JP7408976B2 - air conditioner - Google Patents

Description

The present invention relates to an air conditioner.

For example, an infrared sensor is used to detect temperature unevenness, which is a condition where there is a difference in temperature at various points in an air-conditioned space where an indoor unit is installed. An air conditioner that controls air volume, wind direction, etc. in a machine has been proposed (Patent Document 1).

Japanese Patent Application Publication No. 8-128704

However, in the above-mentioned air conditioner, since control for eliminating temperature irregularities is started after detecting temperature irregularities, it takes time to eliminate temperature irregularities. Therefore, until the temperature unevenness is resolved, users who are present in the area where the temperature unevenness occurs may feel hot or cold and feel uncomfortable.

In view of these problems, it is an object of the present invention to provide an air conditioner and a method for eliminating temperature unevenness that can provide users with a comfortable air-conditioned space.

The air conditioner of the present invention includes an indoor unit, a detection section, and a prediction section. The indoor unit has a wind direction plate that changes the direction of air blown into the air-conditioned space. The detection unit periodically detects temperature distribution in a plurality of areas into which the air-conditioned space is divided. The prediction unit uses a learning model trained with different parameters during cooling operation and heating operation, and the temperature distributions of at least two of the air-conditioned spaces, to calculate a predetermined period of time from the detection point of the most recently detected temperature distribution. Predict future temperature unevenness within the air-conditioned space.

The air conditioner of the present invention can provide users with a comfortable air-conditioned space.

FIG. 1 is an explanatory diagram showing an example of an air conditioning system according to the present embodiment. FIG. 2 is an explanatory diagram showing an example of the temperature distribution area of the air-conditioned space measured by the detection unit. FIG. 3 is a block diagram showing an example of the configuration of the adapter. FIG. 4 is a block diagram showing an example of the configuration of a server device. FIG. 5 is an explanatory diagram showing an example of the contents of driving history data. FIG. 6 is an explanatory diagram showing an example of each temperature distribution used in the temperature unevenness prediction model. FIG. 7 is an explanatory diagram showing an example of an indoor unit control table. FIG. 8 is an explanatory diagram showing an example of a temperature distribution area used when determining the presence or absence of temperature unevenness during cooling operation. FIG. 9 is an explanatory diagram showing an example of a temperature distribution area used when determining the presence or absence of temperature unevenness during heating operation. FIG. 10 is a flowchart illustrating an example of processing operations of the CPU in the server device related to update processing. FIG. 11 is a flowchart illustrating an example of processing operations of the CPU in the adapter related to transmission processing. FIG. 12 is a flowchart illustrating an example of the processing operation of the control section in the indoor unit related to control processing.

Hereinafter, embodiments of the air conditioner and the method for eliminating temperature unevenness disclosed in the present application will be described in detail based on the drawings. Note that the disclosed technology is not limited to this example. Further, each of the embodiments shown below may be modified as appropriate within a range that does not cause contradiction.

FIG. 1 is an explanatory diagram showing an example of an air conditioning system 1 according to the present embodiment. The air conditioning system 1 shown in FIG. 1 includes an indoor unit 2, an adapter 3, an access point 4, a server device 5, a relay device 6, a communication terminal 7, and a communication network 8.

The indoor unit 2 is, for example, part of an air conditioner that is placed indoors and heats or cools indoor air. Note that the user of the indoor unit 2 can remotely control the indoor unit 2 by operating the remote control 9. The indoor unit 2 includes a main body 2A, a control section 2B that controls the main body 2A, a detection section 2C, and a control table 2D. The main body 2A has various devices such as an indoor fan, an expansion valve, an indoor heat exchanger, and a wind direction plate housed in a housing. The control unit 2B controls the indoor fan, expansion valve, and wind direction plate described above. The control unit 2B adjusts the opening degree of the expansion valve, flows the amount of refrigerant required to achieve the air conditioning capacity desired by the user into the indoor heat exchanger, and drives the indoor fan to perform indoor heat exchange. The indoor air that has exchanged heat with the refrigerant in the chamber is deflected by controlling the wind deflector and blown out into the air-conditioned space. This performs heating, cooling, and dehumidification of the air-conditioned space.

The detection unit 2C is a radiation sensor that measures the radiation temperature of the floor surface of the air-conditioned space in which the indoor unit 2 is installed. The detection unit 2C detects the radiant temperature of each of nine areas A1 to A9, for example, as shown in FIG. 2, where the floor surface of the air-conditioned space is divided into a plurality of areas. In Fig. 2, the area on the near side when viewed from the air outlet of the indoor unit 2 is areas A1 to A3, the area on the back side when viewed from the air outlet of the indoor unit 2 is areas A7 to A9, and the area on the near side and the back area are areas A7 to A9. The intermediate areas between the side areas are designated as areas A4 to A6. Furthermore, areas A1, A4, and A7 are areas to the left (L: Left) when viewed from the air outlet of the indoor unit 2, and areas A3, A6, and A9 are to the right (R:) when viewed from the air outlet of the indoor unit 2. Areas A2, A5, and A8 in the C (Center) direction are areas A2, A5, and A8 in the C (Center) direction when viewed from the air outlet of the indoor unit 2.

In this embodiment, the radiant temperature of each area A1 to A9 detected by the detection unit 2C is regarded as the temperature distribution of the space corresponding to each area A1 to A9 (the space above each area A1 to A9), which will be described later. Determine temperature unevenness.

The adapter 3 has a communication function for connecting the indoor unit 2 and the access point 4 by wireless communication, and a control function for controlling the indoor unit 2 using AI. The adapter 3 is provided for each indoor unit 2. The access point 4 is a device that connects the adapter 3 and the communication network 8 by wireless communication using, for example, WLAN (Wireless Local Area Network). The communication network 8 is, for example, a communication network such as the Internet. The server device 5 has a function for generating a learning model used when the AI of the adapter 3 controls the indoor unit 2, a database for storing driving history data, and the like. The server device 5 is placed in a data center, for example.

