WO2020224087A1 - 空调控制的方法、装置及计算机存储介质 - Google Patents

空调控制的方法、装置及计算机存储介质 Download PDF

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Publication number
WO2020224087A1
WO2020224087A1 PCT/CN2019/101383 CN2019101383W WO2020224087A1 WO 2020224087 A1 WO2020224087 A1 WO 2020224087A1 CN 2019101383 W CN2019101383 W CN 2019101383W WO 2020224087 A1 WO2020224087 A1 WO 2020224087A1
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Prior art keywords
heat
cooling load
air conditioner
human body
enclosure structure
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PCT/CN2019/101383
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English (en)
French (fr)
Inventor
杜超
贺世权
李永德
孙冬松
池玉玲
Original Assignee
青岛海尔空调器有限总公司
海尔智家股份有限公司
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Publication of WO2020224087A1 publication Critical patent/WO2020224087A1/zh

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/56—Remote control
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/70—Control systems characterised by their outputs; Constructional details thereof
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F24F2110/12—Temperature of the outside air
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2140/00—Control inputs relating to system states
    • F24F2140/50—Load

Definitions

  • the present disclosure relates to the technical field of smart home appliances, and in particular to methods, devices and computer storage media for air conditioning control.
  • air conditioners have become a necessity in people's daily life.
  • the air conditioner can be controlled according to the user's set temperature and the ambient temperature.
  • this control method is still relatively single, and it cannot be automatically and intelligently adjusted according to the indoor and outdoor temperature and humidity environment, and cannot be combined with the heat output of indoor appliances and user behavior patterns, which results in the inability to ensure that users are in the most comfortable environment, which seriously affects people User experience.
  • the present disclosure provides an air conditioning control method, device, and computer storage medium.
  • a method for air conditioning control including:
  • the operation of the air conditioner is controlled.
  • an air conditioning control device including:
  • the first heat determining unit is configured to determine the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat, wherein the first heat is an outdoor temperature wave dissipating through the enclosure structure where the air conditioner is located of;
  • a second heat determining unit configured to determine a second cooling load of the air conditioner corresponding to a second heat, wherein the second heat is emitted by equipment and a human body in the enclosure structure;
  • the first control unit is configured to control the operation of the air conditioner according to the first cooling load and the second cooling load.
  • an air conditioner including: the above-mentioned air conditioning control device.
  • an electronic device including:
  • At least one processor At least one processor
  • a memory communicatively connected with the at least one processor; wherein,
  • the memory stores instructions that can be executed by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor executes the above-mentioned air conditioning control method.
  • the embodiment of the present disclosure provides a computer-readable storage medium.
  • the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are configured to execute the aforementioned air conditioning control method.
  • the embodiment of the present disclosure provides a computer program product.
  • the computer program product includes a computer program stored on a computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the aforementioned air conditioning control method
  • the cooling load corresponding to the room where the air conditioner is located, the enclosure structure, equipment, and the human body can be determined, and the operation of the air conditioner can be controlled according to the determined cooling load, so that the indoor and outdoor temperature environment can be combined with
  • the indoor equipment emits heat and controls the air conditioner, which further improves the intelligence of the air conditioner control and also improves the user experience.
  • FIG. 1 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a table of the amount of heat dissipation and moisture dissipation of the human body provided by an embodiment of the present disclosure
  • FIG. 3 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure.
  • FIG. 4 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure.
  • Figure 5 is a schematic structural diagram of an air conditioning control device provided by an embodiment of the present disclosure.
  • Fig. 6 is a schematic structural diagram of an air conditioning control device provided by an embodiment of the present disclosure.
  • FIG. 7 is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.
  • a smart home appliance system can be formed.
  • TVs, computers, mobile terminals, electric lights, air conditioners, refrigerators, washing machines and other home appliances can be connected via WIFI to form a smart home appliance system for the Internet of Things.
  • WIFI wireless fidelity
  • the operating data of each device in the system can be obtained, and each household appliance can be controlled correspondingly according to the operating data.
  • the cooling load and wet load of the room where the air conditioner is located are the basic basis for determining the air supply volume of the air conditioning system and the capacity of the air conditioning equipment.
  • the heat gain and humidity gain At that moment, the heat gain is negative, it is called heat consumption (loss).
  • the amount of cold that needs to be supplied to the room is called the cooling load; on the contrary, the heat that needs to be supplied to the room to compensate for the loss of heat in the room is called the heat load;
  • the amount of moisture removed or added to the room is called the wet load.
  • the cooling load of the room where the air conditioner is located can be determined first, and then the operation of the air conditioner can be controlled according to the cooling load of the room where the air conditioner is located.
  • the cooling load and wet load of the room where the air conditioner is located can be determined, and then the operation of the air conditioner can be controlled according to the cooling load and wet load.
  • Fig. 1 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure. As shown in Figure 1, the air conditioning control process includes:
  • Step 101 Determine the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat, where the first heat is emitted by the outdoor temperature wave through the enclosure structure where the air conditioner is located.
  • the heat of the room where the air conditioner is located can be the same as the heat transferred through the enclosure structure with solar radiation and the temperature difference between indoor and outdoor air.
  • the air conditioner is located in the room, that is, indoor. Therefore, in the embodiment of the present disclosure, the enclosure structure includes: an outer wall and a roof forming a main structure, and may also include a window structure.
  • the solar radiation and the temperature difference between the indoor and outdoor air can be equivalent to the outdoor temperature wave. In this way, the first heat is emitted by the outdoor temperature wave through the enclosure structure where the air conditioner is located.
  • the heat per unit area on the outer surface of the building is the sum of convective heat transfer and solar radiation heat transfer:
  • the integrated outdoor air temperature is equivalent to the equivalent temperature of the outdoor air temperature increased by one solar radiation from the original value.
  • the equation is as follows:
  • ⁇ the long-wave radiation coefficient of the outer surface of the enclosure structure
  • ⁇ R The difference between the long-wave radiation emitted from the outer surface of the enclosure structure to the outside world and the long-wave radiation from the sky and surrounding objects to the outer surface of the enclosure structure, W/m2.
  • the engineering simplified calculation method of the harmonic response method can be used to calculate the air conditioning cooling load.
  • determining the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat includes: obtaining the environmental parameter values inside and outside the enclosure structure through the Internet of Things, and determining the effect according to the environmental parameter values through formula (1) The cooling load of the main body corresponding to the heat dissipated by the temperature wave on the outer wall and the roof; by formula (2), determine the first window cooling load corresponding to the heat conducted by the window, and, by formula (3), determine The second window cooling load formed by sunlight radiation through the window;
  • ⁇ - ⁇ is the time for the temperature wave to act on the exterior wall and roof surface
  • K is the heat transfer coefficient of the envelope structure
  • F is the calculated area of the envelope structure
  • ⁇ t ⁇ - ⁇ is the time of the envelope structure at the current moment of action.
  • Cooling load calculation temperature difference ⁇ t ⁇ current cooling load calculation temperature difference of the envelope structure at the current moment of action
  • x g is the effective area coefficient of the window
  • x d is the location correction coefficient
  • C s is the shielding coefficient of the window glass
  • C n is The shading coefficient of the shading facilities in the window
  • J j ⁇ is the cooling load formed by the total solar radiant heat per unit window area at the current moment of action.
  • CLQ ⁇ is the main cooling load
  • CLQ c ⁇ is the first window cooling load
  • CLQ j ⁇ is the second window cooling load.
  • the temperature waves are solar radiation waves and outdoor air temperature waves.
