WO2022130634A1 - 空気調和システム - Google Patents

空気調和システム Download PDF

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Publication number
WO2022130634A1
WO2022130634A1 PCT/JP2020/047515 JP2020047515W WO2022130634A1 WO 2022130634 A1 WO2022130634 A1 WO 2022130634A1 JP 2020047515 W JP2020047515 W JP 2020047515W WO 2022130634 A1 WO2022130634 A1 WO 2022130634A1
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WIPO (PCT)
Prior art keywords
air conditioning
indoor
humidity
air
heat load
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/JP2020/047515
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English (en)
French (fr)
Japanese (ja)
Inventor
▲琢▼哉 阿川
貴則 京屋
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Mitsubishi Electric Corp
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Mitsubishi Electric Corp
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Publication date
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Priority to JP2022569675A priority Critical patent/JP7345687B2/ja
Priority to PCT/JP2020/047515 priority patent/WO2022130634A1/ja
Publication of WO2022130634A1 publication Critical patent/WO2022130634A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F24F11/46—Improving electric energy efficiency or saving
    • 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
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • 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
    • 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
    • F24F2110/20—Humidity

Definitions

  • This disclosure relates to an air conditioning system.
  • the ventilation control device of Patent Document 1 Japanese Unexamined Patent Publication No. 7-120022
  • the ventilation control device of Patent Document 1 has a ventilation fan for ventilating the room, a plurality of sensors for detecting the environmental state in the room, and input values of the sensors to the input layer.
  • a neural network that is trained by allocating ventilation to the output layer, a judgment unit that selects ventilation from the output value of the output layer of the neural network, and a drive that controls the operation of the ventilation fan based on the selection result of the judgment unit. It is equipped with a control unit.
  • the ventilation control device described in Patent Document 1 can optimize the ventilation volume, but is an air conditioning device corresponding to natural ventilation randomly generated by a person opening an opening of an air conditioning management space such as a window. Cannot be controlled.
  • the object of the present disclosure is to provide an air conditioning system capable of controlling the air conditioning equipment according to natural ventilation.
  • the air conditioning outlet when notified that the air conditioning equipment and the opening of the air conditioning control space are open, the air conditioning outlet does not condense multiple indoor target temperatures and indoor target humidity.
  • the candidate having the minimum power consumption is selected, and the control device for controlling the air conditioning equipment is provided based on the selected candidate.
  • the candidate with the lowest power consumption is selected from the candidates for the combination of the indoor target temperature and the indoor target humidity in which the air conditioning outlet does not condense, so that the air conditioning according to the natural ventilation is selected.
  • Equipment can be controlled.
  • FIG. It is a figure which shows the structure of the air conditioning system 100 of Embodiment 1.
  • FIG. It is a figure which shows the structure of the control panel 500 of Embodiment 1.
  • FIG. It is a schematic diagram of the refrigerant circuit of the air conditioning system 100.
  • It is a figure which shows the schematic structure of the ventilation apparatus 13.
  • It is a figure which shows the data about the heat load amount in the air-conditioning management space in Embodiment 1.
  • FIG. It is a figure which shows the structure of the learning apparatus 101.
  • It is a flowchart which shows the learning procedure of a learning apparatus 101.
  • FIG. It is a figure which shows the 1st example of the candidate of the combination of the target temperature and the target humidity so that the air conditioning outlet does not condense dew. It is a figure which shows the 2nd example of the candidate of the combination of the target temperature and the target humidity so that the air conditioning outlet does not condense dew. It is a figure which shows the 3rd example of the candidate of the combination of the target temperature and the target humidity so that the air conditioning outlet does not condense dew.
  • FIG. It is a figure which shows the structure of the air conditioning system 100 of Embodiment 2. It is a figure which shows the data about the heat load amount in the air-conditioning management space in Embodiment 2.
  • FIG. It is a flowchart which shows the procedure of the dew condensation prevention control of Embodiment 2. It is a figure which shows the structure of the air conditioning system 100 of Embodiment 3. It is a figure which shows the structure of the control panel 500 of Embodiment 3. It is a figure which shows the hardware composition of the learning apparatus 101, the inference apparatus 201, or the control apparatus 600.
  • FIG. 1 is a diagram showing the configuration of the air conditioning system 100 of the first embodiment.
  • the air conditioning system 100 includes a control panel 500 and an air conditioning facility 200.
  • the air conditioner 200 includes an air conditioner 1 that operates as an internal air conditioner and a ventilation device 13 that operates as an external air conditioner.
  • the air conditioning device 1 mainly handles the sensible heat load in the room 901, which is an air conditioning management space.
  • the ventilation device 13 ventilates the room 901, which is an air conditioning management space, and mainly processes the latent heat load in the room 901.
  • FIG. 2 is a diagram showing the configuration of the control panel 500 of the first embodiment.