The relay device 6 has a function of communicatively connecting to the communication network 8 and also communicatively connecting to the server device 5 . The relay device 6 receives driving history data and the like used for generating a learning model or updating the learning model in the server device 5 from the indoor unit 2 via the adapter 3 and the communication network 8, and transmits it to the server device 5. Further, the relay device 6 transmits the learning model generated or updated by the server device 5 to the adapter 3 via the communication network 8. The relay device 6 is placed, for example, in a data center.

The relay device 6 includes a first relay section 6A, a second relay section 6B, and a third relay section 6C. The first relay unit 6A relays various data related to AI control between the adapter 3 and the server device 5. Specifically, the first relay unit 6A transmits the driving history data, etc. used for generating or updating the learning model received from the adapter 3 via the communication network 8 to the server device 5, and also transmits the driving history data, etc. Alternatively, the updated learning model is sent to the adapter 3 via the communication network 8. The second relay unit 6B transmits operating conditions of the indoor unit 2 (operating modes such as cooling/heating, set temperature, etc.) set by the user from outside using a communication terminal 7, which will be described later, to the access point 4 and the communication terminal. 8 and transmits it to the indoor unit 2 via the communication network 8, access point 4, and adapter 3. The third relay unit 6C receives external data such as a weather forecast via the communication network 8, and transmits the received external data to the server device 5, for example. Further, the third relay unit 6C transmits the received external data to the adapter 3 via the communication network 8 and the access point 4.

FIG. 3 is a block diagram showing an example of the configuration of the adapter 3. As shown in FIG. The adapter 3 shown in FIG. 3 includes a first communication section 11, a second communication section 12, a storage section 13, and a CPU (Central Processing Unit) 14. The first communication unit 11 is, for example, a communication IF (Interface) such as a UART (Universal Asynchronous Receiver Transmitter), which is communicatively connected to the control unit 2B in the indoor unit 2. The second communication unit 12 is, for example, a communication IF such as a WLAN, which is communicatively connected to the access point 4 . The storage unit 13 includes, for example, a ROM (Read Only Memory) and a RAM (Random Access Memory), and stores various information such as data and programs. The CPU 14 controls the entire adapter 3.

The storage unit 13 includes a driving history memory 13A that temporarily stores driving history data acquired from the indoor unit 2, a model memory 13B that stores a learning model acquired from the server device 5, and an external memory 13C that stores external data. has.

The CPU 14 includes an acquisition section 14A, a transmission section 14B, a reception section 14C, a setting section 14D, and a prediction control section 14E (corresponding to the prediction section of the present invention). The acquisition unit 14A acquires driving history data from the indoor unit 2 at predetermined intervals, for example, every 5 minutes. The acquisition unit 14A stores driving history data acquired every 5 minutes in the driving history memory 13A. Note that the driving history data will be explained in detail later using FIG. 5.

The transmitter 14B transmits the driving history data stored in the driving history memory 13A to the access point 4, and the access point 4 transmits the received driving history data to the relay device 6 via the communication network 8. The first relay unit 6A of the relay device 6 transmits the received driving history data to the server device 5. The receiving unit 14C receives, from the server device 5, a learning model such as a temperature unevenness prediction model for predicting temperature unevenness in areas A1 to A9 shown in FIG. 2, for example. Specifically, the server device 5 transmits the learning model to the relay device 6, and the first relay unit 6A of the relay device 6 transmits the received learning model to the access point 4 via the communication network 8. 4 transmits the received learning model to the receiving section 14C of the adapter 3. Note that the receiving unit 14C stores the received learning model in the model memory 13B. The setting unit 14D applies the learning model stored in the model memory 13B to the predictive control unit 14E.

The predictive control unit 14E controls the control unit 2B of the indoor unit 2 based on the temperature unevenness prediction model stored in the model memory 13B, for example, when the indoor temperature is stable. Note that the stable state of the indoor temperature means that the temperature difference between the indoor temperature (the temperature of the entire air-conditioned space, not the radiant temperature of each area A1 to A9) and the set temperature of the indoor unit 2 is a predetermined threshold, for example, ±0. This is a case within .5. For convenience of explanation, the case where the predictive control unit 14E controls the control unit 2B in the indoor unit 2 based on the learning model has been exemplified; however, the predictive control unit 14E controls the main body of the indoor unit 2 based on the learning model. 2A may be directly controlled. Further, the predictive control unit 14E transmits a control mode based on the learning model to the control unit 2B. In other words, the predictive control section 14E may indirectly control the main body 2A via the control section 2B, and this can be changed as appropriate.

FIG. 4 is a block diagram showing an example of the configuration of the server device 5. As shown in FIG. The server device 5 shown in FIG. 4 communicates with the adapters 3 provided in the plurality of indoor units 2 via the relay device 6, and includes a communication section 31, a storage section 32, and a CPU 33. The communication unit 31 is a communication IF that communicates with the relay device 6 . The storage unit 32 includes, for example, an HDD (Hard Disk Drive), ROM, RAM, etc., and stores various information such as data and programs. The CPU 33 controls the server device 5 as a whole.

The storage unit 32 in the server device 5 includes a data memory 32A and a model storage unit 32B. The data memory 32A stores operation history data of each indoor unit 2 received from each adapter 3 for each indoor unit 2. As will be described later, each indoor unit 2 has an air conditioner ID for identifying the indoor unit 2, and when each indoor unit 2 transmits operation history data, it uses this air conditioner ID. It is also sent. Then, the server device 5 that has received the driving history data from each indoor unit 2 stores the driving history data in the data memory 32A for each air conditioner ID included in the received signal. The model storage unit 32B stores learning models generated or updated by the server device 5. The CPU 33 in the server device 5 includes a model learning section 33A, a receiving section 33B, and a transmitting section 33C.