  • the acquired environmental parameter values inside and outside the enclosure structure include: at the current moment of action, the temperature inside and outside the main structure composed of the outer wall and the roof, so that ⁇ t ⁇ - ⁇ can be obtained, which can be determined according to formula (1)
  • ⁇ t ⁇ and J j ⁇ can be determined according to the environmental parameter values inside and outside the enclosure structure obtained through the Internet of Things, so that the corresponding formula (2) and formula (3) are used to determine Window cooling load.
  • the other parameters in formulas (1), (2) and (3) are all related to the characteristics of the enclosure structure, that is, when the location of the air conditioner is determined, these parameters are also determined. Therefore, these parameters can be saved in advance.
  • determining the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat may include: only determining the main body cooling load corresponding to the heat dissipated by the temperature wave acting on the outer wall and the roof; or, only determining the solar radiation
  • the cooling load of the second window formed by the window alternatively, the cooling load of the main body corresponding to the heat dissipated by the temperature wave acting on the outer wall and the roof is determined, and the cooling load of the second window formed by the solar radiation through the window is determined.
  • the specifics are not listed one by one.
  • Step 102 Determine the second cooling load of the air conditioner corresponding to the second heat, where the second heat is emitted by the equipment and people in the enclosure structure.
  • the second heat is emitted by the equipment and people in the enclosure, and it needs to be determined with the first The second cooling load of the air conditioner corresponding to the second heat.
  • the cooling load formed by the heat dissipated by the equipment and the human body can be simplified by the following formula in engineering:
  • T the time when the equipment is put into use or when the human body enters the room, h;
  • ⁇ -T from the time the equipment is put into use or the human body enters the room to the calculation time
  • JX ⁇ -T Equipment load intensity coefficient for ⁇ -T time, human body load intensity coefficient.
  • the working parameter data of the Internet of Things devices in the enclosure can be obtained, and the device heat Q emitted by the Internet of Things devices can be determined based on the working parameter data. Then, Determine the human body information in the enclosure structure, and determine the human body heat Q emitted by the human body based on the human body information. Therefore, according to the equipment heat and the human body heat, the first air conditioner corresponding to the equipment heat and the human body heat can be determined by formula (4). Two cooling load.
  • Step 103 Control the operation of the air conditioner according to the first cooling load and the second cooling load.
  • the cooling load of the room where the air conditioner is located is the basic basis for determining the air supply volume of the air conditioning system and the capacity of the air conditioning equipment. Therefore, the most suitable air conditioning operation mode plan can be determined according to the first cooling load and the second cooling load, and the instructions are sent to the air conditioner Implementation, automatic control of the temperature, wind speed, etc. of the air conditioner, so that the user is in an optimal environment.
  • the cooling load corresponding to the room where the air conditioner is located, the enclosure structure, equipment, and the human body can be determined through the Internet of Things where the air conditioner is located, and the operation of the air conditioner can be controlled according to the determined cooling load.
  • the air conditioner is controlled, which further improves the intelligence of the air conditioner control and also improves the user experience.
  • the cooling load and the wet load of the room where the air conditioner is located can also be determined, and then the operation of the air conditioner is controlled according to the cooling load and the wet load. Therefore, in the process of air conditioning control, the wet load formed by the equipment in the enclosure and the human body can be determined, and then the operation of the air conditioner can be controlled according to the first cooling load, the second cooling load, and the wet load.
  • the environmental parameter values in the enclosure structure and the working parameter data of the humidifying device through the Internet of Things, and to determine the amount of equipment moisture emitted by the humidifying device according to the working parameter data, and
  • the human body information in the enclosure structure is determined, and the human body moisture content emitted by the human body is determined according to the human body information, so that the corresponding wet load can be determined according to the equipment moisture content and the human body moisture content.
  • formula (5) can be used to determine the corresponding amount of dispersion.
  • Pq The partial pressure of water vapor in the air, Pa
  • v The air velocity around the water surface, m/s.
  • the environmental parameter values of the location of the air conditioner such as Pq, B', etc.
  • formula (2) can be used to determine the amount of equipment moisture emitted by the Internet of Things wet equipment.
  • the working parameter data of the corresponding humidity dissipating equipment can also be obtained, and the equipment distributed by the humidity dissipating equipment can be determined according to the environmental parameter values and the working parameter data. Wet volume.
  • the corresponding relationship of the amount of heat dissipation and moisture dissipation of the human body can be saved, so that after determining the human body information in the enclosure structure, the corresponding relationship of the amount of heat dissipation and moisture dissipation of the human body can be determined according to the corresponding relationship of the human body heat dissipation. , And the amount of human moisture.
  • Fig. 2 is a schematic diagram of a table of the amount of human body heat dissipation and humidity provided by an embodiment of the present disclosure.
  • the human body heat and human body humidity at the current temperature can be determined according to the heat dissipation and moisture dissipation table shown in Figure 2. For example: at 26°C, the human body moisture is 184g/h.
  • the corresponding human body heat in step 102 can also be determined.
  • the cooling load and wet load of the room where the air conditioner is located are the basic basis for determining the air supply volume of the air conditioning system and the capacity of the air conditioning equipment. Therefore, after determining the cooling load and wet load of the room where the air conditioner is located, the operation of the air conditioner can be controlled according to the cooling load and wet load, and the most suitable air conditioning operation mode plan can be determined according to the cooling load and wet load, and the command Send to the air conditioner to execute, automatically control the temperature, wind speed, etc. of the air conditioner, so that the user is in an optimal environment. It further improves the intelligence of the air conditioner and the user experience.
  • TVs, computers, mobile terminals, lights, air conditioners, refrigerators, washing machines and other home appliances can be connected through WIFI to form an IoT smart home appliance system
  • users can also be analyzed based on the operation of each device in the IoT The state of life you are in. For example, the TV, computer, and mobile phone are all turned off at night, and it can be determined that the user is most likely asleep.
  • the air conditioner can be controlled to turn on the silent mode and turn off at regular intervals.
  • the air-conditioning control process may further include: in the case of determining that the living state in the envelope structure is a sleep state according to the working parameter data of the Internet of Things devices in the envelope structure, controlling the air conditioner to be silent and shut down regularly Mode operation.
  • the aforementioned air conditioning control process can be completed by a system processing module in the Internet of Things.
  • the system processing module can be a separate terminal or any device in the Internet of Things, such as air conditioners, televisions, and so on.
  • the air conditioner is located in the Internet of Things system, that is, the air conditioner can communicate with devices in the Internet of Things via WIFI, such as televisions, computers, mobile terminals, electric lights, air conditioners, refrigerators, washing machines and other home appliances. Connect via WIFI to form an IoT smart home appliance system.
  • WIFI wireless fidelity
  • Fig. 3 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure. As shown in Figure 3, the air conditioning control process includes:
  • Step 301 Obtain environmental parameter values inside and outside the enclosure structure through the established Internet of Things.
  • the temperature inside and outside the main structure of the external wall and roof can be obtained at the current moment of action
  • Step 302 Determine the main body cooling load corresponding to the heat dissipated by the temperature wave acting on the outer wall and the roof through formula (1) according to the environmental parameter value.
  • Step 303 Determine the first window cooling load corresponding to the heat conducted by the window through formula (2).
  • ⁇ t ⁇ is obtained according to the temperature of the inside and outside of the environmental parameter values inside and outside of the envelope structure.
  • Step 304 Using formula (3), determine the cooling load of the second window formed by the sunlight radiation passing through the window.
  • J j ⁇ is determined.
  • formula (3) can be used to determine the second window cooling load formed by sunlight radiation through the window.
