor 1800 of the cleaner main body 1000 may obtain data regarding the flow path pressure measured by the pressure sensor 1400. The main processor 1800 of the cleaner main body 1000 may obtain data related to the load of the brush device 2000 through the load detection sensor 1134. And the main processor 1800 of the cleaner main body 1000 provides data on flow path pressure and the brush device 2000 to the first AI model whose parameter values are modified according to the suction force intensity (power consumption) of the suction motor 1100. By applying data related to the load, the current usage environment state of the brush device 2000 can be identified.

For example, when the first flow path pressure value and the first load value are applied to the AI model whose parameter values have been modified, the AI model whose parameter values have been modified has a 'hard floor' as the use environment state of the brush device 2000. )' can be output, and when the second flow path pressure value and the second load value are applied to the AI model whose parameter values have been modified, the AI model whose parameter values have been modified is ' You can print ‘mat’.

Since step S1440 corresponds to step S830 of FIG. 8, detailed description will be omitted.

In step S1450, the wireless cleaner 100, based on the current usage environment state of the brush device 2000, determines the suction force intensity of the suction motor 1110 or the RPM of the rotating brush of the brush device 2000 (hereinafter, also referred to as target RPM). ) can be determined.

According to an embodiment of the present disclosure, when the current use environment of the brush device 2000 is to clean a hard floor, the cleaner main body 1000 adjusts the suction force of the suction motor 2000 to a medium intensity. The first intensity may be determined, and the target RPM of the brush device 2000 may be determined as an intermediate level. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 70W, and the target RPM of the brush device 2000 may be determined to be 2000rpm.

If the current usage environment state of the brush device 2000 is to clean a mat (or high-density carpet), the cleaner main body 1000 determines the suction power intensity of the suction motor 1110 to be a second intensity lower than the first intensity. You can. When a user cleans a mat or high-density carpet, the brush device 2000 adheres too closely to the surface being cleaned, making it difficult for the user to move the wireless cleaner 100. Accordingly, the cleaner main body 1000 may determine the suction force intensity to be lower when cleaning a mat or high-density carpet than when cleaning a floor. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 58W. Additionally, when the current usage environment of the brush device 2000 is a mat cleaning state, the cleaner body 1000 may determine the target RPM of the brush device 2000 to be the lowest (eg, 1000 rpm). According to an embodiment of the present disclosure, the cleaner main body 1000 automatically reduces the suction force intensity of the suction motor 1110 and the rotation speed of the brush device 2000 when the user moves the brush device 2000 onto the mat, User convenience can be improved.

When the current usage environment of the brush device 2000 is for cleaning a general carpet, the cleaner main body 1000 may determine the suction power intensity of the suction motor 1110 to be a third intensity higher than the first intensity. It may require greater suction power to suck up dust or foreign substances from a regular carpet than from a floor. Accordingly, the cleaner main body 1000 can determine the suction power strength to be higher when cleaning a general carpet than a floor, and the target RPM of the brush device 2000 can also be determined to be high. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 115W, and the target RPM of the brush device 2000 may be determined to be 3800rpm. According to an embodiment of the present disclosure, the cleaner main body 1000 automatically increases the suction force intensity of the suction motor 1110 and the rotation speed of the brush device 2000 when the user moves the brush device 2000 on the carpet, It can improve cleaning performance on carpets.

According to an embodiment of the present disclosure, the cleaner main body 1000 uses the suction motor 1110 when the current usage environment state of the brush device 2000 is a state in which the brush device 2000 is lifted a certain distance or more from the surface to be cleaned (hereinafter, a lifted state). The suction force intensity may be determined as the minimum intensity, and the target RPM of the brush device 2000 may be determined as the lowest level. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 40W, and the target RPM of the brush device 2000 may be determined to be 1500rpm. When the brush device 2000 is in a lifted state (or idle state), the cleaner body 1000 can reduce unnecessary power consumption by reducing the power consumption of the suction motor 1110 and the rotation speed of the brush device 2000. , the usage time of the battery 1500 may also be extended.

Meanwhile, according to an embodiment of the present disclosure, when the current use environment state of the brush device 2000 is to clean the corner of the wall, the cleaner main body 1000 increases the suction force of the suction motor 1110 to the maximum intensity. You can decide. For example, the cleaner main body 1000 may determine the power consumption of the suction motor 1110 to be 200W. Accordingly, the cleaner body 1000 can improve the cleaning performance at the wall corner by automatically increasing the suction power of the suction motor 1110 when the user cleans the wall corner.

In step S1460, the wireless cleaner 100 may adjust the suction force intensity of the suction motor 1110 and the RPM of the rotating brush of the brush device 2000.

According to an embodiment of the present disclosure, the main processor 1800 may transmit the determined suction force intensity and the target RPM of the brush device 2000 to the first processor 1131. At this time, the first processor 1131 may adjust the suction force intensity of the suction motor 1110 to the determined suction force intensity. And the first processor 1131 can transmit the target RPM of the brush device 2000 to the second processor 2410 by controlling the operation of the first sub-position element 1132 connected to the signal line 30. According to an embodiment of the present disclosure, the first processor 1131 may transmit the target RPM of the brush device 2000 to the second processor 2410 using UART or I2C. The operation of the first processor 1131 transmitting a signal to the second processor 2410 will be described in detail later with reference to FIGS. 20 to 24 and 27 to 34. When receiving the target RPM of the brush device 2000 from the cleaner main body 1000, the second processor 2410 may adjust the drum RPM of the brush device 2000 to the target RPM.

Hereinafter, with reference to FIGS. 15A to 16C, the wireless cleaner 100 applies the suction force strength of the suction motor 1110 to the first AI model corresponding to the first type of the brush device 2000 to obtain the power of the first AI model. Let's take a closer look at the operation of modifying parameter values.

FIG. 15A is a diagram for explaining the first SVM model 1510 corresponding to the multi brush 501 according to an embodiment of the present disclosure. FIG. 15B is a diagram illustrating an operation in which parameter values of the first SVM model 1510 corresponding to the multi-brush 501 are modified according to a change in power consumption of the suction motor 1110. FIG. 15C is a diagram illustrating an operation in which parameter values of the first SVM model 1510 corresponding to the multi-brush 501 are modified according to a change in power consumption of the suction motor 1110.

15A to 15C illustrate the case where the use environment of the brush device 2000 is divided into four types, such as hard floor (hf), carpet, mat, and lift. I decided to do it.

The first SVM model 1510 corresponding to the multi brush 501 shown in FIG. 15A includes a first hyperplane 1511 for distinguishing the carpet from the mat or floor, and a second hyperplane for distinguishing the floor from the mat ( 1512), and may be composed of a third second plane (1513) to distinguish between carpet and lifting. Each hyperplane can be expressed as a straight line equation (y = ax + b), and in the straight line equation, a and b can be parameters. The parameter values of each of the first second plane 1511, the second second plane 1512, and the third second plane 1513 may correspond to the case where the power consumption of the suction motor 1110 is 40W.

Referring to FIG. 15B, when the power consumption of the suction motor 1110 changes from 40W to 58W, the parameter values of the first SVM model 1510 may be modified. The 1-1 SVM model (1520) with modified parameter values includes a 1-1 second plane (1521) for distinguishing between floors and carpets, a 2-1 second plane (1522) for distinguishing between mats and carpets, and a carpet It may be composed of a 3-1 second plane (1523) to distinguish between and lifting. The 1-1 second plane 1521 may have a smaller slope (a) compared to the 1st second plane 1511, and the 2-1 second plane 1522 may have a slope (a) compared to the 2nd second plane 1512. a) can become larger.

Referring to FIG. 15C, when the power consumption of the suction motor 1110 changes from 40W to 115W, the parameter values of the first SVM model 1510 may be modified. The 1-2 SVM model (1530) with modified parameter values consists of a 1-2 second plane (1531) for distinguishing between floors and carpets, and a 3-2 second plane (1533) for distinguishing between carpets and lifting. It can be. Compared to the first SVM model 1510, the 1-2 SVM model 1530 may not include a second hyperplane 1512 for distinguishing the floor from the mat. For example, when the power consumption of the suction motor 1110 changes from 40W to 115W, the slope a of the second second plane 1512 may be modified to 0.

FIG. 16A is a diagram for explaining a second SVM model 1610 corresponding to the floor brush 502 according to an embodiment of the present disclosure. FIG. 16B is a diagram illustrating an operation in which parameter values of the second SVM model 1610 corresponding to the floor brush 502 are modified according to a change in power consumption of the suction motor 1110. FIG. 16C is a diagram illustrating an operation in which parameter values of the second SVM model 1610 corresponding to the floor brush 502 are modified according to a change in power consumption of the suction motor 1110.

16A to 16C illustrate an example in which the use environment of the brush device 2000 is divided into four types: hard floor (hf), carpet (carpet), mat, and lift. I decided to do it.

The second SVM model 1610 corresponding to the floor brush 502 shown in FIG. 16A includes a first hyper-plane 1611 for distinguishing the floor from the mat, and a second hyper-plane 1612 for distinguishing the floor from the carpet. , It may be composed of a third second plane 1613 to distinguish between the carpet and the lifting. Each hyperplane can be expressed as a straight line equation (y = ax + b), and in the straight line equation, a and b can be parameters. The parameter values of each of the first second plane 1611, the second second plane 1612, and the third second plane 1613 may correspond to the case where the power consumption of the suction motor 1110 is 40W.

Referring to FIG. 16b, when the power consumption of the suction motor 1110 changes from 40W to 58W, the parameter values of the second SVM model 1610 may be modified. The 2-1 SVM model (1620) with modified parameter values includes a 1-1 second plane (1621) for distinguishing between a floor and a mat, a 2-1 second plane (1622) for distinguishing between a floor and a carpet, and a carpet It may be composed of a 3-1 second plane (1623) to distinguish between and lifting.

Referring to FIG. 16C, when the power consumption of the suction motor 1110 changes from 40W to 115W, the parameter values of the second SVM model 1610 may be modified. The 2-2 SVM model (1630) with modified parameter values includes a 1-2 second plane (1631) for distinguishing between floors and mats, a 2-2 second plane (1632) for distinguishing between floors and carpets, and carpets. It may be composed of a 3-2 second plane (1633) to distinguish between and lifting.

FIG. 17 is a flowchart illustrating a method by which the wireless cleaner 100 identifies a state transition in the usage environment of the brush device 2000 according to an embodiment of the present disclosure.

In step S1710, the wireless cleaner 100 may obtain data about the flow path pressure measured by the pressure sensor 1400.

According to an embodiment of the present disclosure, at least one processor 1001 of the cleaner main body 1000 may acquire the pressure value measured by the pressure sensor 1400. For example, the main processor 1800 may receive the pressure value measured by the pressure sensor 1400 from the pressure sensor 1400 through I2C communication. The pressure sensor 1400 is located within the flow path and can measure the pressure inside the flow path (flow path pressure). For example, the pressure sensor 1400 may be located within the suction duct 40 or the motor assembly 1100, but is not limited thereto.

In step S1720, the cleaner main body 1000 may obtain data related to the load of the brush device 2000 through the load detection sensor 1134.

According to an embodiment of the present disclosure, the load detection sensor 1134 is located in the driving circuit 1130 of the motor assembly 1100 and may include, but is limited to, a shunt resistor, a current detection circuit, a load detection circuit, etc. It doesn't work. The main processor 1800 of the cleaner main body 1000 may receive data related to the load of the brush device 2000 from the first processor 1131 in the motor assembly 1100.

In step S1730, the cleaner main body 1000 applies data related to flow path pressure and data related to the load of the brush device 2000 to a previously learned AI model to identify the current usage environment state of the brush device 2000. there is.