The model learning unit 33A receives driving history data from the adapters 3 of the plurality of indoor units 2 via the access point 4, the communication network 8, and the relay device 6. Then, the model learning unit 33A performs learning using the driving history data for N weeks (for example, 3 weeks) stored in the data memory 32A from each adapter 3, and based on the learning results, the model learning unit 33A performs learning for each indoor unit 2. Generate or update a learning model. The learning model includes, for example, a temperature unevenness prediction model that predicts temperature unevenness in indoor areas A1 to A9 described in this embodiment.

The model learning unit 33A then stores the newly generated learning model or the learning model that is an updated version of the existing learning model in the model storage unit 32B. The receiving unit 33B receives driving history data and the like from each adapter 3 via the access point 4, the communication network 8, and the relay device 6. The transmitting unit 33C transmits the learning model newly generated for each indoor unit 2 by the model learning unit 33A or the learning model obtained by updating the existing learning model to each indoor unit via the relay device 6, the communication network 8, and the access point 4. Send to adapter 3 of machine 2.

Note that the indoor unit 2 is connected to an outdoor unit (not shown) via refrigerant piping, and the outdoor unit is equipped with an outdoor fan, a compressor, and the like. Moreover, the communication terminal 7 is a terminal device such as a user's smartphone.

FIG. 5 is an explanatory diagram showing an example of the contents of driving history data. The driving history data includes, for example, driving state, driving mode, set temperature, indoor temperature, indoor humidity, air volume, wind direction, human sensor, temperature distribution, indoor heat exchanger temperature, outdoor temperature, and the like.

The operating state is an ON/OFF state of operation of the indoor unit 2. The operation mode is an operation mode of the indoor unit 2 such as cooling or heating. The set temperature is the indoor target temperature in the room where the indoor unit 2 is used. The indoor temperature is the actual temperature in the room where the indoor unit 2 is used, for example, the heat exchange temperature of the indoor heat exchanger. The indoor humidity is the actual humidity in the room where the indoor unit 2 is used. The air volume is the volume of conditioned air blown out from the indoor unit 2. Note that the air volume is expressed, for example, by the number of rotations of the indoor fan of the indoor unit 2. The wind direction is the direction of the conditioned air blown out from the indoor unit 2. Note that there are three types of wind directions: a left direction (L), a center direction (C), and a right direction (R) when viewed from the air outlet side of the indoor unit 2. The human sensor detects the presence or absence of people in the room and the amount of activity. The temperature distribution is the result of detection of the temperature of the indoor floor and walls by the radiation sensor of the indoor unit 2. The temperature distribution is, for example, the temperature distribution of the radiant temperature of the floor surface for each of the nine areas "A1" to "A9" shown in FIG. The indoor heat exchanger temperature is the temperature of an indoor heat exchanger (not shown) that forms a part of the main body 2A of the indoor unit 2. The outdoor temperature is the outdoor temperature detected by a temperature sensor of an outdoor unit (not shown). The adapter 3 collects the outdoor temperature detected by the temperature sensor of the outdoor unit via the indoor unit 2. Although not shown, the operation history data includes, for example, a time stamp indicating the year, month, date, hour, minute, and second at the time of data acquisition, and an air conditioner that is given to the indoor unit 2 to identify the air conditioner such as the indoor unit 2. There is also hourly cloud amount collected from weather forecast data acquired by the ID and adapter 3 via the communication network 8 and access point 4.

When generating or updating the temperature unevenness prediction model of this embodiment, operating history data such as temperature distribution, indoor temperature, set temperature, outdoor temperature, timestamp, cloud cover, etc., are used as parameters for learning. Use as. Note that the parameters used will be explained in detail later.

The temperature unevenness prediction model uses the actual measured values of the temperature distribution for the most recent three times among the radiant temperatures (hereinafter referred to as temperature distribution) of each area A1 to A9 that are actually measured every 5 minutes. This is a learning model that predicts temperature unevenness after a predetermined period of time, for example, 10 minutes from the time when the temperature distribution is actually measured. FIG. 6 is an explanatory diagram showing an example of each temperature distribution used in the temperature unevenness prediction model. As shown in Figure 6, the last three measured values of temperature distribution are the actual measured value of the current temperature distribution, the measured value of the current temperature distribution, and the actual measured value of the temperature distribution 5 minutes ago from the current value, among the measured values of the temperature distribution obtained from the indoor unit 2 every 5 minutes. These are the actual measured value of the temperature distribution and the actual measured value of the temperature distribution 10 minutes ago from now.

The predictive control unit 14E of the adapter 3 applies the actual measured values of the temperature distribution for the last three times to the temperature unevenness prediction model, and calculates the temperature distribution after a predetermined period of time, for example, 10 minutes from the time when the temperature distribution was actually measured most recently. Temperature unevenness in the air-conditioned space corresponding to each area A1 to A9 is predicted. The transmitting unit 14B of the adapter 3 transmits the prediction result of temperature unevenness predicted by the predictive control unit 14E to the control unit 2B of the indoor unit 2.

The control unit 2B of the indoor unit 2 receives the prediction result of temperature unevenness after a predetermined time from the adapter 3. Further, the control unit 2B obtains the actual measured value of the current temperature distribution through the detection unit 2C. The control unit 2B uses the temperature distribution of the obtained actual measurement values to determine whether there is temperature unevenness in the air-conditioned spaces corresponding to the current areas A1 to A9. The control unit 2B controls the orientation of the wind direction plate based on the prediction result of the presence or absence of temperature unevenness after 10 minutes and the current judgment result of the presence or absence of temperature unevenness determined using the temperature distribution of the actual measurement value. The conditioned air blown out from the machine 2 is deflected. Specifically, if it is determined that there is temperature unevenness, the air direction plate is operated to direct the conditioned air to the area where the temperature unevenness exists to eliminate the temperature unevenness, and if there is no temperature unevenness, the indoor unit 2 Operate the wind direction plate so that the conditioned air is directed toward the center of the conditioned space relative to the installation position. Note that the operation of the wind direction plate is performed at predetermined intervals, for example, every 40 minutes. In other words, once the wind direction board is operated, the direction of the wind direction board is not changed for 40 minutes. The reason for this is that if the wind direction plate is changed frequently, there is a possibility that the user may feel uncomfortable or uncomfortable.