  • Step 305 Obtain working parameter data of the IoT device in the enclosure structure, and determine the device heat emitted by the IoT device according to the working parameter data.
  • Refrigerators, electric lights, etc. can determine the corresponding equipment heat according to the corresponding working parameter data. For example, according to the current power parameters of the refrigerator, determine the corresponding device heat. According to the current power of the lamp and the lighting area, etc., the corresponding device heat can be determined. The process of determining the equipment heat dissipated by the equipment according to the working parameter data of the equipment in the related art can be applied to this.
  • Step 306 Obtain human body information in the enclosure structure, and determine the corresponding human body heat emitted by the human body according to the stored correspondence relationship of the human body's heat dissipation and moisture dissipation.
  • the human body information such as the number, gender, and posture of the human body can be determined through the human body sensor and camera.
  • the corresponding human body can be determined according to the scene information at the location and the human body information through the saved correspondence between the amount of heat dissipation and moisture of the human body Human body heat emitted.
  • Step 307 Determine the second cooling load of the air conditioner corresponding to the device heat and the human body heat through formula (4) according to the device heat and the human body heat.
  • Step 308 Control the operation of the air conditioner according to the first cooling load and the second cooling load.
  • the most suitable air-conditioning operation mode plan can be determined, and the instructions can be sent to the air-conditioning to execute, and the temperature, wind speed, etc. of the air-conditioning can be automatically controlled, so that the user is in the most suitable Environment.
  • the cooling load corresponding to the room where the air conditioner is located, the enclosure structure, equipment, and the human body can be determined through the Internet of Things where the air conditioner is located, and the operation of the air conditioner can be controlled according to the determined cooling load.
  • the air conditioner is controlled, which further improves the intelligence of the air conditioner control and also improves the user experience.
  • an air conditioner is connected with a TV, a computer, a mobile phone terminal, an electric light, a refrigerator, a washing machine, and other household appliances through WIFI to form an IoT smart household appliance system.
  • Fig. 4 is a schematic flowchart of an air conditioning control method provided by an embodiment of the present disclosure. As shown in Figure 4, the air conditioning control process includes:
  • Step 401 Obtain environmental parameter values inside and outside the enclosure structure, working parameter data of the Internet of Things devices in the enclosure structure, and human body information in the enclosure structure through the established Internet of Things.
  • the Internet of Things can communicate with temperature detection equipment or cloud servers to obtain environmental parameter values inside and outside the enclosure, such as outdoor temperature, indoor temperature, outdoor humidity, indoor temperature, and so on.
  • environmental parameter values such as outdoor temperature, indoor temperature, outdoor humidity, indoor temperature, and so on.
  • the Internet of Things communicates with the Internet of Things devices in each enclosure to obtain corresponding working parameter data.
  • human body detection equipment, cameras, etc. determine the human body information in the enclosure structure, for example: determine the number, gender, posture and other human body information of the human body.
  • Step 402 Determine the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat according to the acquired environmental parameter value. Among them, the first heat is emitted by the outdoor temperature wave through the enclosure structure where the air conditioner is located.
  • the enclosure structure may only include the outer wall and the roof.
  • the envelope structure includes external walls and roofs, as well as windows.
  • Step 403 Determine the device heat dissipated by the IoT device according to the obtained working parameter data.
  • Step 404 Determine the human body heat emitted by the human body corresponding to the obtained human body information according to the stored correspondence relationship of the human body heat dissipation and moisture dissipation.
  • Step 405 Determine the second cooling load of the air conditioner corresponding to the device heat and the human body heat according to the device heat and the human body heat.
  • Step 406 According to the acquired environmental parameter values and working parameter data, determine the amount of equipment moisture emitted by the moisture dispersion equipment.
  • the environmental parameter values in the enclosure structure can be obtained, and then formula (5) is used to determine the amount of equipment humidity dissipated by the IoT humidity dissipating equipment.
  • formula (5) is used to determine the amount of equipment humidity dissipated by the IoT humidity dissipating equipment.
  • Step 407 Determine the amount of human body moisture emitted by the human body corresponding to the obtained human body information according to the stored correspondence relationship of the amount of human body heat dissipation and moisture dissipation.
  • the human body information such as the number, gender, and posture of the human body can be determined through the human body sensor and camera.
  • the corresponding relationship can be determined based on the scene information at the location and the human body information through the stored correspondence between the amount of heat dissipation and moisture loss of the human body The amount of human moisture emitted by the human body.
  • Step 408 Determine the wet load corresponding to the wet amount of the equipment and the proper amount of the human body.
  • Step 409 Control the operation of the air conditioner according to the first cooling load, the second cooling load, and the wet load.
  • the most suitable air conditioner operation mode scheme can be determined according to the cooling load and wet load, and the instructions are sent to the air conditioner for execution, and the temperature and wind speed of the air conditioner are automatically controlled, so that the user is in the most suitable Environment. It further improves the intelligence of the air conditioner and the user experience.
  • an air conditioning control device can be constructed.
  • FIG. 5 is a schematic structural diagram of an air conditioning control device provided by an embodiment of the present disclosure. As shown in FIG. 5, the air conditioning control device includes: a first heat determination unit 510, a second heat determination unit 520, and a first control unit 530.
  • the first heat determination unit 510 is configured to determine the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat, where the first heat is emitted by the outdoor temperature wave through the enclosure structure where the air conditioner is located.
  • the second heat determination unit 520 is configured to determine the second cooling load of the air conditioner corresponding to the second heat, where the second heat is emitted by the equipment and the human body in the enclosure structure.
  • the first control unit 530 is configured to control the operation of the air conditioner according to the first cooling load and the second cooling load.
  • the device further includes: a moisture determination unit configured to determine the wet load formed by the equipment and the human body in the enclosure structure;
  • the second control unit is configured to control the operation of the air conditioner according to the first cooling load, the second cooling load, and the wet load.
  • the first heat determination unit 510 is specifically configured to obtain the environmental parameter values inside and outside the enclosure structure through the Internet of Things, and according to the environmental parameter values, through formula (1), determine the effect on the outer wall and roof The cooling load of the main body corresponding to the heat dissipated by the temperature wave; through formula (2), determine the first window cooling load corresponding to the heat conducted by the window, and, through formula (3), determine the sunlight radiation passing through the window The formed second window cooling load;
  • ⁇ - ⁇ is the time for the temperature wave to act on the exterior wall and roof surface
  • K is the heat transfer coefficient of the envelope structure
  • F is the calculated area of the envelope structure
  • ⁇ t ⁇ - ⁇ is the time of the envelope structure at the current moment of action.
  • Cooling load calculation temperature difference ⁇ t ⁇ current cooling load calculation temperature difference of the envelope structure at the current moment of action
  • x g is the effective area coefficient of the window
  • x d is the location correction coefficient
  • C s is the shielding coefficient of the window glass
  • C n is The shading coefficient of the shading facilities in the window
  • J j ⁇ is the cooling load formed by the total solar radiant heat per unit window area at the current moment of action.
  • CLQ ⁇ is the main cooling load
  • CLQ c ⁇ is the first window cooling load
  • CLQ j ⁇ is the second window cooling load.
  • the second heat determination unit 520 is specifically configured to obtain working parameter data of the IoT device in the enclosure structure, and determine the device heat dissipated by the IoT device according to the working parameter data; determine the enclosure structure According to the human body information, determine the human body heat radiated by the human body; according to the equipment heat and the human body heat, through formula (4), determine the second cooling load of the air conditioner corresponding to the equipment heat and the human body heat;
  • Q is the heat gain of the Internet of Things equipment or the human body
  • T is the time when the Internet of Things equipment is put into use or the human body enters the enclosure structure
  • ⁇ -T is the time when the device is put into use or the human body enters the furnace mechanism to the action time
  • JX ⁇ -T is the load intensity coefficient of the Internet of Things equipment at ⁇ -T time and the human body load intensity coefficient.