For example, the main processor 1800 of the vacuum cleaner body 1000 stores data on the flow path pressure obtained from the pressure sensor 1400 and the brush device 2000 obtained from the first processor 1131 in a pre-stored AI model. Data related to the load can be input, and the current usage environment status (e.g., floor, mat, carpet, lifting, corner) of the brush device 2000 can be obtained as an inference result of the AI model.

Since steps S1710 to S1730 correspond to steps S810 to S830 of FIG. 8, detailed description will be omitted.

In step S1740, the wireless cleaner 100 may determine whether the current usage environment state of the brush device 2000 has transitioned. For example, the main processor 1800 of the cleaner main body 1000 applies data related to flow path pressure and data related to the load of the brush device 2000 to the AI model to determine the usage environment state of the brush device 2000. Transitions (hereinafter referred to as state transitions) can be identified.

According to an embodiment of the present disclosure, when the AI model is an SVM model, the hyperplane for inferring the current usage environment state and the hyperplane for inferring the state transition may be different. For example, referring to Figure 18, a first second plane 1810 that distinguishes a floor from a carpet is a 1-1 second plane 1801 that identifies a state transition from a floor to a carpet, and a first second plane 1801 that identifies a state transition from a floor to a carpet. It may be different from the 1-2 second plane 1802 for identifying state transitions. That is, when the load on the brush device 2000 slightly increases while the wireless vacuum cleaner 100 is cleaning the floor, the current usage environment state may be inferred as a carpet based on the first second plane 1810. However, based on the 1-1 second plane 1801, the current usage environment state can be inferred to be the floor. In this case, the wireless vacuum cleaner 100 may determine that the usage environment state has not transitioned from the floor to the carpet.

On the other hand, if the current usage environment state is inferred to be a carpet based on the first second plane 1810, and the current usage environment state is inferred to be a carpet based on the 1-1 second plane 1801, the wireless vacuum cleaner ( 100), it may be determined that the use environment state has transitioned from floor to carpet.

In step S1750, if a state transition is not identified, the wireless vacuum cleaner 100 may maintain the current suction force intensity and the current RPM of the rotating brush.

In step S1760, when a state transition is identified, the wireless vacuum cleaner 100 may determine the suction force intensity and the RPM of the rotating brush (also referred to as target RPM) corresponding to the transitioned usage environment state.

For example, when a state transition from floor to carpet is identified, the main processor 1800 of the vacuum cleaner body 1000 may determine the suction force intensity and the RPM of the rotating brush to be higher than the current state. On the other hand, when the state transition from carpet to floor is identified, the main processor 1800 of the vacuum cleaner body 1000 may determine the suction force intensity and the RPM of the rotating brush to be lower than the current state.

In step S1770, the wireless cleaner 100 may adjust the suction force intensity of the suction motor 1110 and the RPM of the rotating brush.

According to an embodiment of the present disclosure, the main processor 1800 of the cleaner main body 1000 may transmit the determined suction force intensity and the target RPM of the brush device 2000 to the first processor 1131. At this time, the first processor 1131 may adjust the suction force intensity of the suction motor 1110 to the determined suction force intensity. And the first processor 1131 can transmit the target RPM of the brush device 2000 to the second processor 2410 by controlling the operation of the first sub-position element 1132 connected to the signal line 30. According to an embodiment of the present disclosure, the first processor 1131 may transmit the target RPM of the brush device 2000 to the second processor 2410 using UART or I2C.

Hereinafter, the operation of the main processor 1800 transmitting the target RPM to the second processor 2410 through the first processor 1131 will be described in more detail with reference to FIG. 19.

FIG. 19 is a diagram illustrating an operation in which the main processor 1800 communicates with the second processor 2410 through the first processor 1131 according to an embodiment of the present disclosure.

Referring to FIG. 19, the main processor 1800 uses a pre-stored AI model (e.g., SVM model) to determine the RPM (power consumption, intensity of suction force) of the suction motor 1110 and the drum of the brush device 2000. (2200) target RPM, restraint level, etc. can be determined. The main processor 1800 may determine the RPM of the suction motor 1110 based on the user's suction intensity control input through the user interface 1700.

In step S1910, the main processor 1800 stores data including the RPM (power consumption, strength of suction force) of the suction motor 1110, the target RPM of the drum 2200 of the brush device 2000, the target restraint level, etc. It can be transmitted to the first processor 1131. For example, the main processor 1800 may transmit data to the first processor 1131 using UART, but is not limited to this.

In step S1920, the first processor 1131 may transmit data related to control of the brush device 2000 among the data received from the main processor 1800 to the second processor 2410 through signal line communication. For example, the first processor 1131 may transmit data including the target RPM and target constraint level of the drum 2200 to the second processor 2410. At this time, the first processor 1131 may transmit data indicating operating conditions corresponding to the target RPM and target restraint level to the second processor 2410. The operation of the first processor 1131 and the second processor 2410 to transmit and receive data representing operating conditions will be discussed in detail later with reference to FIG. 21 .

When the second processor 2410 of the brush device 2000 receives control-related data from the first processor 1131, it can control the operation of the brush device 2000. For example, the second processor 2410 may change the RPM of the drum 2200 to the target RPM or change the restraint level to the target restraint level.

In step S1930, when receiving control-related data from the first processor 1131, the second processor 2410 of the brush device 2000 sends operation status feedback data to the first processor 1131 through signal line communication. Can be transmitted. The operation status feedback data may include, but is not limited to, whether the brush device 2000 has any abnormalities, the current RPM of the drum 2200, etc.

In step S1940, when the first processor 1131 of the cleaner main body 1000 receives operation state feedback data from the second processor 2410 of the brush device 2000, the first processor 1131 sends the second processor 2410 to the main processor 1800. ) operation status feedback data can be transmitted. The first processor 1131 may transmit operational status feedback data of the second processor 2410 to the main processor 1800 through UART. In addition to the operation status feedback data of the second processor 2410, the first processor 1131 determines whether the suction motor 1110 is abnormal, the strength of the suction force of the suction motor 1110, the load of the brush device 2000, and the brush device 2000. ) may be further transmitted to the main processor 1800.

The main processor 1800 may determine the operating state of the suction motor 1110 and the operating state of the brush device 2000 based on the data received from the first processor 1131. Additionally, the main processor 1800 may monitor the usage environment state of the brush device 2000 and continuously control the operation of the brush device 2000 according to the usage environment state of the brush device 2000. For example, by repeatedly performing steps S1910 to S1940, the first processor 1131 can transfer the control command of the main processor 1800 to the second processor 2410.

Below, with reference to FIG. 20 , an example of a circuit for signal line communication between the first processor 1131 and the second processor 2410 will be described in detail.

FIG. 20 is a diagram illustrating a circuit for signal line communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure. In Figure 20, for convenience of explanation, the case where A is 330KΩ, B is 330KΩ, and C is 82KΩ will be described as an example.

The first processor 1131 may identify the type of brush device 2000 based on the voltage input to the input port (AD port). For example, the AD port input voltage of the first processor 1131 is 2.785V ( ), the first processor 1131 can identify that the multi-brush 501 with an identification resistance 2500 of 330KΩ corresponding to the AD port input voltage of 2.785V is connected (see table 700 in FIG. 7) ).

If the brush device 2000 coupled to the wireless cleaner 100 is identified as a multi-brush 501 including the driving circuit 2400, the cleaner main body 1000 can perform signal line communication with the brush device 2000. there is.

The first processor 1131 of the cleaner main body 1000 may receive a signal using an input port and transmit a signal using an output port. For example, when the first processor 1131 outputs a low signal through the output port, the first switch element 1132 may be turned off. As the first switch element 1132 is turned off, the voltage of the signal line 30 is about 14V ( ), it can be in High state. When the voltage of the signal line 30 is about 14V and is greater than 5V, the PNP transistor 2425 is turned off, and a low (0V) signal can be input to the input port of the second processor 2410. Conversely, when the first processor 1131 outputs a high signal through the output port, the first switch element 1132 may be turned on. As the first switch element 1132 is turned on, the voltage of the signal line 30 changes to 0V (GND) and may be in a low state. When the voltage of the signal line 30 is 0V, the PNP transistor 2425 is turned on, and a high signal (about 4.8V) can be input to the input port of the second processor 2410. That is, when the first processor 1131 outputs a low signal through the output port, the low signal is input to the input port of the second processor 2410, and the first processor 1131 outputs a high signal through the output port. In this case, a high signal may also be input to the input port of the second processor 2410.

The second processor 2410 of the brush device 2000 may receive a signal using an input port and transmit a signal using an output port. For example, when the second processor 2410 outputs a high signal through the output port, the second switch element 2435 may be turned on. As the second switch element 2435 is turned on, the voltage of the signal line 30 changes to 0V (GND) and may be in a low state. When the voltage of the signal line 30 is 0V, a low signal (0V) may be input to the input port of the first processor 1131. Conversely, when the second processor 2410 outputs a low signal through the output port, the second switch element 2435 may be turned off. As the second switch element 2435 is turned off, the voltage of the signal line 30 is about 14V ( ), it can be in High state. When the voltage of the signal line 30 is about 14V, 2.785V can be input to the input port of the first processor 1131. At this time, the driving circuit 1130 of the cleaner main body 1000 includes a voltage divider 1137, so the high voltage (14V) of the signal line 30 is distributed and 2.785V is input to the input port of the first processor 1131. You can. That is, when the second processor 2410 outputs a high signal through the output port, a low signal (0V) is input to the input port of the first processor 1131, and the second processor 2410 outputs a low signal through the output port. When outputting a signal, 2.785V (approximately 2.8V) may be input to the input port of the first processor 1131.

In FIG. 20 , the case in which the PNP transistor 2425 is included as a switch element in the driving circuit 2400 of the brush device 2000 is described as an example, but the present invention is not limited thereto. For example, a P-channel FET may be used as a switch element instead of the PNP transistor 2425.

According to an embodiment of the present disclosure, when the first processor 1131 receives a signal from the second processor 2410, the driving circuit 1130 for signal line communication of the cleaner main body 1000 uses a voltage divider 1137. Since it includes, stable signal transmission is possible by minimizing the noise effect of the signal line 30. That is, since the driving circuit 1130 of the cleaner main body 1000 includes the voltage divider 1137, even if the noise voltage is applied to the signal line 30, the noise voltage is also distributed and the input port (AD) of the first processor 1131 port) can be entered. This will be explained using the case where noise of ±1.5V occurs as an example.

In a typical circuit, the AD port voltage when no noise occurs (normal) is 3.3V, and when noise of ±1.5V occurs, the AD port voltage can range from 1.8V to 4.8V. That is, if noise occurs in a general circuit, the AD port voltage may exceed the maximum voltage of the microcomputer's AD port (e.g., 3.3V), so the first processor 1131 may be easily damaged. Additionally, in a general circuit, a high signal may be mistakenly recognized as a low signal (or a low signal as a high signal) due to noise (±1.5V).

However, according to the driving circuit 1130 according to an embodiment of the present disclosure, the input port voltage of the first processor 1131 in a situation (normal) in which no noise occurs may be 2.78V, and may be ±1.5V. Even if noise occurs, the input port voltage of the first processor 1131 may be 2.49V to 3.08V. That is, according to the driving circuit 1130 including the voltage divider 1137, even if noise occurs, the input port voltage of the first processor 1131 does not exceed the maximum voltage of the microcomputer's AD port (e.g., 3.3V), so robust Signal transmission is possible. In addition, even if noise of ±1.5V occurs on the signal line 30, it only affects the input port of the first processor 1131 by about ±0.3V, causing signal distortion (e.g., misrecognition of a high signal as a low signal, Alternatively, misrecognition of a low signal as a high signal can be minimized.

Hereinafter, signal transmission between the cleaner main body 1000 and the brush device 2000 will be examined in more detail with reference to FIGS. 21 to 24.

FIG. 21 is a diagram for explaining a data format included in a signal transmitted between the cleaner main body 1000 and the brush device 2000 according to an embodiment of the present disclosure.