  • the control panel 500 includes a target temperature / humidity input unit 44, a control device 600, a learning device 101, a learned model storage device 301, and an inference device 201.
  • the control device 600 includes an air conditioning control unit 601 and a display device 701.
  • the air conditioning outlet does not condense dew.
  • the candidate with the lowest power is selected, and the air conditioning equipment 200 is controlled based on the selected candidate.
  • the air-conditioned harmony management space is, for example, an indoor space.
  • the opening is a window, a door, a shutter, or the like.
  • the open / closed state is an open state or a closed state.
  • the control device 600 When the opening of the air conditioning control space is open, the control device 600 does not condense dew on the air conditioning outlet. If there is no candidate for a combination of a plurality of indoor target temperatures and indoor target humidity, the air conditioning equipment 200 The circulation of the refrigerant is stopped, and the air conditioning equipment 200 is operated by blowing air.
  • the control device 600 When the control device 600 receives a notification that the opening of the air conditioning management space is open and then a notification that the opening of the air conditioning management space is closed, the control device 600 manages the air conditioning.
  • the air conditioning equipment 200 is controlled based on the indoor target temperature and the indoor target humidity set by the user through the target temperature / humidity input unit 44 before receiving the notification that the opening of the space is in the open state.
  • the air conditioner 1 includes a plurality of indoor units 11 and an outdoor unit 12.
  • the outdoor unit 12 is installed outdoors.
  • the indoor unit 11 is installed in the room 901.
  • Each of the outdoor unit 12 and each indoor unit 11 is connected to the control device 600 by the transmission line 903.
  • the ventilation device 13 is connected to the control device 600 by the transmission line 903.
  • FIG. 3 is a schematic diagram of the refrigerant circuit of the air conditioning system 100.
  • the air conditioner 1 includes a compressor 2, a four-way valve 3, an outdoor heat exchanger 4, an expansion valve 5, and an indoor heat exchanger 6. These are sequentially connected by pipes to form a refrigeration cycle configured to circulate the refrigerant.
  • the air conditioner 1 further includes an outdoor heat exchanger blower 7 and an indoor heat exchanger blower 8.
  • a compressor 2 a four-way valve 3, an outdoor heat exchanger 4, and a blower for an outdoor heat exchanger 7 are installed in the outdoor unit 12.
  • the outdoor unit 12 is provided with an evaporation temperature detecting device 31.
  • Each indoor unit 11 is provided with a suction temperature / humidity detection device 32 that detects the temperature / humidity of the suction air of the indoor unit 11.
  • the ventilation device 13 includes an expansion valve 5a mounted on the ventilation device and a cooler 9 for the ventilation device.
  • the ventilation device-mounted expansion valve 5a and the ventilation device cooler 9 connected in series to each other are connected in parallel to the expansion valve 5 and the indoor heat exchanger 6.
  • the ventilator 13 is provided with an air supply blower 10 for allowing air to pass through the ventilator cooler 9.
  • the air conditioner 1 is configured so that the flow direction of the refrigerant discharged from the compressor 2 can be switched by the four-way valve 3 to switch between cooling operation and heating operation.
  • the indoor heat exchanger 6 and the ventilator cooler 9 serve as an evaporator
  • the outdoor heat exchanger 4 serves as a condenser
  • the cooling operation is performed.
  • the indoor heat exchanger 6 becomes a condenser
  • the outdoor heat exchanger 4 becomes an evaporator
  • FIG. 3 shows the flow of the refrigerant during the cooling operation.
  • FIG. 4 is a diagram showing a schematic configuration of the ventilation device 13.
  • the ventilation device 13 includes a ventilation device cooler 9, a total heat exchanger 22, an air supply blower 10, and an exhaust blower 21 in the main body casing 13a.
  • the air supply air passage A and the exhaust air passage B are formed independently of each other.
  • the air supply air passage A takes in the outdoor air OA by the air supply blower 10 and passes it through the total heat exchanger 22 and the ventilation device cooler 9, and supplies it to the indoor 901 as the regulated air SA.
  • the exhaust ventilation passage B takes in the indoor air RA by the exhaust blower 21 and passes it through the total heat exchanger 22, and exhausts it to the outside as an exhaust EA.
  • the air that flows into the ventilator cooler 9 after passing through the total heat exchanger 22 in the air supply air passage A is referred to as a cooler inflow air IA.
  • the ventilation device 13 further includes a cooler inflow temperature / humidity detection device 23 that detects the temperature and humidity of the cooler inflow air IA, a CO2 concentration detection device 24 that detects the CO2 concentration of the indoor air RA, and a ventilation air volume detection device 25. To prepare for. The detected values of these detection devices 23 to 25 are output to the control device 600 via the transmission line 903.