  • the moisture content determination unit is specifically used to obtain the environmental parameter values in the enclosure structure and the working parameter data of the moisture dissipating equipment, and determine the equipment emitted by the moisture dissipating equipment according to the working parameter data and the environmental parameter values.
  • Humidity Determine the human body information in the enclosure structure, and determine the human body moisture emitted by the human body based on the human body information.
  • the device further includes: a silent mode control unit for controlling the air conditioner when it is determined that the living state in the enclosure is a sleep state according to the working parameter data of the Internet of Things equipment in the enclosure Run in silent timer shutdown mode.
  • Fig. 6 is a schematic structural diagram of an air conditioning control device provided by an embodiment of the present disclosure.
  • the air conditioning control device may include: a first heat determination unit 510, a second heat determination unit 520, and a first control unit 530.
  • the device further includes a humidity determination unit 540, a second control unit 550, and a mute Mode control unit 560.
  • Air conditioners and TVs, computers, mobile terminals, lights, refrigerators, washing machines and other household appliances are connected via WIFI to form an IoT smart home appliance system.
  • the environmental parameter values inside and outside the enclosure can be obtained , It can also obtain the working parameter data of the Internet of Things devices in the enclosure structure, and also obtain the human body information in the enclosure structure.
  • the enclosure can be determined
  • the silent mode control unit 560 can control the air conditioner to operate in a silent scheduled shutdown mode.
  • the most suitable air conditioning operation mode scheme can be determined according to the cooling load and the wet load, and the instructions are sent to the air conditioning for execution.
  • the first heat determination unit 510 may determine the first cooling load of the air conditioner in the Internet of Things corresponding to the first heat according to the acquired environmental parameter value.
  • the first heat is emitted by the outdoor temperature wave through the enclosure structure where the air conditioner is located.
  • the second heat determination unit 520 can determine the device heat emitted by the IoT device according to the obtained working parameter data of the IoT device; according to the obtained human body information and the stored corresponding relationship between the amount of heat and moisture of the human body, determine the corresponding human body emission According to the heat of the device and the heat of the human body, determine the second cooling load of the air conditioner corresponding to the heat of the device and the heat of the body.
  • the first control unit 530 may control the operation of the air conditioner according to the first cooling load and the second cooling load.
  • the humidity determination unit 540 determines the cooling load, that is, the humidity determination unit 540 can determine the amount of equipment moisture emitted by the moisture dissipating device according to the environmental parameter value and the working parameter data, and can according to the stored human body heat dissipation and moisture dissipation Correspondence, determine the amount of human body moisture emitted by the human body corresponding to the human body information in the enclosure structure, and determine the wet load corresponding to the device moisture amount and the appropriate amount of human body.
  • the second control unit 550 can control the operation of the air conditioner according to the first cooling load, the second cooling load, and the wet load.
  • the most suitable air conditioner operation mode scheme can be determined according to the cooling load, or cooling load and wet load, and the instructions are sent to the air conditioner for execution, and the temperature and wind speed of the air conditioner are automatically controlled, so that the user can In an optimal environment. It further improves the intelligence of the air conditioner and the user experience.
  • the air conditioning control device can be in the system processing module of the Internet of Things, which can be a separate terminal or any device in the Internet of Things, such as: air conditioners, TVs, etc. Therefore, an embodiment of the present disclosure also provides an air conditioner, including the above-mentioned air conditioner control device.
  • the embodiment of the present disclosure also provides a computer-readable storage medium that stores computer-executable instructions, and the computer-executable instructions are configured to execute the aforementioned air conditioning control method.
  • the embodiments of the present disclosure also provide a computer program product, the computer program product includes a computer program stored on a computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, The computer executes the above air conditioning control method.
  • the aforementioned computer-readable storage medium may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
  • the embodiment of the present disclosure also provides an electronic device, the structure of which is shown in FIG. 7, including:
  • At least one processor (processor) 100 one processor 100 is taken as an example in FIG. 7; and a memory (memory) 101 may also include a communication interface (Communication Interface) 102 and a bus 103. Among them, the processor 100, the communication interface 102, and the memory 101 can communicate with each other through the bus 103.
  • the communication interface 102 may be configured for information transmission.
  • the processor 100 can call the logic instructions in the memory 101 to execute the air conditioning control method of the foregoing embodiment.
  • the above-mentioned logical instructions in the memory 101 can be implemented in the form of a software function unit and when sold or used as an independent product, they can be stored in a computer readable storage medium.
  • the memory 101 can be configured to store software programs and computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure.
  • the processor 100 executes functional applications and data processing by running software programs, instructions, and modules stored in the memory 101, that is, realizes the air conditioning control method in the foregoing method embodiment.
  • the memory 101 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the terminal device, etc.
  • the memory 101 may include a high-speed random access memory, and may also include a non-volatile memory.
  • the technical solutions of the embodiments of the present disclosure can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which can be a personal computer, a server, or a network). Equipment, etc.) execute all or part of the steps of the method described in the embodiments of the present disclosure.
  • the aforementioned storage medium may be a non-transitory storage medium, including: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.