FIG. 7 is an explanatory diagram showing the control table 2D of the indoor unit 2 in this embodiment. The control table 2D shown in FIG. 7 associates the determination result of temperature unevenness based on the actual measured value of the temperature distribution, the predicted result of temperature unevenness based on the temperature unevenness prediction model, and the contents of the wind direction control. The temperature unevenness determination result based on the actual measured value of the temperature distribution is the determination result of the control unit 2B which has determined the presence or absence of temperature unevenness from the actual measured value of the temperature distribution. The temperature unevenness prediction result is a prediction result of temperature unevenness after a predetermined time predicted by the temperature unevenness prediction model. The wind direction control content is control content for controlling the direction of the wind direction plate of the indoor unit 2.

For example, if the temperature unevenness determination result based on the actual measured value of the temperature distribution is "temperature unevenness" and the predicted temperature unevenness result is "temperature unevenness", the control unit 2B will , the direction of the wind direction plate is controlled in a direction that eliminates temperature unevenness. In addition, if the temperature unevenness determination result based on the measured value is, for example, that there is temperature unevenness in the L direction of the indoor unit 2 (areas A1/A4/A7 in FIG. 2), turn the air conditioner with the wind direction plate facing the L direction. send air.

For example, if the temperature unevenness determination result based on the actual measured value of the temperature distribution is "temperature unevenness" and the predicted temperature unevenness result is "no temperature unevenness", the control unit 2B will , the direction of the wind direction plate is controlled in a direction that eliminates temperature unevenness.

For example, when the temperature unevenness determination result based on the actual measurement value of the temperature distribution is "no temperature unevenness" and the temperature unevenness prediction result is "temperature unevenness", the control unit 2B eliminates the temperature unevenness based on the temperature unevenness prediction result. Control the orientation of the wind direction plate in the direction of the wind direction.

For example, when the temperature unevenness determination result based on the actual measured value of the temperature distribution is "no temperature unevenness" and the temperature unevenness prediction result is "no temperature unevenness", the control unit 2B directs the direction of the wind direction plate toward the center of the room. Control.

Next, a method for determining the presence or absence of temperature unevenness in actual measured values of temperature distribution, which is performed by the control unit 2B, will be specifically described using FIGS. 8 and 9. The method for determining the presence or absence of temperature unevenness differs depending on whether the indoor unit 2 is in a cooling operation or a heating operation.

First, a method for determining the presence or absence of temperature unevenness during cooling operation will be explained. FIG. 8 is an explanatory diagram showing an example of a temperature distribution area used when determining the presence or absence of temperature unevenness during cooling operation. In cooling operation, the wind direction plate is oriented horizontally, but the cold air blown out from the indoor unit 2 descends toward the floor. , target area). Therefore, the control unit 2B during cooling operation targets areas A4, A5, and A6, which are reached by the cold air blown out from the indoor unit 2, out of all the temperature distribution areas A1 to A9. The temperatures of areas A4, A5, and A6 are used to determine the presence or absence of temperature unevenness.

Next, the control unit 2B selects the minimum temperature from the temperatures in the target areas A4, A5, and A6. Then, the control unit 2B compares the temperature with the minimum value for each target area A4, A5, and A6, and determines that the temperature difference between the temperature of each target area and the minimum value is equal to or higher than a predetermined temperature, for example, 1.25°C. In this case, the target area has a higher temperature than the area with the minimum value, and it is determined that there is temperature unevenness in the target area. Further, the control unit 2B determines that there is no temperature unevenness when the temperature difference between the radiant temperature and the minimum value for each target area is less than 1.25°C.

Next, a method for determining the presence or absence of temperature unevenness during heating operation will be described. FIG. 9 is an explanatory diagram showing an example of a temperature distribution area used when determining the presence or absence of temperature unevenness during heating operation. During heating operation, warm air blown out from the indoor unit 2 rises toward the ceiling. Therefore, during heating operation, the wind direction plate is directed downward in order to allow the warm air blown out to reach the floor surface as much as possible. At this time, the warm air blown out evenly spreads over areas A1 to A9, so during heating operation, all of areas A1 to A9 become target areas used to determine the presence or absence of temperature unevenness.

First, the control unit 2B controls all areas A1 to A9 of the temperature distribution to the L area group (A1, A4, A7), the C area group (A2, A5, A8), and the R area group (A3, A6, A9). Divide into three area groups. Next, the control unit 2B calculates the average temperature of each of the areas A1 to A9. Next, the control unit 2B sets the minimum temperature among the temperatures of each area of the L area group (A1, A4, A7) as the minimum temperature of the L area group. Further, the control unit 2B sets the minimum temperature among the temperatures of each area of the C area group (A2, A5, A8) as the minimum temperature of the C area group. Further, the control unit 2B sets the minimum temperature among the temperatures of each area of the R area group (A3, A6, A9) as the minimum temperature of the R area group. Then, the control unit 2B compares the minimum temperature and average temperature of each area group for each area group, and if the temperature difference between the minimum temperature and the average temperature in each area group is 1.25°C or more, the control unit 2B The minimum temperature of the group is lower than the average temperature, and it is determined that there is temperature unevenness within the area group. Furthermore, if the temperature difference between the minimum temperature and the average temperature in each area group is less than 1.25°C, the control unit 2B determines that there is no temperature unevenness in each area group.

The control unit 2B uses the method described above to determine the presence or absence of temperature unevenness in the air-conditioned spaces corresponding to the current areas A1 to A9 using the actual measured values of temperature distribution in each case of cooling operation and heating operation. Determine.