Referring to FIG. 21, in each of the memory 1900 of the cleaner main body 1000 and the memory of the brush device 2000, operation information 2102 and operation conditions ( A lookup table 2110 containing data 2103 representing 2101 may be stored. At this time, the operation information 2102 of the wireless vacuum cleaner 100 corresponding to the operating condition 2101 includes the power consumption of the suction motor 1110, the drum RPM of the brush device 2000, and the restraint level of the brush device 2000 ( Trip level), etc., but is not limited thereto. Additionally, data 2103 representing the operating condition 2101 may be 8-bit data, but is not limited thereto. For example, data 2103 representing the operating condition 2101 may be 5-bit data.

According to an embodiment of the present disclosure, when the data 2103 representing the operating condition 2101 consists of 8 bits, the data 2103 representing the operating condition 2101 includes one start bit and three commands. It may consist of a (command) bit, three parity bits, and one stop bit. In FIG. 21, since there are three command bits, the operating conditions 2301 are divided into eight. However, if the number of command bits increases, the operating conditions may increase.

The operating conditions 2301 include the type of brush device 2000, the state of the environment in which the brush device 2000 is used (e.g., the state of the surface to be cleaned (floor, carpet, mat, corner, etc.), the state lifted from the surface to be cleaned, etc.), It can be classified according to the abnormality of the suction motor 1110, etc.

Referring to the look-up table 2110 of FIG. 21, the first operating condition indicates when the state of the surface to be cleaned is a floor, and the first operating information under the first operating condition is “power consumption of the suction motor 1110: It may be 70W, drum RPM: 2000, trip level: 4.0A”. That is, when the main processor 1800 identifies that the current state of the surface to be cleaned is a floor, the wireless cleaner 100 may decide to operate based on the first operation information corresponding to the first operation condition. Accordingly, the main processor 1800 may transfer information about the first operating condition to the first processor 1131, and the first processor 1131 may check the first operating information corresponding to the first operating condition and inhale. The power consumption of the motor 1110 can be adjusted to 70W. Additionally, the first processor 1131 may transmit data (00011101) representing the first operating condition to the second processor 2410. When receiving data (00011101) representing the first operating condition, the second processor 2410 checks the first operation information corresponding to the first operating condition, adjusts the drum RPM to 2000 rpm, and sets the restraint level to 4.0A. It can be set to .

The second operation condition indicates when the state of the surface to be cleaned is a carpet (normal load), and the second operation information under the second operation condition is "power consumption of suction motor 1110: 115W, drum RPM: 3800, restraint. Trip level: may be 4.9A". That is, when the main processor 1800 identifies that the current state of the surface to be cleaned is a carpet (normal load), the wireless cleaner 100 may decide to operate based on the second operation information corresponding to the second operation condition. . Accordingly, the main processor 1800 may transfer information about the second operating condition to the first processor 1131, and the first processor 1131 may check the second operating information corresponding to the second operating condition and inhale. The power consumption of the motor 1110 can be adjusted to 115W. Additionally, the first processor 1131 may transmit data (00101011) representing the second operating condition to the second processor 2410. When receiving data (00101011) representing the second operating condition, the second processor 2410 checks the second operation information corresponding to the second operating condition, adjusts the drum RPM to 3800 rpm, and sets the restraint level to 4.9. It can be set to A. When the surface to be cleaned is a carpet (normal load) rather than a floor, the power consumption (suction force intensity) of the suction motor 1110 is greater, so the restraint level can also be increased from 4.0A to 4.9A. The restraint level is to prevent overload of the brush device 2000, and when the load of the brush device 2000 reaches 4.9A, the motor 2100 may stop.

The third operation condition indicates when the state of the surface to be cleaned is a carpet (overload, high-density carpet), and the third operation information under the third operation condition is "power consumption of suction motor 1110: 40W, drum RPM: 2000. , Trip level: may be 4.9A". When the state of the surface to be cleaned is a carpet (overload) compared to a carpet (normal load), the brush device 2000 may come into excessive contact with the surface to be cleaned, so the cleaner main body 1000 lowers the power consumption of the suction motor 1110 and , the drum RPM of the brush device 2000 can also be lowered. If the main processor 1800 identifies that the current state of the surface to be cleaned is carpet (overload), the wireless cleaner 100 may decide to operate based on the third operation information corresponding to the third operation condition. Accordingly, the main processor 1800 may transfer information about the third operating condition to the first processor 1131, and the first processor 1131 may check the third operation information corresponding to the third operating condition and inhale. The power consumption of the motor 1110 can be adjusted to 40W. Additionally, the first processor 1131 may transmit data (00111001) representing the third operating condition to the second processor 2410. When receiving data (00111001) representing the third operating condition, the second processor 2410 checks the third operation information corresponding to the third operating condition, adjusts the drum RPM to 2000 rpm, and sets the restraint level to 4.9. It can be set to A.

The fourth operating condition indicates when the brush device 2000 is lifted from the surface to be cleaned (hereinafter also referred to as lifted state), and the fourth operation information under the fourth operating condition is “power consumption of the suction motor 1110.” : 40W, drum RPM: 1000, trip level: 4.0A". Since the strength of the suction power does not need to be large when in the lifted state, the cleaner main body 1000 lowers the power consumption of the suction motor 1110 to the lowest power consumption (e.g. 40W), and the drum RPM of the brush device 2000 is also set to the lowest RPM. It can be lowered to (1000rpm). If the main processor 1800 identifies that the current state of the surface to be cleaned is the lifted state, the wireless cleaner 100 may decide to operate based on the fourth operation information corresponding to the fourth operation condition. Accordingly, the main processor 1800 may transfer information about the fourth operating condition to the first processor 1131, and the first processor 1131 may check the fourth operation information corresponding to the fourth operating condition and inhale. The power consumption of the motor 1110 can be adjusted to 40W. Additionally, the first processor 1131 may transmit data (01000111) representing the fourth operating condition to the second processor 2410. When receiving data (01000111) indicating the fourth operating condition, the second processor 2410 checks the fourth operation information corresponding to the fourth operating condition, adjusts the drum RPM to 1000 rpm, and sets the restraint level to 4.0. It can be set to A.

The fifth operation condition indicates when the state of the surface to be cleaned is a mat, and the fifth operation information under the fifth operation condition is "power consumption of suction motor 1110: 58W, drum RPM: 1000, trip level" ): 4.9A". That is, if the main processor 1800 identifies that the current state of the surface to be cleaned is a mat, the wireless cleaner 100 may decide to operate based on the fifth operation information corresponding to the fifth operation condition. Therefore, the main processor 1800 can transmit information about the fifth operating condition to the first processor 1131, and the first processor 1131 checks the fifth operating information corresponding to the fifth operating condition and inhales. The power consumption of the motor 1110 can be adjusted to 58W. Additionally, the first processor 1131 may transmit data (01010101) representing the fifth operating condition to the second processor 2410. When receiving data (01010101) representing the fifth operating condition, the second processor 2410 checks the fifth operation information corresponding to the fifth operating condition, adjusts the drum RPM to 1000 rpm, and sets the restraint level to 4.9A. It can be set to .

The sixth operating condition indicates when the operation of the cordless vacuum cleaner 100 should be stopped, and the sixth operating information for the sixth operating condition is “power consumption of suction motor 1110: 58W, drum RPM: 0, Trip level: may be 0A. For example, the cleaner body 1000 controls the operation of the brush motor 2100 as it identifies an abnormality in the motor 2100 (hereinafter also referred to as the brush motor 2100) included in the brush device 2000. You can decide to stop it. The main processor 1800 may identify an abnormality in the brush motor 2100 and stop the operation of the brush motor 2100, and the first processor 1131 may identify an abnormality in the brush motor 2100 to stop the brush motor 2100. ) can also stop the operation. When it is decided to stop the operation of the brush motor 2100, the first processor 1131 controls the on/off operation of the first switch element 1132 to signal ( Example: Data (01100011) representing the sixth operating condition can be transmitted to the second processor 2410 of the brush device 2000 through the signal line 30. When receiving data (01100011) indicating the sixth operating condition, the second processor 2410 generates sixth operation information (drum RPM: 0, trip level: 0A) corresponding to the sixth operating condition. After confirmation, the operation of the brush motor 2100 can be stopped.

Hereinafter, with reference to FIG. 22, the first processor 1131 of the cleaner main body 1000 transmits 8-bit data (01010101) indicating the fifth operating condition (mat) to the second processor 2410 of the brush device 2000. ) Let's look in detail at an example of transmitting.

FIG. 22 is a diagram for explaining an operation of transmitting a signal from the cleaner main body 1000 to the brush device 2000 according to an embodiment of the present disclosure.

In FIG. 22, the case where the cleaner main body 1000 transmits an 8-bit signal (01010101) representing the fifth operating condition to the brush device 2000, and the transmission time is 10 ms per bit will be described as an example. .

According to the communication protocol according to an embodiment of the present disclosure, 0 and 1 can be distinguished based on the state of the signal line 30. For example, 0 may be transmitted when the signal line 30 is in a low state (L), and 1 may be transmitted when the signal line 30 is in a high state (H). Accordingly, the first processor 1131 turns on the first switch element 1132 to apply a first level voltage lower than the threshold to the signal line 30 to transmit code 0, and the first switch element 1132 Code 1 can be transmitted by turning off 1132 so that a second level voltage higher than the threshold is applied to the signal line 30.

The first processor 1131 may set the state of the signal line 30 to LHLHLHLH in order to transmit 01010101, which represents the fifth operating condition, to the second processor 2410. For example, the first processor 1131 outputs a high signal (5V or 3.3V) through the output port for the first 10 ms to turn on the first switch element 1132 and change the state of the signal line 30 to low ( 0V), and output a low signal (0V) through the output port for the next 10 ms to turn off the first switch element 1132 and make the signal line 30 high (14V) four times. It can be repeated. In this case, the first processor 1131 may transmit 01010101 to the second processor 2410 for 80 ms. While the first processor 1131 transmits a signal, the output port of the second processor 2410 may be maintained in a low (0V) state.

When receiving the first signal (01010101) indicating the fifth operating condition from the cleaner main body 1000, the second processor 2410 determines the fifth operating condition from the lookup table 2110 stored in the memory of the brush device 2000. The corresponding fifth operation information (power consumption of suction motor 1110: 58W, drum RPM: 1000, trip level: 4.9A) can be confirmed. And the second processor 2410 can adjust the drum RPM to 1000 rpm and set the trip level to 4.9A. Thereafter, the second processor 2410 may transmit a second signal indicating the current state to the first processor 1131 in response to the first signal. For example, since the second processor 2410 changed the settings based on the fifth operation information corresponding to the fifth operating condition, it sends a second signal (e.g., 01010101) indicating that the current state is the state corresponding to the fifth operating condition. Can be transmitted to the first processor 1131. An operation in which the second processor 2410 transmits a second signal (eg, 01010101) indicating the current state to the first processor 1131 will be described with reference to FIG. 23.

FIG. 23 is a diagram for explaining an operation of transmitting a signal from the brush device 2000 to the cleaner main body 1000 according to an embodiment of the present disclosure.

In Figure 23, the brush device 2000 transmits a second signal (e.g., 01010101) indicating that the current state corresponds to the fifth operating condition to the cleaner main body 1000, and has a transmission time of 10 ms per bit. Let's explain with an example.

According to the communication protocol according to an embodiment of the present disclosure, 0 and 1 can be distinguished based on the state of the signal line 30. For example, 0 may be transmitted when the signal line 30 is in a low state (L), and 1 may be transmitted when the signal line 30 is in a high state (H). Accordingly, the second processor 2410 turns on the second switch element 2435 to apply a first level voltage lower than the threshold to the signal line 30 to transmit code 0, and the second switch element 2435 Code 1 can be transmitted by turning off 2435 so that a second level voltage higher than the threshold is applied to the signal line 30.