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Abstract

一种空调控制的方法、装置及计算机存储介质。所述方法包括：确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，所述第一热量是室外温度波通过所述空调所在的围护结构散入的；确定与第二热量对应的所述空调的第二冷负荷，其中，所述第二热量是所述围护结构内的设备和人体散出的；根据所述第一冷负荷和所述第二冷负荷，控制所述空调的运行。这样，根据空调的冷负荷，确定出最适宜的空调运行模式方案并执行，提高了空调的智能性。

Description

空调控制的方法、装置及计算机存储介质
本申请基于申请号为201910371789.4、申请日为2019年05月06日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开涉及智能家电技术领域，特别涉及空调控制的方法、装置及计算机存储介质。
背景技术
随着生活水平的提高，空调已经是人们日常生活的必备品。空调可根据用户设定温度，以及所在环境温度，对空调进行控制。但是，这种控制方式还比较单一，还不能根据室内外温湿度环境，以及无法结合室内家电放热量和用户行为模式进行自动智能调节，导致不能保证用户处于最舒适的环境中，严重影响了人们的用户体验。
发明内容
为解决相关技术中的问题，本公开提供了空调控制的方法、装置及计算机存储介质。
根据本公开实施例的第一方面，提供一种空调控制的方法，所述方法包括：
确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，所述第一热量是室外温度波通过所述空调所在的围护结构散入的；
确定与第二热量对应的所述空调的第二冷负荷，其中，所述第二热量是所述围护结构内的设备和人体散出的；
根据所述第一冷负荷和所述第二冷负荷，控制所述空调的运行。
根据本公开实施例的第二方面，提供一种空调控制的装置，所述装置包括：
第一热量确定单元，被配置为确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，所述第一热量是室外温度波通过所述空调所在的围护结构散入的；
第二热量确定单元，被配置为确定与第二热量对应的所述空调的第二冷负荷，其中，所述第二热量是所述围护结构内的设备和人体散出的；
第一控制单元，被配置为根据所述第一冷负荷和所述第二冷负荷，控制所述空调的运行。
根据本公开实施例的第三方面，提供一种空调，所述空调包括：上述空调控制的装置。
根据本公开实施例的第四方面，提供一种电子设备，所述电子设备包括：
至少一个处理器；以及
与所述至少一个处理器通信连接的存储器；其中，
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处 理器执行时，使所述至少一个处理器执行上述的空调控制方法。
本公开实施例提供了一种计算机可读存储介质。所述计算机可读存储介质存储有计算机可执行指令，所述计算机可执行指令设置为执行上述的空调控制方法。
本公开实施例提供了一种计算机程序产品。所述计算机程序产品包括存储在计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述的空调控制方法
本公开的实施例提供的技术方案可以包括以下有益效果：
可通过空调所在的物联网，确定空调所在房间与围护结构、设备以及人体分别对应的冷负荷，并根据确定出的冷负荷，控制空调的运行，从而，可根据室内外温度环境，并结合室内设备放热量，对空调进行控制，进一步提高了空调控制的智能性，也提高了用户体验。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性的，并不能限制本公开。
附图说明
此处的附图被并入说明书中并构成本公开说明书的一部分，示出了符合本公开的实施例，并与说明书一起用于解释本公开的原理。
图1是本公开实施例提供的空调控制方法的流程示意图；
图2是本公开实施例提供的人体散热散湿量的表格示意图；
图3是本公开实施例提供的空调控制方法的流程示意图；
图4是本公开实施例提供的空调控制方法的流程示意图；
图5是本公开实施例提供的空调控制装置的结构示意图；
图6是本公开实施例提供的空调控制装置的结构示意图；以及
图7是本公开实施例提供的电子设备的结构示意图。
具体实施方式
这里将详细地对示例性实施例进行说明，其示例表示在附图中。下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本公开相一致的所有实施方式。相反，它们仅是与如所附权利要求书中所详述的、本公开的一些方面相一致的装置和方法的例子。
随着物联网技术的发展，可形成智能家电系统，在该系统中，电视、电脑、手机终端、电灯、空调、冰箱、洗衣机等等家电设备都可通过WIFI连接，形成了物联网智能家电系统，从而，通过物联网，可获取系统中每个设备的运行数据，并可根据运行数据对各个家电设备进行对应的控制。
空调所在房间冷负荷，湿负荷是确定空调系统送风量和空调设备容量的基本依据。在室内外热，湿扰量作用下，某一时刻进入一个恒温恒湿房间内的总热量和湿量称为该时刻 的得热量和得湿量。而当得热量为负值时称为耗(失)热量。在某一时刻为保持房间恒温恒湿，需向房间供应的冷量称为冷负荷；相反，为补偿房间失热而需要向房间供应的热量称为热负荷；为维持室内相对湿度所需由房间除去或增加的湿量称为湿负荷。因此，本公开实施例中，可首先确定空调所在房间的冷负荷，然后根据空调所在房间冷负荷，控制空调的运行。或者，可确定空调所在房间的冷负荷以及湿负荷，然后，根据冷负荷以及湿负荷，控制空调的运行。
图1是本公开实施例提供的空调控制方法的流程示意图。如图1所示，空调控制的过程包括：
步骤101：确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，第一热量是室外温度波通过空调所在的围护结构散入的。
一般，空调所在房间的热量可与太阳辐射和室内外空气温差经围护结构传入的热量。而空调所在位置位于房间内，即室内，因此，本公开实施例中，围护结构包括：外墙体和屋顶组成主体结构，还可包括：窗体结构。而太阳辐射和室内外空气温差可等效于室外温度波，这样，第一热量是室外温度波通过空调所在的围护结构散入的。
由于围护结构外表面同时受到太阳辐射和室外空气温度的热作用，建筑物外表面单位面积上得到的热量为对流换热与太阳辐射换热之和：
q＝α w(t z-τ w)
室外空气综合温度是相当于室外气温由原来的值增加了一个太阳辐射的等效温度，方程如下：
Figure PCTCN2019101383-appb-000001
式中，ε——围护结构外表面的长波辐射系数；
△R——围护结构外表面向外界发射的长波辐射和由天空及周围物体向围护结构外表面的长波辐射之差，W/m2。
本公开实施例中，计算空调冷负荷可以用谐波反应法的工程简化计算方法。这样，确定与第一热量对应的处于物联网中的空调的第一冷负荷包括：通过物联网，获取围护结构内外的环境参数值，并根据环境参数值，通过公式(1)，确定作用在外墙体和屋顶上的温度波散入的热量对应的主体冷负荷；通过公式(2)，确定与窗体传导的热量对应的第一窗体冷负荷，以及，通过公式(3)，确定阳光辐射通过窗体形成的第二窗体冷负荷；
CLQ τ＝KFΔt τ-ε……………………………………………..…(1)
CLQ c·τ＝KFΔt τ……………………………………………..…(2)
CLQ j·τ＝x gx dC nC sFJ j·τ……………………………………………..…(3)
其中，τ-ε为温度波作用于外墙体和屋顶表面的时间，K为围护结构传热系数，F为 围护结构的计算面积，Δt τ-ε为当前作用时刻下围护结构的冷负荷计算温差，Δt τ当前作用时刻下围护结构的冷负荷计算温差，x g为窗体的有效面积系数，x d为地点修正系数，C s为窗体玻璃的遮挡系数，C n为窗体内遮阳设施的遮阳系数，J j·τ为当前作用时刻时，透过单位窗口面积的太阳总辐射热形成的冷负荷。当然，CLQ τ为主体冷负荷，CLQ c·τ为第一窗体冷负荷，而CLQ j·τ为第二窗体冷负荷。