During cooling operation, when the control unit 2B determines the presence or absence of temperature unevenness in the air-conditioned space corresponding to each of the current areas A1 to A9 using the actual measured value of the temperature distribution, the control unit 2B uses the actual measured value of the temperature distribution to determine the presence or absence of temperature unevenness in the air-conditioned space. Compare the temperature of each target area A4, A5, and A6 with the minimum value of each temperature of target areas A4, A5, and A6, and if the temperature difference between the temperature of each target area A4, A5, and A6, and the minimum value is 1.25 degrees Celsius or more. If at least one certain area exists, it is determined that there is temperature unevenness in the air-conditioned spaces corresponding to the current areas A1 to A9. In addition, when the temperature difference between the temperature and the minimum value in all target areas A4, A5, and A6 is less than 1.25°C, the control unit 2B controls the temperature in the air-conditioned space corresponding to each of the current areas A1 to A9. It is determined that there is no unevenness. In other words, if there is a temperature difference between at least two of the areas, the control unit 2B determines that there is temperature unevenness because the temperature of the target area is higher than the temperature of the area with the minimum value. When it is determined that there is temperature unevenness, the control unit 2B controls the wind direction plate so that the air conditioning airflow is supplied to the area where the temperature unevenness occurs.

During heating operation, when the control unit 2B determines the presence or absence of temperature unevenness in the air-conditioned space corresponding to each of the current areas A1 to A9 using the actual measured value of the temperature distribution, If there is at least one area where the temperature difference between each minimum temperature value and the average temperature is 1.25°C or more, it is determined that there is temperature unevenness in the air-conditioned space corresponding to each of the current areas A1 to A9. do. In addition, if the temperature difference between each minimum value and the average temperature for all target area groups is less than 1.25°C, the control unit 2B determines that there is currently no temperature unevenness in the air-conditioned spaces corresponding to each area A1 to A9. It is determined that That is, when there is a temperature difference between at least two area groups among each area group, the control unit 2B determines that there is temperature unevenness because the minimum temperature of the target area group is lower than the average temperature. When it is determined that there is temperature unevenness, the control unit 2B controls the wind direction plate so that the air conditioning airflow is supplied to the area where the temperature unevenness occurs.

As described above, when determining the presence or absence of temperature unevenness in an air-conditioned space, the target areas used for determination are different during cooling operation and during heating operation. Therefore, the parameters used when learning or updating the temperature unevenness prediction model differ between cooling operation and heating operation, as described below.

The parameters used for learning the temperature unevenness prediction model during cooling operation are (outdoor temperature - indoor temperature), set temperature, actual measured value of temperature distribution, left (L) direction as seen from indoor unit 2, and center (C) direction. There are the equivalent amount of heat carried in the direction and right (R) direction, a time flag, cloud amount, etc. The actual measured value of the temperature distribution is the temperature detected by the detection unit 2C for each of the areas "A1" to "A9". The equivalent amount of heat carried to the LCR can be calculated using, for example, the heat exchanger temperature, the suction temperature, the fan rotation speed, and the current direction of the wind direction plate. The suction temperature is the temperature of the indoor air sucked into the indoor unit 2, and the wind direction ratio is the wind direction ratio (L:C:R) for each wind direction with respect to the entire outlet of the indoor unit 2. The reason why (outdoor temperature - indoor temperature) is used as a parameter for the temperature unevenness prediction model during cooling operation is to reflect the influence of solar radiation.

The parameters used for learning the temperature unevenness prediction model during heating operation include, for example, the outdoor temperature, the average value of the radiant temperature of the floor detected by the detection unit 2C, the actual measured value of the temperature distribution, the equivalent amount of heat carried to the LCR, There are time flags, cloud cover, etc. The average value of the radiant temperature is the average value of the temperatures detected by the detection units 2C in areas "A1" to "A9". The reason why the average value of radiant temperature is used to generate the temperature unevenness prediction model during heating operation is that during heating operation, the warm air blown out from indoor unit 2 rises toward the ceiling. This is to take into consideration the fact that the floor temperature of the area tends to change easily, that is, the floor temperature tends to vary from area to area.

Note that when the control unit 2B determines the presence or absence of temperature unevenness during heating operation, the temperature difference between the maximum value and the minimum value of the actually measured temperatures in each area A1 to A9 is determined as a first predetermined temperature, for example, 15°C. In the above case, it is determined that another heat source (for example, a heater such as a gas fan heater) is present in the air-conditioned space. Furthermore, when the control unit 2B determines that there is another heater in the air-conditioned space, it notifies the adapter 3 of the determination result. When the adapter 3 receives a determination result that there is another heater in the air-conditioned space, it does not predict temperature unevenness using the temperature distribution of the most recent three measured values. Further, the adapter 3 transmits the determination result received from the control unit 2B to the server device 5. Until it is determined that there is no other heater in the air-conditioned space, the server device 5 uses the 5-minute period operation history data received while there is another heater in the air-conditioned space to learn the temperature unevenness prediction model ( generation) or update.

Note that, after it is determined by the method described above that there is another heater in the air-conditioned space, the control unit 2B determines that the temperature difference between the maximum value and the minimum temperature in the temperature distribution of the air-conditioned space is a first predetermined temperature difference. When the temperature is lower than, for example, 15° C., it is determined that there is no other heater in the air-conditioned space, and the determination result is transmitted to the server device 5 via the adapter 3.

Next, the operation of the air conditioning system 1 of this embodiment will be explained. FIG. 10 is a flowchart showing an example of the processing operation of the CPU 33 in the server device 5 related to the learning model update process. Note that the CPU 33 generates a temperature unevenness prediction model using operation history data acquired up to N weeks after the air conditioning system 1 was installed and started, that is, N weeks worth of operation history data, and then Each time the CPU 33 acquires new driving history data, it updates the temperature unevenness prediction model using N weeks' worth of driving history data including this new driving history data.

In the air conditioning system 1 of this embodiment, the receiving unit 33B of the CPU 33 in the server device 5 determines whether or not driving history data has been received from the adapter 3 (step S11). When the receiving unit 33B receives the driving history data (Step S11: Yes), the receiving unit 33B stores the received driving history data in the data memory 32A (Step S12).