The second processor 2410 sets the state of the signal line 30 to LHLHLHLH in order to transmit a second signal (e.g., 01010101) indicating that it is currently operating in a state corresponding to the fifth operating condition to the first processor 1131. It can be made with For example, the second processor 2410 outputs a high signal (5V or 3.3V) through the output port for the first 10 ms to turn on the second switch element 2435 to change the state of the signal line 30 to low ( 0V), and output a low signal (0V) through the output port for the next 10 ms to turn off the second switch element 2435 and make the signal line 30 high (14V) four times. It can be repeated. In this case, the second processor 2410 may transmit 01010101 to the second processor 2410 for 80 ms. While the second processor 2410 transmits a signal, the output port of the first processor 1131 may be maintained in a low (0V) state.

When the first processor 1131 receives a second signal (e.g., 01010101) indicating the fifth operating condition from the second processor 2410 of the brush device 2000, the first processor 1131 uses a lookup table stored in the memory of the cleaner main body 1000. At 2110, fifth operation information corresponding to the fifth operation condition (power consumption of suction motor 1110: 58W, drum RPM: 1000, trip level: 4.9A) can be confirmed. Additionally, the first processor 1131 may identify that the current drum RPM of the brush device 2000 is 1000 rpm and the current trip level is 4.9A.

Let's take a closer look at the operation of transmitting and receiving signals between the cleaner main body 1000 and the brush device 2000 with reference to FIG. 24.

FIG. 24 is a flowchart illustrating an operation of mutually transmitting signals between the cleaner main body 1000 and the brush device 2000 according to an embodiment of the present disclosure. In Figure 24, the case where the cleaner main body 1000 operates as a master device and the brush device 2000 operates as a slave device will be described as an example.

The vacuum cleaner main body 1000 may receive a user input to turn on the power (S2410). When the cleaner main body 1000 is turned on, the cleaner main body 1000 may communicate with the brush device 2000 coupled to the wireless cleaner 100 through the signal line 30. For example, the cleaner main body 1000 may transmit an A1 signal (A1-A) indicating the first operating condition to the brush device 2000 (S2420). The A1 signal (A1-A) can be transmitted for 80ms. When the brush device 2000 receives the A1 signal (A1-A), the brush device 2000 may transmit an A1 response signal (A1-R) indicating the current state to the cleaner main body 1000 (S2430). A1 response signal (A1-R) can also be transmitted for 80ms.

The brush device 2000 may execute a command according to the A1 signal (A1-A) (S2440). For example, the brush device 2000 may adjust drum RPM, restraint level, etc. based on first operation information corresponding to the first operation condition.

The cleaner main body 1000 may transmit the A2 signal (A2-A) to the brush device 2000 when a predetermined time has elapsed after transmitting the A1 signal (A1-A) (S2450). In Figure 24, the case where the predetermined time is 200 ms is explained as an example, but it is not limited to this. If the usage environment condition (e.g., floor, carpet, mat, corner, lift, etc.) of the brush device 2000 has not changed between transmitting the A1 signal (A1-A) and transmitting the A2 signal (A2-A), The A2 signal (A2-A) may continue to represent the first operating condition. On the other hand, if the usage environment state of the brush device 2000 changes between the transmission of the A1 signal (A1-A) and the transmission of the A2 signal (A2-A), the A2 signal (A2-A) is not the first operating condition. A second operating condition may be indicated.

When the brush device 2000 receives the A2 signal (A2-A), the brush device 2000 may transmit an A2 response signal (A2-R) indicating the current state to the cleaner main body 1000 (S2460). The A2 response signal (A2-R) can also be transmitted for 80ms. At this time, the A2 response signal (A2-R) may include the command execution result of the brush device 2000. For example, when the brush device 2000 adjusts the drum RPM, restraint level, etc. based on the first operation information corresponding to the first operating condition, the A2 response signal (A2-R) indicates the first operating condition. Data (or data indicating drum RPM and restraint level) may be included.

The cleaner main body 1000 may transmit the A3 signal (A3-A) to the brush device 2000 when a predetermined time (200 ms) has elapsed after transmitting the A2 signal (A2-A) (S2470). When the brush device 2000 receives the A3 signal (A3-A), it can transmit the A3 response signal (A3-A) indicating the current status to the cleaner main body 1000.

Accordingly, the cleaner main body 1000 continuously communicates with the brush device 2000 at predetermined time intervals (200 ms) to determine the usage environment status (e.g., floor, carpet, mat, corner, lift, etc.) of the brush device 2000. Accordingly, the operation of the brush device 2000 can be adaptively controlled.

For example, when the user is cleaning the floor with the wireless cleaner 100, the cleaner body 1000 transmits data indicating the first operating condition corresponding to the floor to the brush device 2000, and the brush device 2000 The drum RPM can be changed to 2000 rpm based on the first operating condition corresponding to the floor. While the user is cleaning the floor, the cleaner main body 1000 may transmit data representing the first operating condition corresponding to the floor to the brush device 2000 every 200 ms, and the brush device 2000 may transmit the current state (corresponding to the floor) The cleaner main body 1000 may respond (operate based on the first operating condition). When the user cleans a carpet (normal load) instead of the floor, the cleaner body 1000 may transmit data indicating a second operating condition corresponding to the carpet (normal load) to the brush device 2000, and the brush device 2000 may transmit data indicating a second operating condition corresponding to the carpet (normal load). (2000) can change the drum RPM to 3800 rpm based on the second operating condition corresponding to cafe (normal load). Additionally, the brush device 2000 may respond to the cleaner body 1000 regarding its current status (operation based on the second operating condition corresponding to the carpet).

According to an embodiment of the present disclosure, when the cleaner main body 1000 does not receive the second signal from the brush device 2000 for a predetermined time after transmitting the first signal through the signal line 30, the brush device ( 2000) may decide that communication is not possible. For example, if a response signal (second signal) is not received from the brush device 2000 while the cleaner main body 1000 transmits the first signal to the brush device 2000 three times, the cleaner body 1000 It may be decided that communication is not possible.

As it is determined that communication with the brush device 2000 is impossible, the cleaner main body 1000 may switch the operation mode from AI mode to normal mode. The AI mode is a mode in which the suction power of the suction motor 1110 or the drum RPM of the brush device 2000 is automatically adjusted depending on the usage environment condition of the brush device 2000, and the normal mode is a mode in which the user controls the suction motor 1110. This may be a mode in which you must manually adjust the suction power strength. If communication with the brush device 2000 is not possible, the cleaner main body 1000 cannot transmit data to adjust the drum RPM of the brush device 2000 to the brush device 2000, and therefore cannot operate in AI mode anymore.

As the cleaner main body 1000 determines that communication with the brush device 2000 is impossible, it may output a notification indicating that operation in AI mode is impossible through the output interface. The operation of the vacuum cleaner main body 1000 to output a notification will be examined in detail later with reference to FIG. 36.

Meanwhile, according to an embodiment of the present disclosure, when it is determined that communication with the brush device 2000 is impossible, the cleaner main body 1000 does not adjust the drum RPM of the brush device 2000 and the brush device 2000 Depending on the usage environment, only the strength of the suction force of the suction motor 1110 may be adjusted.

FIG. 25 is a diagram for explaining an operation of the cleaner main body 1000 identifying the type of the brush device 2000 based on a signal received from the brush device 2000 according to an embodiment of the present disclosure.

Referring to FIG. 25, the brush device 2000 may indicate the type of the brush device 2000 using the start bit of a data signal transmitted during signal line communication. For example, the brush device 2000 defines the start bit as 11 if the brush device 2000 is a type A brush, defines the start bit as 10 if the brush device 2000 is a type B brush, and defines the start bit as 10 if the brush device 2000 is a type B brush. In this case, the start bit can be defined as 01, and in the case of a D-type brush, the start bit can be defined as 00, but it is not limited to this.

According to an embodiment of the present disclosure, the cleaner main body 1000 may identify the type of the brush device 2000 by analyzing the start bit of the data signal transmitted from the brush device 2000. For example, if the start bit contains 11, the cleaner body 1000 identifies the brush device 2000 as a type A brush, and if the start bit contains 10, the cleaner body 1000 identifies the brush device 2000 as a type A brush. The brush device 2000 can be identified as a B-type brush.

According to an embodiment of the present disclosure, when the type of brush device 2000 exceeds four, the number of start bits may be increased. Meanwhile, according to an embodiment of the present disclosure, a separate bit to indicate the type of the brush device 2000 may be added to the data signal instead of the start bit.

FIG. 26 is a diagram for explaining an operation in which the lighting device 2300 is controlled according to the usage environment state of the brush device 2000 according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the cleaner main body 1000 operates the suction motor 1110 according to the use environment condition of the brush device 2000 (e.g., floor, mat, general carpet, high-density carpet, lifting, wall corner, etc.). ) In addition to the power consumption and the drum RPM of the brush device 2000, the lighting brightness and lighting color of the brush device 2000 can also be determined. Additionally, the cleaner body 1000 may transmit data regarding the determined lighting brightness or determined lighting color to the second processor 2410 of the brush device 2000 through signal line communication. At this time, the second processor 2410 of the brush device 2000 may control the lighting device 2300 based on the lighting brightness or lighting color determined by the cleaner main body 1000.

For example, when the usage environment state of the brush device 2000 is audible 2601, the cleaner body 1000 may determine the color of the lighting device 2300 to be white, and the cleaner body 1000 may determine the color of the lighting device 2300 to be white. Depending on control, the lighting device 2300 may output white light. In addition, when the usage environment state of the brush device 2000 is Maru 2602, the cleaner body 1000 may determine the color of the lighting device 2300 to be green, and the usage environment state of the brush device 2000 may be green. If the is the mat 2603, the cleaner body 1000 may determine the color of the lighting device 2300 to be yellow, and if the usage environment state of the brush device 2000 is the carpet 2604, 2605, the cleaner body 1000 may determine the color of the lighting device 2300 to be yellow. (1000) may determine the color of the lighting device (2300) to be blue, and if the usage environment state of the brush device (2000) is a wall (corner) (2606), the cleaner body (1000) may set the lighting device (2300) to blue. ) can be determined to be orange.

According to an embodiment of the present disclosure, a user may perceive a change in the usage environment state of the brush device 2000 through a change in the color of the lighting device 2300.

Hereinafter, various circuits that enable communication between the cleaner main body 1000 and the brush device 2000 will be looked at with reference to FIGS. 27 to 34.

FIG. 27 is a diagram illustrating a circuit for signal line communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

The driving circuit 1130 of the cleaner main body 1000 shown in FIG. 27 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 27 Since the driving circuit 2400-1 of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

Referring to FIG. 27, the driving circuit 2400-1 of the brush device 2000 may include a voltage divider like the driving circuit 1130 of the cleaner main body 1000. Therefore, for convenience of explanation, the voltage divider of the cleaner body 1000 is expressed as a first voltage divider 1137, and the voltage divider of the brush device 2000 is expressed as a second voltage divider 2427.

The second voltage divider 2427 is used to distribute the voltage input from the signal line 30 to the input port of the second processor 2410. When the driving circuit 2400-1 of the brush device 2000 includes the second voltage divider 2427, even if a noise voltage is applied to the signal line 30, the noise voltage is also distributed to the input of the second processor 2410. It can be input as a port (AD port).

Therefore, according to an embodiment of the present disclosure, when the second processor 2410 receives a signal from the first processor 1131, the driving circuit 2400-1 for signal line communication of the brush device 2000 is Since it includes two voltage dividers 2427, stable signal reception is possible by minimizing the noise effect of the signal line 30.

In Figure 27, for convenience of explanation, the case where A is 180KΩ, B is 330KΩ, C is 82KΩ, D is 330KΩ, and E is 82KΩ will be described as an example. At this time, the signal line voltage is 13.4487V ( ) can be.