可见，对于外墙体和屋顶组成主体结构，温度波为太阳辐射波和室外空气温度波。通过物联网，获取的围护结构内外的环境参数值包括：当前作用时刻下，外墙体和屋顶组成主体结构内外的温度，从而可得到Δt τ-ε，从而可根据公式(1)，确定作用在外墙体和屋顶上温度波散入的热量对应的主体冷负荷。同样，可根据通过物联网，获取的围护结构内外的环境参数值，确定Δt τ，以及，J j·τ，从而，分别通过公式(2)、公式(3)，确定与窗体对应的窗体冷负荷。
公式(1)、(2)以及(3)中的其他参数都是与围护结构的特征是相关的，即空调所在位置确定了，这些参数也就确定了，因此，可预先保存这些参数。
当然，确定与第一热量对应的处于物联网中的空调的第一冷负荷可包括：只确定作用在外墙体和屋顶上温度波散入的热量对应的主体冷负荷；或者，只确定阳光辐射通过窗体形成的第二窗体冷负荷；或者，确定作用在外墙体和屋顶上温度波散入的热量对应的主体冷负荷，以及确定阳光辐射通过窗体形成的第二窗体冷负荷。具体就不一一列举了。
步骤102：确定与第二热量对应的空调的第二冷负荷，其中，第二热量是围护结构内的设备和人散出的。
空调所在房间内有其他的物联网设备，例如：电视、电脑、灯等等。这些设备运行时也会散入热量，同时，房间中的人体也会散入热量，因此，本公开实施例中，第二热量是围护结构内的设备和人散出的，需确定与第二热量对应的空调的第二冷负荷。
设备和人体散热得热形成的冷负荷，在工程上可用下式简化计算：
CLQ τ＝QJX τ-T……………………………………………..…(4)
式中，Q——设备和人体的得热，W；
T——设备投入使用时刻或人体进入房间时刻，h；
τ-T——从设备投入使用时刻或人体进入房间时刻到计算时间；
JX τ-T——τ-T时间的设备负荷强度系数，人体负荷强度系数。
由于电视、电脑、灯等等这些设备位于物联网中，因此，可获取围护结构内的物联网设备的工作参数数据，并根据工作参数数据，确定物联网设备散发的设备热量Q，然后，确定围护结构内的人体信息，并根据人体信息，确定人体散发的人体热量Q，从而，可根 据设备热量、人体热量，通过公式(4)，确定与设备热量和人体热量对应的空调的第二冷负荷。
步骤103：根据第一冷负荷和第二冷负荷，控制空调的运行。
空调所在房间冷负荷是确定空调系统送风量和空调设备容量的基本依据，因此，可根据第一冷负荷和第二冷负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行，自动控制空调的温度、风速等等，从而，使用户处在一个最适宜的环境中。
可见，本公开实施例中，可通过空调所在的物联网，确定空调所在房间与围护结构、设备以及人体分别对应的冷负荷，并根据确定出的冷负荷，控制空调的运行，从而，可根据室内外温度环境，并结合室内设备放热量，对空调进行控制，进一步提高了空调控制的智能性，也提高了用户体验。
当然，本公开实施例中，还可确定空调所在房间的冷负荷以及湿负荷，然后，根据冷负荷以及湿负荷，控制空调的运行。因此，空调控制的过程中，还可确定围护结构内的设备和人体散湿形成的湿负荷，然后，根据第一冷负荷，第二冷负荷，以及湿负荷，控制空调的运行。
在一些实施例中，同样可通过物联网，获取围护结构内的环境参数值，以及散湿设备的工作参数数据，并根据工作参数数据，确定散湿设备散发的设备湿量，并且，可确定围护结构内的人体信息，并根据人体信息，确定人体散发的人体湿量，从而，可根据设备湿量以及人体湿量，确定对应的湿负荷。
在一些实施例中，对于一些散湿设备，可公式(5)，确定对应的散适量。
Figure PCTCN2019101383-appb-000002
式中，P q□b——相应于水表面温度下的空气饱和水蒸气分压力，Pa；
Pq——空气中水蒸气分压力，Pa；
F——散湿设备的表面积，m2
β——蒸发系数，β＝(a+0.00363v)10-5；
B——标准大气压力，Pa；
B‘——当地实际大气压力，Pa；
a——周围空气温度为15～30℃时，不同水温下的扩散系数；
v——水面上周围空气流速，m/s。
因此，通过物联网，获取空调所在位置的环境参数值，例如：Pq、B‘等等，即可通过公式(2)，即可确定物联网散湿设备散发的设备湿量。在另一些实施例中，对应物联网中散湿设备，例如冰箱，洗衣机，还可获取对应的散湿设备的工作参数数据，并根据环境参数值以及工作参数数据，确定散湿设备散发的设备湿量。
本公开实施例中，可保存的人体散热散湿量对应关系，从而，确定述围护结构内的人体信息后，即可根据保存的人体散热散湿量对应关系，即可确定对应的人体热量，以及人 体湿量。
图2是本公开实施例提供的人体散热散湿量的表格示意图。当确定的人体信息为成年男子，处于轻度劳动状态，则可根据图2所示的散热散湿量的表格，确定当前温度下的人体热量，以及人体湿量。例如：26℃时，人体湿量为184g/h。当然，根据图2所示的散热散湿量的表格，也可确定步骤102中对应的人体热量。
空调所在房间冷负荷，湿负荷是确定空调系统送风量和空调设备容量的基本依据。因此，确定了空调所在房间的冷负荷以及湿负荷后，可根据冷负荷以及湿负荷，控制空调的运行，即可根据冷负荷以及湿负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行，自动控制空调的温度、风速等等，使用户处在一个最适宜的环境中。进一步提高了空调的智能性，以及用户的体验。
当然，由于电视、电脑、手机终端、电灯、空调、冰箱、洗衣机等等家电设备都可通过WIFI连接，形成物联网智能家电系统，因此，还可根据物联网中各设备运行情况，分析出用户所处的生活状态。比如晚上电视、电脑、手机都呈关机状态，即可确定出用户很大可能是在睡眠，此时可控制空调开启静音模式，并定时关机。则在一些实施例中，空调控制过程还可包括：在根据围护结构内的物联网设备的工作参数数据，确定围护结构内的生活状态为睡眠状态的情况下，控制空调处于静音定时关机模式运行。
上述空调控制过程可由物联网中系统处理模块来完成，该系统处理模块可是一个单独的终端，也可是物联网中的任一设备，例如：空调，电视等。
下面将操作流程集合到具体实施例中，举例说明本发明实施例提供的控制方法。
本公开一实施例中，空调位于物联网系统中，即空调可通过WIFI与物联网中的设备进行通讯，例如：电视、电脑、手机终端、电灯、空调、冰箱、洗衣机等等家电设备都可通过WIFI连接，形成物联网智能家电系统。
图3是本公开实施例提供的空调控制方法的流程示意图。如图3所示，空调控制的过程包括：
步骤301：通过已构建的物联网，获取围护结构内外的环境参数值。
可获取当前作用时刻下，外墙体和屋顶组成主体结构内外的温度，
步骤302：根据环境参数值，通过公式(1)，确定作用在外墙体和屋顶上的温度波散入的热量对应的主体冷负荷。
根据环境参数值中的外墙体和屋顶组成主体结构内外的温度，得到Δt τ-ε，从而，可根据公式(1)，得到对应的主体冷负荷。
步骤303：通过公式(2)，确定与窗体传导的热量对应的第一窗体冷负荷。
同样，根据围护结构内外的环境参数值中的内外的温度，得到Δt τ，这样，通过公式(2)，确定与窗体传导的热量对应的第一窗体冷负荷。
步骤304：通过公式(3)，确定阳光辐射通过窗体形成的第二窗体冷负荷。
根据围护结构内外的环境参数值，确定J j·τ，这样，即可通过公式(3)，确定阳光辐 射通过窗体形成的第二窗体冷负荷。
步骤305：获取围护结构内的物联网设备的工作参数数据，并根据工作参数数据，确定物联网设备散发的设备热量。
冰箱、电灯等等都可根据对应的工作参数数据，确定对应的设备热量。例如根据冰箱的当前功率参数，确定对应的设备热量。根据电灯的当前功率以及照明面积等等，可确定对应的设备热量。相关技术中根据设备的工作参数数据确定设备散发的设备热量的过程都可以应用于此。
步骤306：获取围护结构内的人体信息，并根据保存的人体散热散湿量对应关系，确定对应的人体散发的人体热量。
例如：通过人体传感器、摄像头，确定人体的个数、性别、姿态等人体信息，这样，可根据所在位置的场景信息，以及人体信息，通过保存的人体散热散湿量对应关系，确定对应的人体散发的人体热量。
步骤307：根据设备热量、人体热量，通过公式(4)，确定与设备热量和人体热量对应的空调的第二冷负荷。
步骤308：根据第一冷负荷和第二冷负荷，控制空调的运行。
可根据第一冷负荷和第二冷负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行，自动控制空调的温度、风速等等，从而，使用户处在一个最适宜的环境中。
可见，本公开实施例中，可通过空调所在的物联网，确定空调所在房间与围护结构、设备以及人体分别对应的冷负荷，并根据确定出的冷负荷，控制空调的运行，从而，可根据室内外温度环境，并结合室内设备放热量，对空调进行控制，进一步提高了空调控制的智能性，也提高了用户体验。