Upon receiving the driving history data from the adapter 3, the model learning unit 33A updates the temperature unevenness prediction model based on the driving history data stored in the data memory 32A (step S13). The model learning unit 33A uses (outdoor temperature - indoor temperature), set temperature, actual measured value of temperature distribution, equivalent amount of heat carried to the LCR, time flag, cloud cover, etc. from the operation history data to determine temperature unevenness during cooling operation. Update the predictive model. In addition, the model learning unit 33A uses the outdoor temperature, the average value of the radiant temperature, the actual measured value of the temperature distribution, the equivalent amount of heat carried to the LCR, the time flag, the amount of clouds, etc. in the operation history data to improve the temperature unevenness during the heating operation. Update the predictive model. For convenience of explanation, in step S13, the model learning unit 33A updates the temperature unevenness prediction model based on the driving history data stored in the data memory 32A. If the driving history data is almost the same as that used to generate the temperature unevenness prediction model, the temperature unevenness prediction model is not updated.

The model learning unit 33A stores the updated temperature unevenness prediction model in the storage unit 32B (step S14). Further, the transmitter 33C in the CPU 33 transmits the temperature unevenness prediction model to the adapter 3 (step S15), and ends the processing operation shown in FIG. 10. Further, if the receiving unit 33B has not received the driving history data (step S11: No), the receiving unit 33B ends the processing operation shown in FIG. 10.

As explained above, the server device 5 uses the driving history data acquired from the adapter 3 to generate or update the learning model. As a result, the server device 5 can maintain high accuracy of the learning model.

For convenience of explanation, the case where the temperature unevenness prediction model is generated or updated when the driving history data is for N weeks has been illustrated, but this is not limited to the prediction model for N weeks or the temperature portion. The learning model can also be changed as appropriate depending on the amount of historical data stored.

FIG. 11 is a flowchart showing an example of the processing operation of the CPU 14 in the adapter 3 related to the process of transmitting the temperature unevenness prediction result to the indoor unit 2. In FIG. 11, the acquisition unit 14A in the CPU 14 in the adapter 3 determines whether or not the last three measured values of the temperature distribution including the last acquired actual measured value of the temperature distribution have been acquired, that is, the last three measured values of the temperature distribution have been acquired. (Step S21). Note that the obtained actual measured values of the temperature distribution for the last three times are stored in the external memory 13C of the storage unit 13.

When the prediction control unit 14E in the CPU 14 has acquired the actual measured values of the temperature distribution for the most recent three times (step S21: Yes), the predictive control unit 14E in the CPU 14 applies the acquired actual measured values of the temperature distribution for the most recent three times to the temperature unevenness prediction model, Temperature unevenness in the air-conditioned space after a predetermined period of time is predicted (step S22). Further, the prediction control unit 14E stores the prediction result of temperature unevenness in the external memory 13C (step S23). Furthermore, the transmitter 14B in the CPU 14 transmits the prediction result of temperature unevenness to the indoor unit 2 (step S24), and ends the processing operation shown in FIG. 11. If the predictive control unit 14E has not acquired the last three measured values of the temperature distribution (step S21: No), the predictive control unit 14E ends the processing operation shown in FIG. 11.

As explained above, the adapter 3 applies the actual measured values of the temperature distribution for the last three times to the temperature unevenness prediction model, predicts the temperature unevenness after a predetermined time, and sends the temperature unevenness prediction result to the indoor unit 2. . As a result, the indoor unit 2 can control the wind direction plate, which will be described next, using the prediction result of temperature unevenness 10 minutes ahead.

FIG. 12 is a flowchart illustrating an example of the processing operation of the control section 2B of the indoor unit 2 related to determining the presence or absence of temperature unevenness and controlling the wind direction plate based on the determination result. In FIG. 12, the control unit 2B of the indoor unit 2 detects the current indoor temperature, which is the temperature of the entire air-conditioned space (step S31), and determines that the temperature difference between the current indoor temperature and the set temperature is within ±0.5°C. It is determined whether or not (step S32). If the temperature difference between the current indoor temperature and the set temperature is within ±0.5°C (step S32: Yes), the control unit 2B determines that the indoor temperature is stable and predicts temperature unevenness in the air-conditioned space. It is determined whether the result has been received from the adapter 3 (step S33).

When the control unit 2B receives from the adapter 3 the prediction result of temperature unevenness in the air-conditioned space obtained by the adapter 3 in the process of step S22 in the flowchart of FIG. 11 (step S33: Yes), the control unit 2B acquires the actual measured value of the temperature distribution. (Step S34). Furthermore, the control unit 2B determines whether there is temperature unevenness in the obtained temperature distribution (step S34A).

Next, the control unit 2B refers to the control table 2D and determines whether to use the temperature unevenness determination result based on the actual measured value of the temperature distribution (step S35). When using the temperature unevenness determination result based on the actual measured value of the temperature distribution (step S35: Yes), the control unit 2B controls the wind direction plate (wind direction control) based on the temperature unevenness determination result based on the actual measured value of the temperature distribution (step S36).

After controlling the wind direction plate, the control unit 2B starts a timer for a first predetermined time (step S37). Here, the first predetermined time is a time period for preventing the direction of the wind direction plate from being changed frequently after controlling the direction of the wind direction plate, and is, for example, 40 minutes. Users may feel strange or uncomfortable if the direction of the wind direction board changes frequently, so the direction of the wind direction board is changed immediately after the direction of the wind direction board is controlled until the first predetermined time period has elapsed. Suppress the operation of

The control unit 2B determines whether a first predetermined time has elapsed since the timer was started in S37, that is, whether the first predetermined time timer has timed out (step S38). If the first predetermined time timer has not timed up (step S38: No), the control unit 2B returns the process to step S38 and waits for the first predetermined time timer to time up. On the other hand, when the first predetermined time timer times up (step S38: Yes), the control unit 2B resets the first predetermined time timer (step S39) and returns the process to step S31.