The first processor 1131 may identify the type of brush device 2000 based on the voltage input to the input port (AD port). For example, the AD port input voltage of the first processor 1131 is 2.677V ( ), the first processor 1131 can identify that the multi-brush 501 having an identification resistance 2500 of 180KΩ (A) corresponding to the AD port input voltage of 2.677V is connected.

If the brush device 2000 coupled to the wireless cleaner 100 is identified as a multi-brush 501 including a driving circuit 2400-1, the cleaner body 1000 is configured to use the brush device 2000. ) and signal line communication can be performed.

The first processor 1131 of the cleaner main body 1000 may receive a signal using an input port and transmit a signal using an output port. For example, when the first processor 1131 outputs a low signal through the output port, the first switch element 1132 may be turned off. As the first switch element 1132 is turned off, the voltage of the signal line 30 can be in a high state at 13.4487V. If the voltage of the signal line 30 is 13.4487V, the input port of the second processor 2410 is 2.677V ( ) can be entered. At this time, the driving circuit 2400-1 of the brush device 2000 includes a second voltage divider 2427, so that the high voltage (13.4487V) of the signal line 30 is distributed to the input port of the second processor 2410. Only 2.677V can be input. Conversely, when the first processor 1131 outputs a high signal through the output port, the first switch element 1132 may be turned on. As the first switch element 1132 is turned on, the voltage of the signal line 30 changes to 0V (GND) and may be in a low state. When the voltage of the signal line 30 is 0V, a low signal (0V) may be input to the input port of the second processor 2410. That is, when the first processor 1131 outputs a low signal through the output port, a high signal (2.677V) is input to the input port of the second processor 2410, and the first processor 1131 outputs a low signal through the output port. When outputting a high signal, a low signal may be input to the input port of the second processor 2410.

The second processor 2410 of the brush device 2000 may receive a signal using an input port and transmit a signal using an output port. For example, when the second processor 2410 outputs a high signal through the output port, the second switch element 2435 may be turned on. As the second switch element 2435 is turned on, the voltage of the signal line 30 changes to 0V (GND) and may be in a low state. When the voltage of the signal line 30 is 0V, a low signal (0V) may be input to the input port of the first processor 1131. Conversely, when the second processor 2410 outputs a low signal through the output port, the second switch element 2435 may be turned off. As the second switch element 2435 is turned off, the voltage of the signal line 30 can be in a high state at 13.4487V. When the voltage of the signal line 30 is 13.4487V, 2.677V can be input to the input port of the first processor 1131. At this time, the driving circuit 1130 of the cleaner main body 1000 includes the first voltage divider 1137, so the high voltage (13.4487V) of the signal line 30 is distributed to the input port of the first processor 1131 to 2.677V. can only be entered. That is, when the second processor 2410 outputs a high signal through the output port, a low signal (0V) is input to the input port of the first processor 1131, and the second processor 2410 outputs a low signal through the output port. When outputting a signal, a high signal (2.677V) may be input to the input port of the second processor 2410.

FIG. 28 is a diagram illustrating a circuit for I2C communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 28, the cleaner main body 1000 may include a driving circuit 1130a for I2C (Inter-Integrated Circuit) communication, and the brush device 2000 may also include a driving circuit 2400a for I2C communication. can do. The driving circuit 1130a of the cleaner main body 1000 shown in FIG. 28 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 28 Since the driving circuit 2400a may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to an embodiment of the present disclosure, the wireless cleaner 100 includes a first communication line 41 and a second communication line 42 for I2C communication instead of the signal line 30 connected to the power lines 10 and 20. can do.

I2C communication is a synchronization communication method that uses a clock signal to adjust data transmission timing. Accordingly, the wireless cleaner 100 may include a first communication line 41 for transmitting and receiving SDA (Serial Data) and a second communication line 42 for transmitting and receiving SCL (Serial Clock).

Due to the nature of the cordless cleaner 100, it is inevitable that there will be a lot of noise generated due to attachment and detachment of the brush device 2000 or movement or collision of the cordless cleaner 100. Therefore, in order to minimize electrical or mechanical damage or stress during I2C communication between the cleaner body 1000 and the brush device 2000, SDA (Serial Data) and SCL (Serial Clock) are input to the input terminal. A noise reduction circuit may be applied. For example, the cleaner body 1000 may include a first noise reduction circuit 1139, and the brush device 2000 may include a second noise reduction circuit 2450.

The first noise reduction circuit 1139 and the second noise reduction circuit 2450 include a low pass filter, a high pass filter, a band pass filter, and a damping resistor. Resistor), and may include at least one of a distribution resistor, but are not limited thereto.

Serial data (SDA) and serial clock (SCL) transmitted from the second processor 2410 through the first communication line 41 and the second communication line 42 are transmitted through the first noise reduction circuit 1139 to the first processor ( 1131), the influence of noise can be minimized. In addition, SDA (Serial Data) and SCL (Serial Clock) transmitted from the first processor 1131 through the first communication line 41 and the second communication line 42 are transmitted through the second noise reduction circuit 2450. By being input to the processor 2410, the influence of noise can be minimized.

According to an embodiment of the present disclosure, the cleaner main body 1000 operates as a master device and the brush device 2000 operates as a slave device, thereby performing I2C communication. I2C communication signals can consist of a start signal (start bit), a data signal (command bit), and a stop signal (end bit).

The first processor 1131 may transmit a signal indicating an operating condition to the second processor 2410 through the first communication line 41 and the second communication line 42. The operating conditions include the target revolutions per minute (RPM) of the drum 2200 of the brush device 2000, the target trip level of the brush device 2000, or the suction motor 1110 included in the cleaner body 1000. It may include at least one of the power consumption.

The second processor 2410 of the brush device 2000 may execute a command based on operation information corresponding to the received operating condition. For example, the brush device 2000 can adjust drum RPM, restraint level, etc. In addition, the second processor 2410 of the brush device 2000 sends a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the first communication line 41 and the second communication line 42. Can be transmitted.

FIG. 29 is a diagram illustrating a circuit for UART full-duplex communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 29, the cleaner main body 1000 may include a driving circuit 1130b for UART full duplex communication, and the brush device 2000 may also include a driving circuit 2400b for UART full duplex communication. can do. The driving circuit 1130b of the cleaner main body 1000 shown in FIG. 29 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 29 Since the driving circuit 2400b of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to one embodiment of the present disclosure, the wireless cleaner 100 may include two wires for UART full-duplex communication instead of the signal line 30 connected to the power lines 10 and 20. For example, the wireless cleaner 100 may include a third communication line 51 and a fourth communication line 52. The third communication line 51 is a line for transmitting a signal from the first processor 1131 to the second processor 2410, and the fourth communication line 52 is a line for the second processor 2410 to transmit a signal to the first processor 1131. It may be a line for transmitting signals. The first processor 1131 and the second processor 2410 can simultaneously transmit and receive signals through the third communication line 51 and the fourth communication line 52, respectively.

Due to the nature of the cordless cleaner 100, it is inevitable that there will be a lot of noise generated due to attachment and detachment of the brush device 2000 or movement or collision of the cordless cleaner 100. Therefore, a noise reduction circuit may be applied to the input terminal where a signal is input to minimize electrical or mechanical damage or stress during UART communication between the cleaner main body 1000 and the brush device 2000. For example, the cleaner body 1000 may include a first noise reduction circuit 1139, and the brush device 2000 may include a second noise reduction circuit 2450.

The first noise reduction circuit 1139 and the second noise reduction circuit 2450 include a low pass filter, a high pass filter, a band pass filter, and a damping resistor. Resistor), and may include at least one of a distribution resistor, but are not limited thereto.

The data signal transmitted from the first processor 1131 through the third communication line 51 is input to the second processor 2410 through the second noise reduction circuit 2450, thereby minimizing the influence of noise. In addition, the data signal transmitted from the second processor 2410 through the fourth communication line 52 is input to the first processor 1131 through the first noise reduction circuit 1139, thereby minimizing the effect of noise. .

According to an embodiment of the present disclosure, the cleaner main body 1000 operates as a master device and the brush device 2000 operates as a slave device, thereby performing UART full-duplex communication. The UART communication signal may consist of a start signal (start bit), a data signal (command bit), and a stop signal (end bit).

The first processor 1131 may transmit a signal indicating an operating condition to the second processor 2410 through the third communication line 52. The operating conditions include the target revolutions per minute (RPM) of the drum 2200 of the brush device 2000, the target trip level of the brush device 2000, or the suction motor 1110 included in the cleaner body 1000. It may include at least one of the power consumption.

The second processor 2410 of the brush device 2000 may execute a command based on operation information corresponding to the received operating condition. For example, the brush device 2000 can adjust drum RPM, restraint level, etc. Additionally, the second processor 2410 of the brush device 2000 may transmit a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the fourth communication line 52.

FIG. 30 is a diagram illustrating a circuit for UART half-duplex communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 30, the cleaner main body 1000 may include a driving circuit 1130c for UART half-duplex communication, and the brush device 2000 may also include a driving circuit 2400c for UART half-duplex communication. It can be included. The driving circuit 1130c of the cleaner main body 1000 shown in FIG. 30 may correspond to the driving circuit 1130b of the cleaner main body 1000 shown in FIG. 29, and the brush device 2000 shown in FIG. 30 Since the driving circuit 2400c of may correspond to the driving circuit 2400b shown in FIG. 29, overlapping description will be omitted.

According to one embodiment of the present disclosure, the wireless cleaner 100 may include one wire for UART half-duplex communication instead of the signal line 30 connected to the power lines 10 and 20. For example, the wireless cleaner 100 may include a fifth communication line 53. The fifth communication line 53 may be a line for the first processor 1131 and the second processor 2410 to alternately transmit signals. When the first processor 1131 transmits the first signal through the fifth communication line 53, the second processor 2410 receives the first signal through the fifth communication line 53, and the second processor 2410 When transmitting the second signal through the fifth communication line 53, the first processor 1131 may receive the second signal through the fifth communication line 53.

Meanwhile, the data signal transmitted from the first processor 1131 through the fifth communication line 53 is input to the second processor 2410 through the second noise reduction circuit 2450, thereby minimizing the effect of noise. . In addition, the data signal transmitted from the second processor 2410 through the fifth communication line 53 is input to the first processor 1131 through the first noise reduction circuit 1139, thereby minimizing the effect of noise. .

According to an embodiment of the present disclosure, the cleaner main body 1000 operates as a master device and the brush device 2000 operates as a slave device, thereby performing UART half-duplex communication. The UART communication signal may consist of a start signal (start bit), a data signal (command bit), and a stop signal (end bit).

The first processor 1131 may transmit a signal indicating an operating condition to the second processor 2410 through the fifth communication line 53. The operating conditions include the target revolutions per minute (RPM) of the drum 2200 of the brush device 2000, the target trip level of the brush device 2000, or the suction motor 1110 included in the cleaner body 1000. It may include at least one of the power consumption.

The second processor 2410 of the brush device 2000 may execute a command based on operation information corresponding to the received operating condition. For example, the brush device 2000 can adjust drum RPM, restraint level, etc. Additionally, the second processor 2410 of the brush device 2000 may transmit a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the fifth communication line 53.

FIG. 31 is a diagram illustrating a circuit for I2C communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 31, the cleaner main body 1000 may include a driving circuit 1130d for I2C (Inter-Integrated Circuit) communication, and the brush device 2000 may also include a driving circuit 2400d for I2C communication. can do. The driving circuit 1130d of the cleaner main body 1000 shown in FIG. 31 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 31 Since the driving circuit 2400d of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to an embodiment of the present disclosure, the wireless cleaner 100 includes a first communication line 41 and a second communication line 42 for I2C communication instead of the signal line 30 connected to the power lines 10 and 20. can do. The first communication line 41 may be a line for transmitting and receiving SDA (Serial Data), and the second communication line 42 may be a line for transmitting and receiving SCL (Serial Clock).