本公开另一实施例中，空调与电视、电脑、手机终端、电灯、冰箱、洗衣机等等家电设备，通过WIFI连接，形成物联网智能家电系统。
图4是本公开实施例提供的空调控制方法的流程示意图。如图4所示，空调控制的过程包括：
步骤401：通过已构建的物联网，获取围护结构内外的环境参数值、围护结构内的物联网设备的工作参数数据、以及围护结构内的人体信息。
这样，可通过物联网，与温度检测设备或者云端服务器进行通讯，获取围护结构内外的环境参数值，例如：室外温度值，室内温度值，室外湿度值，室内温度值等等。通过物联网，与每个围护结构内的物联网设备进行通讯，获取对应的工作参数数据。通过人体检测设备、摄像头等，确定围护结构内的人体信息，例如：确定人体的个数、性别、姿态等人体信息。
步骤402：根据获取的环境参数值，确定第一热量对应的处于物联网中的空调的第一冷负荷。其中，第一热量是室外温度波通过空调所在的围护结构散入的。
本实施例中，围护结构可只包括外墙体和屋顶。或者，围护结构包括外墙体和屋顶， 以及窗体。
步骤403：根据获取的工作参数数据，确定物联网设备散发的设备热量。
步骤404：根据保存的人体散热散湿量对应关系，确定与获取的人体信息对应的人体散发的人体热量。
步骤405：根据设备热量、人体热量，确定与设备热量和人体热量对应的空调的第二冷负荷。
步骤406：根据获取的环境参数值和工作参数数据，确定散湿设备散发的设备湿量。
本实施例中，对于一些散湿设备，例如水槽，可获取围护结构内的环境参数值，然后通过公式(5)，确定物联网散湿设备散发的设备湿量。对于冰箱、洗衣机等这些物联网中的散湿设备，不仅需获取围护结构内的环境参数值，还需通过物联网，获取对应的散湿设备的工作参数数据，并根据环境参数值以及工作参数数据，确定散湿设备散发的设备湿量。
步骤407：根据保存的人体散热散湿量对应关系，确定获取的人体信息对应的人体散发的人体湿量。
当然，可以通过人体传感器、摄像头，确定人体的个数、性别、姿态等人体信息，这样，可根据所在位置的场景信息，以及人体信息，通过保存的人体散热散湿量对应关系，确定对应的人体散发的人体湿量。
步骤408：确定与设备湿量以及人体适量对应的湿负荷。
步骤409：根据第一冷负荷，第二冷负荷，以及湿负荷，控制空调的运行。
可见，本实施例中，可根据冷负荷以及湿负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行，自动控制空调的温度、风速等等，使用户处在一个最适宜的环境中。进一步提高了空调的智能性，以及用户的体验。
根据上述空调控制的过程，可构建一种空调控制的装置。
图5是本公开实施例提供的空调控制装置的结构示意图。如图5所示，空调控制装置包括：第一热量确定单元510、第二热量确定单元520以及第一控制单元530。
第一热量确定单元510，被配置为确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，第一热量是室外温度波通过空调所在的围护结构散入的。
第二热量确定单元520，被配置为确定与第二热量对应的空调的第二冷负荷，其中，第二热量是围护结构内的设备和人体散出的。
第一控制单元530，被配置为根据第一冷负荷和第二冷负荷，控制空调的运行。
在一些实施例中，该装置还包括：湿量确定单元，被配置为确定围护结构内的设备和人体散湿形成的湿负荷；
第二控制单元，被配置为根据第一冷负荷，第二冷负荷，以及湿负荷，控制空调的运行。
在一些实施例中，第一热量确定单元510，具体被配置为通过物联网，获取围护结构 内外的环境参数值，并根据环境参数值，通过公式(1)，确定作用在外墙体和屋顶上的温度波散入的热量对应的主体冷负荷；通过公式(2)，确定与窗体传导的热量对应的第一窗体冷负荷，以及，通过公式(3)，确定阳光辐射通过窗体形成的第二窗体冷负荷；
CLQ τ＝KFΔt τ-ε……………………………………………..…(1)
CLQ c·τ＝KFΔt τ……………………………………………..…(2)
CLQ j·τ＝x gx dC nC sFJ j·τ……………………………………………..…(3)
其中，τ-ε为温度波作用于外墙体和屋顶表面的时间，K为围护结构传热系数，F为围护结构的计算面积，Δt τ-ε为当前作用时刻下围护结构的冷负荷计算温差，Δt τ当前作用时刻下围护结构的冷负荷计算温差，x g为窗体的有效面积系数，x d为地点修正系数，C s为窗体玻璃的遮挡系数，C n为窗体内遮阳设施的遮阳系数，J j·τ为当前作用时刻时，透过单位窗口面积的太阳总辐射热形成的冷负荷。当然，CLQ τ为主体冷负荷，CLQ c·τ为第一窗体冷负荷，而CLQ j·τ为第二窗体冷负荷。
在一些实施例中，第二热量确定单元520，具体被配置为获取围护结构内的物联网设备的工作参数数据，并根据工作参数数据，确定物联网设备散发的设备热量；确定围护结构内的人体信息，并根据人体信息，确定人体散发的人体热量；根据设备热量、人体热量，通过公式(4)，确定与设备热量和人体热量对应的空调的第二冷负荷；
Figure PCTCN2019101383-appb-000003
其中，Q为物联网设备或人体的得热，T为物联网设备投入使用时刻或人体进入围护结构内的时刻，τ-T为设备投入使用时刻或人体进入围炉机构内时刻到作用时间，JX τ-T为τ-T时间的物联网设备负荷强度系数、以及人体负荷强度系数。
在一些实施例中，湿量确定单元，具体用于获取围护结构内的环境参数值，以及散湿设备的工作参数数据，并根据工作参数数据以及环境参数值，确定散湿设备散发的设备湿量；确定围护结构内的人体信息，并根据人体信息，确定人体散发的人体湿量。
在一些实施例中，该装置还包括：静音模式控制单元，用于在根据围护结构内的物联网设备的工作参数数据，确定围护结构内的生活状态为睡眠状态的情况下，控制空调处于静音定时关机模式运行。
下面对空调控制的装置进行具体的描述。
图6是本公开实施例提供的空调控制装置的结构示意图。如图6所示，空调控制装置可包括：第一热量确定单元510、第二热量确定单元520以及第一控制单元530，该装置还包括：湿量确定单元540、第二控制单元550以及静音模式控制单元560。
空调与电视、电脑、手机终端、电灯、冰箱、洗衣机等等家电设备，通过WIFI连接，形成物联网智能家电系统，这样，可通过已构建的物联网，可获取围护结构内外的环境参数值，还可获取围护结构内的物联网设备的工作参数数据，并且，还能获取到围护结构内的人体信息，这样，在根据围护结构内的物联网设备的工作参数数据，确定围护结构内的生活状态为睡眠状态的情况下，静音模式控制单元560可控制空调处于静音定时关机模式运行。
而在其他的生活状态下，可根据冷负荷以及湿负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行。
其中，第一热量确定单元510可根据获取的环境参数值，确定第一热量对应的处于物联网中的空调的第一冷负荷。其中，第一热量是室外温度波通过空调所在的围护结构散入的。而第二热量确定单元520可根据获取的物联网设备的工作参数数据，确定物联网设备散发的设备热量；根据获取的人体信息，以及保存的人体散热散湿量对应关系，确定对应的人体散发的人体热量；以及，根据设备热量、人体热量，确定与设备热量和人体热量对应的空调的第二冷负荷。
而在湿量确定单元540未启动的情况下，第一控制单元530可根据第一冷负荷和第二冷负荷，控制空调的运行。而在湿量确定单元540确定冷负荷的情况下，即湿量确定单元540可根据环境参数值和工作参数数据，确定散湿设备散发的设备湿量，并可根据保存的人体散热散湿量对应关系，确定围护结构内的人体信息对应的人体散发的人体湿量，以及确定与设备湿量以及人体适量对应的湿负荷。这样，第二控制单元550可根据第一冷负荷，第二冷负荷，以及湿负荷，控制空调的运行。
可见，本实施例中，可根据冷负荷，或冷负荷与湿负荷，确定出最适宜的空调运行模式方案，并将指令发送给空调执行，自动控制空调的温度、风速等等，使用户处在一个最适宜的环境中。进一步提高了空调的智能性，以及用户的体验。
空调控制装置可在物联网的系统处理模块中，该系统处理模块可是一个单独的终端，也可是物联网中的任一设备，例如：空调，电视等。因此，本公开实施例还提供了一种空调，包括上述空调控制装置。
本公开实施例还提供了一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令设置为执行上述空调控制方法。