In addition, if the temperature difference between the current indoor temperature and the set temperature is not within ±0.5°C (step S32: No), or if the prediction result of temperature unevenness is not received from the adapter 3, the control unit 2B (Step S33: No) turns the direction of the wind direction plate toward the center and returns the process of Step S31.

In step S35, if the temperature unevenness determination result based on the actual measurement value of the temperature distribution is not used (step S35: No), the control unit 2B determines whether or not the temperature unevenness prediction result is used (step S40). When using the temperature unevenness prediction result (step S40: Yes), the control unit 2B controls the wind direction plate based on the temperature unevenness prediction result (step S41), and starts the first predetermined time timer. The process returns to step S37.

Further, if the prediction result of temperature unevenness is not used (step S40: No), the control unit 2B fixes the wind direction of the wind direction plate (step S42), and performs the process of step S37 to start the first predetermined time timer. Return to

As explained above, when the temperature difference between the indoor temperature and the set temperature is within ±0.5°C, and when the prediction result of temperature unevenness is received from the adapter 3, the indoor unit 2 uses the actual measured value of the temperature distribution. , determine temperature unevenness. As a result, the indoor unit 2 obtains a prediction result of temperature unevenness after a predetermined period of time and a determination result of temperature unevenness based on the actual measured value of the temperature distribution.

If the temperature unevenness judgment result based on the actual measured value of the temperature distribution is "temperature unevenness" and the predicted temperature unevenness result is "temperature unevenness", the indoor unit 2 , the direction of the wind direction plate is controlled in a direction that eliminates temperature unevenness. As a result, the currently occurring temperature unevenness in the air-conditioned space can be quickly eliminated.

If the temperature unevenness determination result based on the actual measured value of the temperature distribution is "temperature unevenness" and the predicted temperature unevenness result is "no temperature unevenness", the indoor unit 2 , the direction of the wind direction plate is controlled in a direction that eliminates temperature unevenness. As a result, the currently occurring temperature unevenness in the air-conditioned space can be preferentially eliminated.

If the temperature unevenness determination result based on the actual measured value of temperature distribution is "no temperature unevenness" and the temperature unevenness prediction result is "temperature unevenness", the indoor unit 2 eliminates the temperature unevenness based on the temperature unevenness prediction result. Control the orientation of the wind direction plate in the direction of the wind direction. As a result, temperature unevenness that is predicted to occur in the air-conditioned space in the future can be prevented, and the discomfort felt by the user due to temperature unevenness can be reduced.

If the temperature unevenness determination result based on the actual measured value of temperature distribution is "no temperature unevenness" and the predicted temperature unevenness result is "no temperature unevenness", the indoor unit 2 orients the wind direction plate toward the center of the air-conditioned space. Control as follows. Thereby, it is possible to agitate the airflow in the air-conditioned space and appropriately prevent the occurrence of temperature unevenness.

The air conditioning system 1 of this embodiment uses a learning model trained with different parameters during cooling operation and heating operation, and temperature distributions of at least two air-conditioned spaces, to calculate the most recently detected temperature distribution. Predict temperature unevenness after a predetermined time from the time of detection. As a result, temperature unevenness after a predetermined period of time can be predicted.

Furthermore, when it is predicted that there will be temperature unevenness based on the prediction result of temperature unevenness, the air conditioning system 1 proactively controls the wind direction plate so that the temperature unevenness does not occur. As a result, temperature unevenness can be eliminated in advance and a comfortable air-conditioned space can be provided to the user.

The air conditioning system 1 operates so that the currently occurring temperature unevenness is resolved when it is determined that temperature unevenness has occurred from the temperature distribution of the air conditioned space detected at a first predetermined time interval (40 minutes). Control the wind deflector. As a result, the currently occurring temperature unevenness can be quickly resolved, and a comfortable air-conditioned space can be provided to the user.

Furthermore, if there is no temperature unevenness in the temperature distribution and it is predicted that temperature unevenness will occur in the air-conditioned space after a predetermined time, the air conditioner will adjust the wind direction so that the temperature unevenness after a predetermined time will be eliminated. Control the board. As a result, temperature irregularities that will occur in the future can be eliminated in advance, and a comfortable air-conditioned space can be provided to users.

Although the adapter 3 of this embodiment has been exemplified to transmit the operation history data of the indoor unit 2 to the server device 5 via the relay device 6, it is possible to send the operation history data as it is without passing through the relay device 6. , may be transmitted to the server device 5, and can be changed as appropriate.

Further, although the process of determining whether the temperature difference between the current indoor temperature and the set temperature in step S32 shown in FIG. 12 is within ±0.5°C has been illustrated, the threshold value of the temperature difference is ±0.5 The temperature is not limited to °C and can be changed as appropriate.

In addition, when the temperature unevenness determination result based on the actual measured value of the temperature distribution is "temperature unevenness" and the temperature unevenness prediction result is "temperature unevenness exists", the control unit 2B is directed to eliminate the temperature unevenness based on the actual measured value of the temperature distribution. An example of controlling the direction of the wind direction plate is given below. However, the direction of the wind direction plate may be controlled in a direction that eliminates the temperature unevenness based on both the temperature unevenness determination result based on the actual measurement value of the temperature distribution and the temperature unevenness prediction result.

Moreover, although the case where the control part 2B determines the presence or absence of temperature unevenness based on the measured value of temperature distribution was illustrated, the determination of the presence or absence of temperature unevenness may be performed on the adapter 3 side, and can be changed as appropriate.

The temperature unevenness prediction model is based on the most recent three measured values of temperature distribution, and the case where the temperature in the air-conditioned space is uneven is exemplified, but it is not limited to the most recent three measured values of temperature distribution. times, the most recent two times, the most recent three times or more, and can be changed as appropriate. Further, the temperature unevenness to be predicted is not limited to 10 minutes ahead, but may be a temperature distribution 15 minutes ahead from the detection point of the latest temperature distribution, for example, and can be changed as appropriate.