According to an embodiment of the present disclosure, for noise-resistant communication, the driving circuit 1130d of the cleaner main body 1000 may include a first level shifter circuit 1141 and a second level shifter circuit 1142. . Each of the first level shifter circuit 1141 and the second level shifter circuit 1142 may be a level shift IC (Integrated Circuit) packing a switch element and a peripheral circuit. The driving circuit 2400d of the brush device 2000 may include a first pull-up resistor 2451, a first damping resistor 2452, a second pull-up resistor 2453, and a second damping resistor 2454.

By operating as a master device, the cleaner main body 1000 can transmit signals representing operating conditions to the second processor 2410 through the first communication line 41 and the second communication line 42. For example, when the first processor 1131 outputs a high signal (5V) in the direction of the first level shifter circuit 1141, the switch element (e.g., N-channel) included in the first level shifter circuit 1141 Since the FET) is in the OFF state, 3.3V (High) connected to the first pull-up resistor 2451 is applied to the first communication line 41, and 3.3V (High) is also applied to the second processor 2410 through the first damping resistor 2452. V (High) can be input. On the other hand, when the first processor 1131 outputs a low signal (0V) in the direction of the first level shifter circuit 1141, a switch element (e.g., N-channel FET) included in the first level shifter circuit 1141 Since is in the ON state, the voltage of the first communication line 41 becomes 0V (Low), and 0V (Low) can also be input to the second processor 2410. That is, when the first processor 1131 outputs a High signal in the direction of the first level shifter circuit 1141, the High signal is input to the second processor 2410 through the first communication line 41, and the first processor ( When 1131) outputs a low signal in the direction of the first level shifter circuit 1141, the low signal may be input to the second processor 2410 through the first communication line 41.

Likewise, when the first processor 1131 outputs a High signal in the direction of the second level shifter circuit 1142, the High signal is input to the second processor 2410 through the second communication line 42, and the first processor ( When 1131) outputs a low signal in the direction of the second level shifter circuit 1142, the low signal may be input to the second processor 2410 through the second communication line 42.

Meanwhile, the second processor 2410 of the brush device 2000 sends a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the first communication line 41 and the second communication line 42. Can be transmitted. For example, when the second processor 2410 outputs a high signal (3.3V) in the direction of the first damping resistor 2452, 3.3V (high) is also applied to the first communication line 41. At this time, since the switch element (eg, N-channel FET) included in the first level shifter circuit 1141 does not operate, 5V (High) is input to the first processor 1131. That is, in the first level shifter circuit 1141, +5V power cannot flow to the first communication line 41 through the 10KΩ resistor and the body diode (BD) of the switch element (e.g., N-channel FET) ( current path is not formed), 5V is input to the first processor 1131, and the SDA of the first processor 1131 becomes High (+5V). On the other hand, when the second processor 2410 outputs a low signal (0V) in the direction of the first damping resistor 2452, the size of the first damping resistor 2452 is very small compared to the first pull-up resistor 2451. , a voltage (low) close to 0 is also applied to the first communication line 41. For example, the voltage of the first communication line 41 may be in a LOW state at 0.032673V (= 3.3V *[100 / (10K+100)]. Additionally, the voltage included in the first level shifter circuit 1141 Since the resistance (10KΩ) is large, the voltage drop is large, so a voltage (Low) close to 0 is input to the first processor 1131. That is, the switch element (e.g., N-) included in the first level shifter circuit 1141 channel FET) is in the OFF state, but a current path of +5V is formed to the first communication line 41 through a resistance (10KΩ) and the body diode (BD) of the switch element (e.g., N-channel FET). , SDA of the first processor 1131 becomes Low. For example, assuming that the voltage (VF) of the body diode (BD) of the switch element (e.g., N-channel FET) is 0.6V, the first processor 1131 ) input voltage (also called SDA voltage) can be as follows.

First processor (1131) SDA voltage = N-FET BD VF (0.6V) + first communication line (41) voltage

= 0.6V + 0.032673V = 0.632673V (approximately 4.367V applied to a 10KΩ resistor)

0V)가 입력된다.Therefore, when the second processor 2410 outputs a high signal (3.3V) in the direction of the first damping resistor 2452, a high signal (5V) is also output to the first processor 1131 through the first communication line 41. input, and when the second processor 2410 outputs a Low signal (0V) in the direction of the first damping resistor 2452, a Low signal (0V) is also sent to the first processor 1131 through the first communication line 41.

0V) is input.

0V)가 입력된다.Likewise, when the second processor 2410 outputs a high signal (3.3V) in the direction of the second damping resistor 2454, a high signal (5V) is also output to the first processor 1131 through the second communication line 42. input, and when the second processor 2410 outputs a low signal (0V) in the direction of the second damping resistor 2454, a low signal (0V) is also sent to the first processor 1131 through the second communication line 42.

0V) is input.

When the cordless vacuum cleaner 100 includes a first level shifter circuit 1141 and a second level shifter circuit 1142, the voltage output from the first processor 1131 and the voltage output from the second processor 2410 are Even if they are different, I2C communication between the cleaner body 1000 and the brush device 2000 is possible.

According to an embodiment of the present disclosure, the driving circuit 1130d of the cleaner main body 1000 includes a first pull-up resistor 2451, a first damping resistor 2452, a second pull-up resistor 2453, and a second damping resistor ( 2454), and the driving circuit 2400d of the brush device 2000 may include a first level shifter circuit 1141 and a second level shifter circuit 1142.

FIG. 32 is a diagram illustrating a circuit for UART communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 32, the cleaner main body 1000 may include a driving circuit 1130e for UART communication, and the brush device 2000 may also include a driving circuit 2400e for UART communication. The driving circuit 1130e of the cleaner main body 1000 shown in FIG. 32 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 32 Since the driving circuit 2400e of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to one embodiment of the present disclosure, the wireless cleaner 100 may include two wires for UART full-duplex communication instead of the signal line 30 connected to the power lines 10 and 20. For example, the wireless cleaner 100 may include a third communication line 51 and a fourth communication line 52. The third communication line 51 is a line for transmitting a signal from the first processor 1131 to the second processor 2410, and the fourth communication line 52 is a line for the second processor 2410 to transmit a signal to the first processor 1131. It may be a line for transmitting signals. The first processor 1131 and the second processor 2410 can simultaneously transmit and receive signals through the third communication line 51 and the fourth communication line 52, respectively.

According to an embodiment of the present disclosure, for noise-resistant communication, the driving circuit 1130e of the cleaner main body 1000 may include a first level shifter circuit 1141 and a second level shifter circuit 1142. . Each of the first level shifter circuit 1141 and the second level shifter circuit 1142 may be a level shift IC packing a switch element and a peripheral circuit. The driving circuit 2400e of the brush device 2000 may include a first pull-up resistor 2451, a first damping resistor 2452, a second pull-up resistor 2453, and a second damping resistor 2454.

By operating as a master device, the cleaner main body 1000 can transmit signals indicating operating conditions to the second processor 2410 through the third communication line 51. For example, when the first processor 1131 outputs a high signal (5V), the switch element (e.g., N-channel FET) included in the first level shifter circuit 1141 is in the OFF state, so the third 3.3V (High) connected to the first pull-up resistor 2451 is applied to the communication line 51, and 3.3V (High) can also be input to the second processor 2410 through the first damping resistor 2452. On the other hand, when the first processor 1131 outputs a low signal (0V), the switch element (e.g., N-channel FET) included in the first level shifter circuit 1141 is turned on, so the third communication line ( 51) becomes 0V (Low), and 0V (Low) can also be input to the second processor 2410. That is, when the first processor 1131 outputs a high signal (5V), the high signal (3.3V) is input to the second processor 2410 through the third communication line 51, and the first processor 1131 When outputting a low signal (0V), the low signal (0V) may be input to the second processor 2410 through the third communication line 51.

0V)가 입력된다. 도 32의 레벨 쉬프터 회로들(1141, 1142)의 동작은 도 31의 레벨 쉬프터 회로들(1141, 1142)의 동작과 동일하므로, 중복되는 설명은 생략하기로 한다.Meanwhile, the second processor 2410 of the brush device 2000 may transmit a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the fourth communication line 52. For example, when the second processor 2410 outputs a high signal (3.3V), 3.3V (high) is also applied to the fourth communication line 52. At this time, since the switch element (eg, N-channel FET) included in the second level shifter circuit 1142 does not operate, 5V (High) is input to the first processor 1131. On the other hand, when the second processor 2410 outputs a low signal (0V), the size of the second damping resistor 2454 is very small compared to the second pull-up resistor 2453, so the fourth communication line 52 also has 0. A voltage (low) close to is applied. In addition, since the resistance (10K) included in the second level shifter circuit 1142 is large, the voltage drop is large, and a voltage (Low) close to 0 is input to the first processor 1131. That is, when the second processor 2410 outputs a high signal (3.3V), a high signal (5V) is also input to the first processor 1131 through the fourth communication line 52, and the second processor 2410 When outputting a Low signal (0V), a Low signal (0V) is also sent to the first processor 1131 through the fourth communication line 52.

0V) is input. Since the operation of the level shifter circuits 1141 and 1142 of FIG. 32 is the same as the operation of the level shifter circuits 1141 and 1142 of FIG. 31, overlapping descriptions will be omitted.

When the cordless vacuum cleaner 100 includes a first level shifter circuit 1141 and a second level shifter circuit 1142, the voltage output from the first processor 1131 and the voltage output from the second processor 2410 are Even if they are different, UART communication between the cleaner main body 1000 and the brush device 2000 is possible.

According to an embodiment of the present disclosure, the driving circuit 1130e of the cleaner main body 1000 includes a first pull-up resistor 2451, a first damping resistor 2452, a second pull-up resistor 2453, and a second damping resistor ( 2454), and the driving circuit 2400e of the brush device 2000 may include a first level shifter circuit 1141 and a second level shifter circuit 1142.

FIG. 33 is a diagram illustrating a circuit for UART full-duplex communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 33, the cleaner main body 1000 may include a driving circuit 1130f for UART communication, and the brush device 2000 may also include a driving circuit 2400f for UART communication. The driving circuit 1130f of the cleaner body 1000 shown in FIG. 33 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 33 Since the driving circuit 2400f of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to one embodiment of the present disclosure, the wireless cleaner 100 may include two wires for UART communication. For example, the wireless cleaner 100 may include a third communication line 51 and a fourth communication line 52. The third communication line 51 is a line for transmitting a signal from the first processor 1131 to the second processor 2410, and the fourth communication line 52 is a line for the second processor 2410 to transmit a signal to the first processor 1131. It may be a line for transmitting signals. The first processor 1131 and the second processor 2410 can simultaneously transmit and receive signals through the third communication line 51 and the fourth communication line 52, respectively.

According to an embodiment of the present disclosure, for noise-resistant communication, the driving circuit 1130f of the cleaner main body 1000 includes a first circuit 1141a similar to the first level shifter circuit 1141, and a third damping circuit. It may include a resistor 1143 and a first voltage divider 1137. The driving circuit 2400f of the brush device 2000 may include a second voltage divider 2427, a first damping resistor 2452, and a second circuit 2455 of a similar form to the first level shifter circuit 1141. there is.

By operating as a master device, the cleaner main body 1000 can transmit signals indicating operating conditions to the second processor 2410 through the third communication line 51. For example, when the first processor 1131 outputs a high signal (5V), the switch element (e.g., N-channel FET) included in the first circuit 1141a is in the OFF state, so the third communication line ( 51), the voltage (25.2V) (High) of the + power line (10) connected through the R1 resistor is applied. At this time, a high signal (=Battery voltage (25.2V) * R3/(R1+R2+R3)) may be input to the second processor 2410 through the second voltage divider 2427. On the other hand, when the first processor 1131 outputs a low signal (0V), the switch element (e.g., N-channel FET) included in the first circuit 1141a is turned on, so the third communication line 51 The voltage becomes 0V (Low), and 0V (Low) can also be input to the second processor 2410. That is, when the first processor 1131 outputs a high signal (5V), the high signal (3.3V) is input to the second processor 2410 through the third communication line 51, and the first processor 1131 When outputting a low signal (0V), the low signal (0V) may be input to the second processor 2410 through the third communication line 51.