本公开实施例还提供了一种计算机程序产品，所述计算机程序产品包括存储在计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述空调控制方法。
上述的计算机可读存储介质可以是暂态计算机可读存储介质，也可以是非暂态计算机可读存储介质。
本公开实施例还提供了一种电子设备，其结构如图7所示，包括：
至少一个处理器(processor)100，图7中以一个处理器100为例；和存储器(memory) 101，还可以包括通信接口(Communication Interface)102和总线103。其中，处理器100、通信接口102、存储器101可以通过总线103完成相互间的通信。通信接口102可以被配置为信息传输。处理器100可以调用存储器101中的逻辑指令，以执行上述实施例的空调控制方法。
此外，上述的存储器101中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。
存储器101作为一种计算机可读存储介质，可被配置为存储软件程序、计算机可执行程序，如本公开实施例中的方法对应的程序指令/模块。处理器100通过运行存储在存储器101中的软件程序、指令以及模块，从而执行功能应用以及数据处理，即实现上述方法实施例中的空调控制方法。
存储器101可包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序；存储数据区可存储根据终端设备的使用所创建的数据等。此外，存储器101可以包括高速随机存取存储器，还可以包括非易失性存储器。
本公开实施例的技术方案可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括一个或多个指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本公开实施例所述方法的全部或部分步骤。而前述的存储介质可以是非暂态存储介质，包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等多种可以存储程序代码的介质，也可以是暂态存储介质。
本领域技术人员在考虑说明书及实践这里的公开后，将容易想到本公开的其它实施方案。本申请旨在涵盖本公开的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本公开的一般性原理并包括本公开未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本公开的真正范围和精神由下面的权利要求指出。
应当理解的是，本公开并不局限于上面已经描述并在附图中示出的精确结构，并且可以在不脱离其范围进行各种修改和改变。本公开的范围仅由所附的权利要求来限制。

Claims (10)

  1. 一种空调控制的方法，其特征在于，所述方法包括：
    确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，所述第一热量是室外温度波通过所述空调所在的围护结构散入的；
    确定与第二热量对应的所述空调的第二冷负荷，其中，所述第二热量是所述围护结构内的设备和人体散出的；
    根据所述第一冷负荷和所述第二冷负荷，控制所述空调的运行。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    确定所述围护结构内的设备和人体散湿形成的湿负荷；
    根据所述第一冷负荷，所述第二冷负荷，以及所述湿负荷，控制所述空调的运行。
  3. 根据权利要求1或2所述的方法，其特征在于，所述确定与第一热量对应的处于物联网中的空调的第一冷负荷包括：
    通过所述物联网，获取所述围护结构内外的环境参数值，并根据所述环境参数值，通过公式(1)，确定作用在外墙体和屋顶上的温度波散入的热量对应的主体冷负荷；
    通过公式(2)，确定与窗体传导的热量对应的第一窗体冷负荷，以及，通过公式(3)，确定阳光辐射通过所述窗体形成的第二窗体冷负荷；
    CLQ τ＝KFΔt τ-ε……………………………………………..…(1)
    CLQ c·τ＝KFΔt τ……………………………………………..…(2)
    CLQ j·τ＝x gx dC nC sFJ j·τ……………………………………………..…(3)
    其中，τ-ε为温度波作用于外墙体和屋顶表面的时间，K为围护结构传热系数，F为围护结构的计算面积，Δt τ-ε为当前作用时刻下围护结构的冷负荷计算温差，Δt τ当前作用时刻下围护结构的冷负荷计算温差，x g为窗体的有效面积系数，x d为地点修正系数，C s为窗体玻璃的遮挡系数，C n为窗体内遮阳设施的遮阳系数，J j·τ为当前作用时刻时，透过单位窗口面积的太阳总辐射热形成的冷负荷。当然，CLQ τ为主体冷负荷，CLQ c·τ为第一窗体冷负荷，而CLQ j·τ为第二窗体冷负荷。
  4. 根据权利要求1或2所述的方法，其特征在于，所述确定与第二热量对应的所述空调的第二冷负荷包括：
    获取所述围护结构内的物联网设备的工作参数数据，并根据所述工作参数数据，确定所述物联网设备散发的设备热量；
    确定所述围护结构内的人体信息，并根据所述人体信息，确定人体散发的人体热量；
    根据所述设备热量、所述人体热量，通过公式(4)，确定与所述设备热量和人体热 量对应的所述空调的第二冷负荷；
    CLQ τ＝QJX τ-T……………………………………………(4)；
    其中，Q为物联网设备或人体的得热，T为物联网设备投入使用时刻或人体进入围护结构内的时刻，τ-T为设备投入使用时刻或人体进入围炉机构内时刻到作用时间，JX τ-T为τ-T时间的物联网设备负荷强度系数、以及人体负荷强度系数。
  5. 根据权利要求2所述的方法，其特征在于，所述确定所述围护结构内的设备和人散湿形成的湿负荷包括：
    获取所述围护结构内的环境参数值，以及散湿设备的工作参数数据，并根据所述工作参数数据以及所述环境参数值，确定所述散湿设备散发的设备湿量；
    确定所述围护结构内的人体信息，并根据所述人体信息，确定人体散发的人体湿量。
  6. 根据权利要求1或2所述的方法，其特征在于，所述方法还包括：
    在根据所述围护结构内的物联网设备的工作参数数据，确定所述围护结构内的生活状态为睡眠状态的情况下，控制所述空调处于静音定时关机模式运行。
  7. 一种空调控制的装置，其特征在于，所述装置包括：
    第一热量确定单元，被配置为确定与第一热量对应的处于物联网中的空调的第一冷负荷，其中，所述第一热量是室外温度波通过所述空调所在的围护结构散入的；
    第二热量确定单元，被配置为确定与第二热量对应的所述空调的第二冷负荷，其中，所述第二热量是所述围护结构内的设备和人体散出的；
    第一控制单元，被配置为根据所述第一冷负荷和所述第二冷负荷，控制所述空调的运行。
  8. 根据权利要求7所述的装置，其特征在于，所述装置还包括：
    湿量确定单元，被配置为确定所述围护结构内的设备和人体散湿形成的湿负荷；
    第二控制单元，被配置为根据所述第一冷负荷，所述第二冷负荷，以及所述湿负荷，控制所述空调的运行。
  9. 一种电子设备，其特征在于，包括：
    至少一个处理器；以及
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行时，使所述至少一个处理器执行权利要求1至6任一项所述的方法。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机可执行指令，所述计算机可执行指令设置为执行如权利要求1至6任一项所述的方法。
PCT/CN2019/101383 2019-05-06 2019-08-19 空调控制的方法、装置及计算机存储介质 WO2020224087A1 (zh)

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CN111076390A (zh) * 2019-12-31 2020-04-28 北京世纪互联宽带数据中心有限公司 一种精密空调运行管理方法及装置
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