The temperature unevenness prediction model predicts temperature unevenness within an air-conditioned space, calculates the probability of occurrence of an area where temperature unevenness will occur in the temperature distribution, and predicts the area to be an area where temperature unevenness occurs if the probability of occurrence exceeds a predetermined threshold. It can be changed as appropriate.

Further, although the first predetermined time timer for monitoring the switching timing of the wind direction plate is set to 40 minutes, it is not limited to this and can be changed as appropriate.

In addition, the control unit 2B controls the control unit 2B to control the temperature difference between the maximum and minimum temperatures in the temperature distribution of the air-conditioned space when the temperature difference is a first predetermined temperature, for example, 15° C. or more, during the heating operation. The following is an example of a case where it is determined that there is an opportunity. However, the first predetermined temperature is not limited to 15° C. and can be changed as appropriate. Moreover, although the case where the control part 2B executes the process of determining whether there is another heater in the air-conditioned space is illustrated, the CPU 14 in the adapter 3 may execute the process, and the process can be changed as appropriate.

Moreover, in the temperature unevenness prediction model, a case where temperature unevenness in an air-conditioned space is predicted based on the last three measured temperature distribution values is exemplified. However, the learning model may predict the temperature distribution in each area within the air-conditioned space based on the last three measured values of the temperature distribution, and may transmit the prediction results to the control unit 2B. In this case, the control unit 2B uses the temperature distribution that is the prediction result to determine the presence or absence of temperature unevenness during cooling operation or the result of determining the presence or absence of temperature unevenness during heating operation. The prediction result may be obtained and can be changed as appropriate.

Further, each component of each part shown in the drawings does not necessarily have to be physically configured as shown in the drawings. In other words, the specific form of dispersion/integration of each part is not limited to what is shown in the diagram, but all or part of it may be functionally or physically distributed/integrated in arbitrary units depending on various loads, usage conditions, etc. can be configured.

Furthermore, various processing functions performed in each device can be performed in whole or in part on a CPU (Central Processing Unit) (or a microcomputer such as an MPU (Micro Processing Unit) or an MCU (Micro Controller Unit)). You may also choose to execute it. Further, various processing functions may be executed in whole or in part on a program that is analyzed and executed by a CPU (or a microcomputer such as an MPU or MCU) or on hardware using wired logic. Needless to say.

1 Air conditioning system 2 Indoor unit 2A Main unit 2B Control unit 2C Detection unit 3 Adapter 5 Server device 14A Acquisition unit 14E Predictive control unit 33A Model learning unit

Claims (8)

an indoor unit having a wind direction plate that changes the direction of air blown into the air-conditioned space;
a detection unit that periodically detects temperature distribution in a plurality of areas into which the air-conditioned space is divided;
Using a learning model trained with different parameters during cooling operation and heating operation, and temperature distributions of at least two of the air-conditioned spaces, the air-conditioned space is detected a predetermined time after the last temperature distribution is detected. a prediction unit that predicts temperature unevenness within the
a control unit that controls the wind direction plate to eliminate the temperature unevenness when the prediction result of the prediction unit predicts that the temperature unevenness occurs in the air-conditioned space after the predetermined time. death,
The control unit includes:
At every first predetermined time period that is longer than the predetermined time period, the temperature distribution of the air-conditioned space detected by the detection unit is referred to, and if there is a temperature difference of a predetermined temperature or more in the temperature distribution, the temperature distribution is determined to be within the temperature distribution. determining that temperature unevenness has occurred in the temperature distribution, and controlling the wind direction plate so that the temperature unevenness within the same temperature distribution is eliminated;
If it is determined that there is no temperature unevenness in the temperature distribution, and the prediction result of the prediction unit predicts that the temperature unevenness will occur in the air conditioned space after the predetermined time, An air conditioner characterized in that the wind direction plate is controlled so as to eliminate the temperature unevenness occurring in the air-conditioned space . The control unit includes:
When it is determined that there is no temperature unevenness in the temperature distribution, and the prediction result of the prediction unit predicts that the temperature unevenness does not occur in the air-conditioned space after the predetermined time, the air-conditioned space The air conditioner according to claim 1, wherein the wind direction plate is controlled so that the airflow is directed toward the center of the air conditioner. The control unit includes:
The air conditioner according to claim 1 , wherein the wind direction plate is controlled so as not to change the direction of the airflow into the air-conditioned space during the first predetermined time. The control unit includes:
Among the temperatures of each area in the air-conditioned space, the temperature used to determine the presence or absence of temperature unevenness is different between the determination of the presence or absence of temperature unevenness during the cooling operation and the determination of the presence or absence of temperature unevenness during the heating operation. The air conditioner according to claim 1 . When the temperature difference between the maximum value and the minimum value in the temperature distribution of the air-conditioned space is equal to or higher than a first predetermined temperature during heating operation, the temperature distribution in which the temperature difference is equal to or higher than the first predetermined temperature is predicted. 2. The air conditioner according to claim 1, wherein the air conditioner is not used in the air conditioner. When the temperature difference between the maximum value and the minimum value in the temperature distribution of the air-conditioned space is equal to or higher than a first predetermined temperature during heating operation, the temperature distribution in which the temperature difference is equal to or higher than the first predetermined temperature is learned. The air conditioner according to claim 1, wherein the air conditioner is not used for generating or updating a model. Parameters that differ between the cooling operation and the heating operation include:
The air conditioner according to claim 1, characterized in that it is a difference between an outdoor temperature and an indoor temperature, which is included in the parameters during the cooling operation. Parameters that differ between the cooling operation and the heating operation include:
The air conditioner according to claim 1 or 7 , wherein the temperature average value is an average value of all temperatures in the temperature distribution in the air-conditioned space, which is included in the parameters during the heating operation.

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