Meanwhile, the second processor 2410 of the brush device 2000 may transmit a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the fourth communication line 52. For example, when the second processor 2410 outputs a high signal (3.3V), the switch element (e.g., N-channel FET) included in the second circuit 2455 is in the OFF state, so the fourth communication line The voltage (25.2V) (High) of the + power line (10) connected through the R4 resistor is applied to (52). At this time, a high signal (=Battery voltage (25.2V) * R6/(R4+R5+R6)) may be input to the first processor 1131 through the first voltage divider 1137. On the other hand, when the second processor 2410 outputs a low signal (0V), the switch element (e.g., N-channel FET) included in the second circuit 2455 is turned on, so the fourth communication line 52 The voltage becomes 0V (Low), and 0V (Low) can also be input to the first processor 1131. That is, when the second processor 2410 outputs a high signal (3.3V), the high signal is input to the first processor 1131 through the fourth communication line 52, and the second processor 2410 outputs a low signal ( When outputting 0V), a low signal (0V) may be input to the first processor 1131 through the fourth communication line 52.

According to an embodiment of the present disclosure, when the cleaner main body 1000 and the brush device 2000 communicate with UART, high voltage signals can be transmitted and received through the third communication line 51 and the fourth communication line 52, thereby reducing noise. You can be strong.

FIG. 34 is a diagram illustrating a circuit for I2C communication of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

Referring to FIG. 34, the cleaner main body 1000 may include a driving circuit 1130g for I2C (Inter-Integrated Circuit) communication, and the brush device 2000 may also include a driving circuit 2400g for I2C communication. can do. The driving circuit 1130g of the cleaner body 1000 shown in FIG. 34 may correspond to the driving circuit 1130 of the cleaner main body 1000 shown in FIG. 20, and the brush device 2000 shown in FIG. 33 Since the driving circuit 2400g of may correspond to the driving circuit 2400 shown in FIG. 20, redundant description will be omitted.

According to an embodiment of the present disclosure, the wireless cleaner 100 may include a sixth communication line 43, a seventh communication line 44, and an eighth communication line 45 for I2C communication. The sixth communication line 43 is a line for transmitting SDA (Serial Data) from the cleaner main body 1000 to the brush device 2000, and the seventh communication line 44 is a line for transmitting SDA (Serial Data) from the brush device 2000 to the cleaner main body 1000. It is a line for transmitting SDA (Serial Data), and the eighth communication line 45 may be a line for transmitting SCL (Serial Clock) from the cleaner main body 1000 to the brush device 2000.

According to an embodiment of the present disclosure, for noise-resistant communication, the driving circuit 1130g of the cleaner main body 1000 includes a first circuit 1141a similar to the first level shifter circuit 1141, and a second level circuit 1141a. It may include a third circuit 1142a, a third damping resistor 1143, and a first voltage divider 1137 similar to the shifter circuit 1142. The driving circuit 2400g of the brush device 2000 includes a second voltage divider 2427, a first damping resistor 2452, a second damping resistor 2454, and a second circuit similar to the first level shifter circuit 1141. It may include circuit 2455.

By operating as a master device, the cleaner main body 1000 can transmit signals representing operating conditions to the second processor 2410 through the sixth communication line 43 and the seventh communication line 44. For example, when the first processor 1131 outputs a high signal (5V) in the direction of the first circuit 1141a, the switch element (e.g., N-channel FET) included in the first circuit 1141a is turned off. Therefore, the voltage (25.2V) (High) of the + power line 10 connected through the R1 resistor is applied to the sixth communication line 43. At this time, a high signal (=Battery voltage (25.2V) * R3/(R1+R2+R3)) may be input to the second processor 2410 through the second voltage divider 2427. On the other hand, when the first processor 1131 outputs a low signal (0V) in the direction of the first circuit 1141a, the switch element (e.g., N-channel FET) included in the first circuit 1141a is in the ON state. Therefore, the voltage of the sixth communication line 43 becomes 0V (Low), and 0V (Low) can also be input to the second processor 2410. That is, when the first processor 1131 outputs a high signal (5V) to transmit a data signal (SDA), a high signal (3.3V) is input to the second processor 2410 through the sixth communication line 43. When the first processor 1131 outputs a low signal (0V) to transmit the data signal (SDA), the low signal (0V) is input to the second processor 2410 through the sixth communication line 43. It can be. Likewise, when the first processor 1131 outputs a high signal (5V) to transmit a clock signal (SCL), a high signal (3.3V) is input to the second processor 2410 through the seventh communication line 44. When the first processor 1131 outputs a low signal (0V) to transmit the clock signal (SCL), the low signal (0V) is input to the second processor 2410 through the seventh communication line 44. It can be.

Meanwhile, the second processor 2410 of the brush device 2000 sends a response signal indicating the current status to the first processor 1131 of the cleaner main body 1000 through the eighth communication line 45 and the seventh communication line 44. Can be transmitted. For example, when the second processor 2410 outputs a high signal (3.3V), the switch element (e.g., N-channel FET) included in the second circuit 2455 is in the OFF state, so the 8th communication line The voltage (25.2V) (High) of the + power line (10) connected through the R7 resistor is applied to (45). At this time, a high signal (=Battery voltage (25.2V) * R9/(R7+R8+R9)) may be input to the first processor 1131 through the first voltage divider 1137. On the other hand, when the second processor 2410 outputs a low signal (0V), the switch element (e.g., N-channel FET) included in the second circuit 2455 is turned on, so the eighth communication line 45 The voltage becomes 0V (Low), and 0V (Low) can also be input to the first processor 1131. That is, when the second processor 2410 outputs a high signal (3.3V) to transmit the data signal (SDA), the high signal is input to the first processor 1131 through the eighth communication line 45, and the high signal is input to the first processor 1131 through the eighth communication line 45. 2 When the processor 2410 outputs a low signal (0V) to transmit the data signal (SDA), the low signal (0V) may be input to the first processor 1131 through the eighth communication line 45. .

According to an embodiment of the present disclosure, when the cleaner main body 1000 and the brush device 2000 communicate using I2C, the sixth communication line 43, the seventh communication line 44, and the eighth communication line 45 are used. Since high voltage signals can be transmitted and received through it, it can be resistant to noise.

FIG. 35 is a diagram illustrating an operation of the wireless vacuum cleaner 100 to output an operation status notification according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, when the user selects the AI mode, the cleaner main body 1000 may display the first GUI 3501 on an output interface (eg, LCD). The first GUI 3501 may indicate that the wireless vacuum cleaner 100 is operating in AI mode, and may also indicate the cleaning time (remaining battery usage time) under AI mode.

The cleaner main body 1000 uses the AI model to identify the usage environment state of the brush device 2000, and depending on the usage environment state of the brush device 2000, the suction force strength of the suction motor 1110 or the usage environment state of the brush device 2000 When the drum RPM is adjusted, the second GUI 3502 may be displayed on the output interface of the cleaner main body 1000. For example, the second GUI 3502 may include a notification that says, “Optimized for the situation.”

After the second GUI 3502 is displayed on the output interface, the first GUI 3501 may be displayed again after a predetermined time (e.g., 3 seconds) has elapsed. Afterwards, if the suction force intensity of the suction motor 1110 or the drum RPM of the brush device 2000 changes again depending on the usage environment of the brush device 2000, the second GUI 3502 may be displayed again.

FIG. 36 is a diagram for explaining the GUI of the wireless vacuum cleaner 100 according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, when the user selects the AI mode and the cleaner main body 1000 and the brush device 2000 can communicate, the cleaner main body 1000 displays the first message on the output interface (e.g., LCD). A GUI (3601) can be displayed. The first GUI 3601 may indicate that the wireless vacuum cleaner 100 is operating in AI mode.

According to an embodiment of the present disclosure, when communication between the cleaner main body 1000 and the brush device 2000 is impossible, the cleaner main body 1000 may display the second GUI 3602 on an output interface (e.g., LCD). there is. The second GUI 3602 may include a notification that operation in AI mode is not possible. For example, if the cleaner main body 1000 does not receive the second signal for a predetermined time after transmitting the first signal through the signal line 30, it may determine that communication with the brush device 2000 is impossible. As the cleaner main body 1000 determines that communication with the brush device 2000 is impossible, a notification indicating that operation in AI mode is impossible may be output through the output interface.

According to an embodiment of the present disclosure, when the user presses the power button and selects the AI mode, but the operating current of the brush device 2000 is not detected, the brush device 2000 is not properly coupled to the wireless cleaner 100. It may not be true. Accordingly, the cleaner main body 1000 may display a third GUI 3603 asking to check the status of the brush device 2000. In addition, according to an embodiment of the present disclosure, when it is determined that communication with the brush device 2000 is impossible or the load of the brush device 2000 is more than a threshold value (overload state), the cleaner main body 1000 uses the brush device ( A third GUI 3603 may be displayed asking you to check the status of 2000).

Meanwhile, according to an embodiment of the present disclosure, as it is determined that communication with the brush device 2000 is impossible, the cleaner main body 1000 switches the operation mode from AI mode to normal mode and outputs a GUI corresponding to the normal mode. It can also be displayed through the interface.

According to an embodiment of the present disclosure, the current usage environment state of the brush device 2000 is identified using an AI model, and the suction force intensity of the suction motor 1110 is automatically adjusted according to the current usage environment state of the brush device 2000. A wireless vacuum cleaner 100 that can be adjusted may be provided.

According to an embodiment of the present disclosure, the current usage environment state of the brush device 2000 is identified using an AI model, and the RPM of the rotating brush of the brush device 2000 is determined according to the current usage environment state of the brush device 2000. A wireless vacuum cleaner 100 that automatically adjusts may be provided.

The wireless cleaner 100 according to an embodiment of the present disclosure includes a suction motor 1110 that forms a vacuum inside the wireless cleaner 100; A pressure sensor 1400 that measures pressure in the flow path inside the wireless vacuum cleaner 100; A load detection sensor 1134 for measuring the load of the brush device 2000; a memory 1900 that stores an AI model learned to infer the state of the usage environment of the brush device 2000; and at least one processor 1001. At least one processor 1001 may obtain data about the flow path pressure measured by the pressure sensor 1400 from the pressure sensor 1400 . At least one processor 1001 may obtain data related to the load of the brush device 2000 through the load detection sensor 1134. At least one processor 1001 applies data related to flow path pressure and data related to the load of the brush device 2000 to the AI model stored in the memory 1900 to identify the current usage environment state of the brush device 2000. can do. At least one processor 1001 may adjust the suction force intensity of the suction motor 1110 based on the current usage environment state of the identified brush device 2000.

Data related to the load of the brush device 2000 according to an embodiment of the present disclosure may include at least one of the operating current of the brush device 2000, the voltage applied to the brush device 2000, or the power consumption of the brush device 2000. It can contain one.

The current usage environment state of the brush device 2000 according to an embodiment of the present disclosure is the state of the surface to be cleaned on which the brush device 2000 is currently located, the relative position state of the brush device 2000 within the surface to be cleaned, or the state of the brush device 2000's relative position within the surface to be cleaned. The device 2000 may include at least one of the following states: the device 2000 is lifted from the surface being cleaned.

At least one processor 1001 according to an embodiment of the present disclosure may determine the target RPM of the rotating brush of the brush device 2000 based on the current usage environment state of the identified brush device 2000. At least one processor 1001 may transmit a control signal indicating the determined target RPM of the rotating brush to the brush device 2000.

At least one processor 1001 according to an embodiment of the present disclosure may receive a signal indicating the current state of the brush device 2000 from the brush device 2000 in response to the control signal.

At least one processor 1001 according to an embodiment of the present disclosure determines the color or brightness of the lighting device 2300 included in the brush device 2000, based on the current usage environment state of the identified brush device 2000. You can decide on at least one of the following. At least one processor 1001 may transmit a control signal representing at least one of the determined color or brightness of the lighting device 2300 to the brush device 2000.

At least one processor 1001 may select a first AI model corresponding to the first type of the brush device 2000 from among a plurality of AI models stored in the memory 1900. At least one processor 1001 may identify the current usage environment state of the brush device 2000 by applying data related to flow path pressure and data related to the load of the brush device 2000 to the selected first AI model. .

The brush device 2000 according to an embodiment of the present disclosure may include a first identification resistor representing a first type of the brush device 2000. At least one processor 1001 may identify the first type of brush device 2000 corresponding to the first identification resistor based on the first voltage value input to the suction motor 1110.

At least one processor 1001 may receive a data signal indicating the first type of the brush device 2000 from the brush device 2000.

At least one processor 1001 may modify parameter values of the AI model by applying the strength of suction force of the suction motor 1110 to the AI model. At least one processor 1001 applies data related to flow path pressure and data related to the load of the brush device 2000 to the AI model whose parameter values have been modified to identify the current usage environment state of the brush device 2000. You can.

The AI model according to an embodiment of the present disclosure may include at least one of a Support Vector Machine (SVM) model, a Neural Networks model, a Random Forest model, or a Graphical Model. .

The pressure sensor 1400 according to an embodiment of the present disclosure may include at least one of an absolute pressure sensor and a relative pressure sensor.

The pressure sensor 1400 according to an embodiment of the present disclosure may be provided in the suction duct 40 of the cleaner main body 1000 including the suction motor 1110.

At least one processor 1001 may configure a first pressure value measured through the pressure sensor 1400 before driving the suction motor 1110 and a second pressure value measured through the pressure sensor 1400 after driving the suction motor 1110. The difference can be obtained as data on flow path pressure.

At least one processor 1001 may adjust the suction force intensity of the suction motor 1110 to a first intensity of medium intensity when the current usage environment state of the brush device 2000 is a state of cleaning a hard floor. there is. At least one processor 1001 adjusts the suction force intensity of the suction motor 1110 to a second intensity lower than the first intensity when the current usage environment state of the brush device 2000 is a state of cleaning a mat or high-density carpet. You can. At least one processor 1001 may adjust the suction power intensity of the suction motor 1110 to a third intensity higher than the first intensity when the current usage environment state of the brush device 2000 is a state of cleaning a general carpet. .

At least one processor 1001 adjusts the suction force intensity of the suction motor 1110 to the minimum intensity when the current usage environment state of the brush device 2000 is a state in which the brush device 2000 is lifted a certain distance or more from the surface to be cleaned, and the brush device 2000 )'s target RPM can be determined at the lowest level.

At least one processor 1001 may adjust the suction force intensity of the suction motor 1110 to the maximum intensity when the current usage environment state of the brush device 2000 is to clean the corner of the wall.

At least one processor 1001 may adjust the trip level of the brush device 2000 based on the adjusted suction strength of the suction motor 1110.

At least one processor 1001 may identify a transition in the current usage environment state of the brush device 2000 by applying data related to flow path pressure and data related to the load of the brush device 2000 to the AI model. At least one processor 1001 may adjust the suction force intensity of the suction motor 1110 as a transition in the current usage environment state of the brush device 2000 is identified.

A method for the wireless vacuum cleaner 100 to automatically adjust the suction force intensity of the suction motor 1110 according to an embodiment of the present disclosure includes the step of acquiring data on the flow path pressure measured by the pressure sensor 1400 (S810) ), acquiring data related to the load of the brush device 2000 through the load detection sensor 1134 (S820), data related to flow path pressure and data related to the load of the brush device 2000 are acquired through a pre-learned AI model. Applying to, identifying the current usage environment state of the brush device 2000 (S830); and adjusting the suction force intensity of the suction motor 1110 based on the current usage environment state of the identified brush device 2000 (S840).

A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here, 'non-transitory storage medium' simply means that it is a tangible device and does not contain signals (e.g. electromagnetic waves). This term refers to cases where data is semi-permanently stored in a storage medium and temporary storage media. It does not distinguish between cases where it is stored as . For example, a 'non-transitory storage medium' may include a buffer where data is temporarily stored.

According to one embodiment, methods according to various embodiments disclosed in this document may be provided and included in a computer program product. Computer program products are commodities and can be traded between sellers and buyers. A computer program product may be distributed in the form of a machine-readable storage medium (e.g. compact disc read only memory (CD-ROM)) or through an application store or between two user devices (e.g. smartphones). It may be distributed in person or online (e.g., downloaded or uploaded). In the case of online distribution, at least a portion of the computer program product (e.g., a downloadable app) is stored on a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server. It can be temporarily stored or created temporarily.

Claims (20)

In the wireless vacuum cleaner 100,
A suction motor 1110 that creates a vacuum inside the wireless cleaner 100;
A pressure sensor 1400 that measures flow path pressure inside the wireless vacuum cleaner 100;
A load detection sensor 1134 for measuring the load of the brush device 2000;
a memory 1900 that stores an AI model learned to infer the usage environment state of the brush device 2000; and
Comprising at least one processor 1001,
The at least one processor 1001,
Obtaining data about the flow path pressure measured by the pressure sensor 1400 from the pressure sensor 1400,
Obtaining data related to the load of the brush device 2000 through the load detection sensor 1134,
Applying data related to the flow path pressure and data related to the load of the brush device 2000 to the AI model stored in the memory 1900 to identify the current usage environment state of the brush device 2000,
Adjusting the suction force intensity of the suction motor 1110 based on the current usage environment state of the identified brush device 2000,
Cordless vacuum cleaner (100). The method of claim 1, wherein data related to the load of the brush device (2000) is:
A wireless cleaner (100) including at least one of an operating current of the brush device (2000), a voltage applied to the brush device (2000), and power consumption of the brush device (2000). The method of claim 1 or 2, wherein the current usage environment state of the brush device (2000) is:
Includes at least one of the state of the surface to be cleaned where the brush device 2000 is currently located, the relative position of the brush device 2000 within the surface to be cleaned, or the state in which the brush device 2000 is lifted from the surface to be cleaned. A wireless vacuum cleaner (100). The method of any one of claims 1 to 3, wherein the at least one processor (1001):
Based on the current usage environment state of the identified brush device (2000), determine a target RPM of the rotating brush of the brush device (2000),
A wireless cleaner (100) that transmits a control signal representing the determined target RPM of the rotating brush to the brush device (2000). The method of claim 4, wherein the at least one processor (1001):
In response to the control signal, the wireless cleaner (100) receives a signal indicating the current state of the brush device (2000) from the brush device (2000). The method of any one of claims 1 to 5, wherein the at least one processor (1001):
Based on the current usage environment state of the identified brush device 2000, determine at least one of the color or brightness of the lighting device 2300 included in the brush device 2000,
A wireless cleaner (100) that transmits a control signal representing at least one of the determined color or brightness of the lighting device (2300) to the brush device (2000). The method of any one of claims 1 to 6, wherein the at least one processor (1001):
Selecting a first AI model corresponding to the first type of the brush device 2000 from among a plurality of AI models stored in the memory 1900,
A wireless cleaner (100) that identifies the current usage environment state of the brush device (2000) by applying data related to the flow path pressure and data related to the load of the brush device (2000) to the selected first AI model. According to claim 7,
The brush device (2000) includes a first identification resistor representing the first type of the brush device (2000),
The at least one processor 1001 identifies the first type of the brush device 2000 corresponding to the first identification resistor, based on the first voltage value input to the suction motor 1110. Cordless vacuum cleaner (100). The method of claim 7, wherein the at least one processor (1001):
A wireless cleaner (100) that receives a data signal indicating the first type of the brush device (2000) from the brush device (2000). The method of any one of claims 1 to 9, wherein the at least one processor (1001):
Applying the suction force intensity of the suction motor 1110 to the AI model to modify parameter values of the AI model,
A wireless cleaner (100) that identifies the current usage environment state of the brush device (2000) by applying data related to the flow path pressure and data related to the load of the brush device (2000) to the AI model in which the parameter values have been modified. ). The method according to any one of claims 1 to 10, wherein the AI model is:
A wireless vacuum cleaner 100, including at least one of a Support Vector Machine (SVM) model, a Neural Networks model, a Random Forest model, or a Graphical Model. The method of any one of claims 1 to 11, wherein the pressure sensor 1400,
A wireless vacuum cleaner (100) including at least one of an absolute pressure sensor and a relative pressure sensor. The method of any one of claims 1 to 12, wherein the pressure sensor 1400,
A wireless cleaner (100) provided in the suction duct (40) of the cleaner main body (1000) including the suction motor (1110). The method of any one of claims 1 to 13, wherein the at least one processor (1001):
The difference between the first pressure value measured through the pressure sensor 1400 before driving the suction motor 1110 and the second pressure value measured through the pressure sensor 1400 after driving the suction motor 1110 is calculated into the flow path. A wireless vacuum cleaner (100) that obtains data on pressure. 15. The method of any one of claims 1 to 14, wherein the at least one processor (1001):
When the current usage environment of the brush device 2000 is to clean a hard floor, the suction power intensity of the suction motor 1110 is adjusted to the first intensity, which is a medium intensity,
When the current usage environment of the brush device 2000 is cleaning a mat or high-density carpet, the suction power intensity of the suction motor 1110 is adjusted to a second intensity lower than the first intensity,
The wireless vacuum cleaner (100) adjusts the suction power intensity of the suction motor (1110) to a third intensity higher than the first intensity when the current usage environment of the brush device (2000) is for cleaning a general carpet. 16. The method of any one of claims 1 to 15, wherein the at least one processor (1001):
If the current usage environment state of the brush device 2000 is a state in which the brush device 2000 is lifted a certain distance or more from the surface to be cleaned, the suction force intensity of the suction motor 1110 is adjusted to the minimum intensity, and the target RPM of the brush device 2000 is set to the highest level. A wireless vacuum cleaner (100) that decides on a low level. 17. The method of any one of claims 1 to 16, wherein the at least one processor (1001):
The wireless vacuum cleaner (100) adjusts the suction power of the suction motor (1110) to the maximum intensity when the current usage environment of the brush device (2000) is for cleaning the corner of the wall. 18. The method of any one of claims 1 to 17, wherein the at least one processor (1001):
A cordless vacuum cleaner (100) that adjusts the trip level of the brush device (2000) based on the adjusted suction strength of the suction motor (1110). 19. The method of any one of claims 1 to 18, wherein the at least one processor (1001):
Applying data related to the flow path pressure and data related to the load of the brush device 2000 to the AI model to identify a transition in the current use environment state of the brush device 2000,
A wireless vacuum cleaner (100) that adjusts the intensity of suction force of the suction motor (1110) as a transition in the current usage environment state of the brush device (2000) is identified. In the method of automatically adjusting the suction force intensity of the suction motor 1110 of the wireless vacuum cleaner 100,
Obtaining data on flow path pressure measured by the pressure sensor 1400 of the wireless cleaner 100 (S810);
Obtaining data related to the load of the brush device 2000 through the load detection sensor 1134 of the wireless cleaner 100 (S820);
By applying the data related to the flow path pressure and the data related to the load of the brush device 2000 to the AI model stored in the memory 1900 of the wireless cleaner 100, the current usage environment status of the brush device 2000 is determined. Identifying step (S830); and
A method comprising adjusting the intensity of suction force of the suction motor 1110 (S840) based on the current usage environment state of the identified brush device 2000.

Images