  • the total heat exchanger 22 has, for example, a structure in which ventilation passages orthogonal to each other are alternately laminated.
  • the ventilator cooler 9 is composed of an evaporator of a refrigerating cycle, and cools the air passing through itself to a dew point temperature or lower to dehumidify it.
  • the ventilator 13 handles the latent heat load in the room 901 by the total heat exchanger 22 and the ventilator cooler 9.
  • the air supply blower 10 and the exhaust blower 21 control the amount of air flowing in the ventilation device 13 by controlling the rotation speed.
  • the ventilation device 13 configured in this way, ventilation is performed with the required ventilation volume (air volume VA) for maintaining a good environment (air quality, for example, CO2 concentration) in the room 901 (for example, keeping the CO2 concentration at 1000 ppm or less).
  • the control device 600 controls the rotation speeds of the air supply blower 10 and the exhaust blower 21.
  • the ventilation device 13 passes the outdoor air OA through the total heat exchanger 22 of the air supply air passage A and the cooler 9 for the ventilation device to dehumidify and supply the room 901, while the indoor air RA is supplied to the indoor air passage.
  • the latent heat load in the room 901 is processed by passing it through B and exhausting it to the outside of the room.
  • the air conditioning system 100 further includes an indoor temperature sensor 501, an indoor humidity sensor 502, an outdoor temperature sensor 503, and an outdoor humidity sensor 504.
  • the indoor temperature sensor 501 and the indoor humidity sensor 502 are arranged indoors, and the outdoor temperature sensor 503 and the outdoor humidity sensor 504 are arranged outdoors.
  • the control device 600 is connected to each of the indoor temperature sensor 501, the indoor humidity sensor 502, the outdoor temperature sensor 503, and the outdoor humidity sensor 504 by a transmission line 903.
  • the indoor temperature sensor 501 detects the indoor temperature Ta.
  • the outdoor temperature sensor 503 detects the outside air temperature Tb.
  • the target temperature / humidity input unit 44 sets the target temperature Ta_tgt in the room based on the operation of the user.
  • the indoor humidity sensor 502 detects the indoor humidity Xa.
  • the outdoor humidity sensor 504 detects the outside air humidity Xb.
  • the target temperature / humidity input unit 44 sets the target humidity Xa_tgt in the room based on the user's operation.
  • the air conditioning control unit 601 executes air conditioning control based on the detection values of the detection devices 31 and 32 in the air conditioning device 1 and the detection values of the detection devices 23 to 25 of the ventilation device 13.
  • the air conditioning control unit 601 calculates the temperature difference ⁇ T between the room temperature Ta detected by the room temperature sensor 501 and the target temperature Ta_tgt set by the target temperature / humidity input unit 44 as the air conditioning sensible heat load Q1.
  • the air conditioning control unit 601 calculates the outside air latent heat load Q2o by the following formula.
  • Q2o VA ⁇ ⁇ a ⁇ (Xa_o-Xa_tgt) ⁇ ⁇ ⁇ (1)
  • VA represents the ventilation air volume detected by the ventilation air volume detecting device 25
  • Xa_o represents the humidity of the air after passing through the total heat exchanger 22
  • ⁇ a represents the air density.
  • the air conditioning control unit 601 calculates the latent heat load Q2m of the human body by the following formula.
  • Q2m Qi ⁇ N ...
  • Qi is the latent heat load per person
  • N is the number of people in the room.
  • the number of people in the room N can be determined by using the CO2 concentration, the detection value VA of the ventilation air volume detection device 25, the motion sensor, or the like.
  • the air conditioning control unit 601 calculates the sum of the outside air latent heat load Q2o and the human body latent heat load Q2m as the air conditioning latent heat load Q2.
  • the trained model storage device 301 stores a trained model that infers the open / closed state of the opening of the air conditioning management space from the data regarding the heat load amount in the air conditioning management space.
  • the learning device 101 generates a trained model and stores it in the trained model storage device 301.
  • FIG. 5 is a diagram showing data regarding the amount of heat load in the air conditioning management space according to the first embodiment.
  • the data regarding the heat load amount in the air conditioning control space in the first embodiment includes the outside air temperature, the outside air humidity, the room temperature, the room humidity, the sensible heat load for air conditioning, the latent heat load for air conditioning, the power consumption of the equipment in the room, and the date and time. Includes at least one.
  • the data on the amount of heat load in these air-conditioning control spaces are highly related to the open / closed state of the opening of the air-conditioning control space.
  • the air conditioning control unit 601 acquires the outside air temperature Tb from the outdoor temperature sensor 503.
  • the air conditioning control unit 601 acquires the outside air humidity Xb from the outdoor humidity sensor 504.
  • the air conditioning control unit 601 acquires the indoor temperature Ta from the indoor temperature sensor 501.
  • the air conditioning control unit 601 acquires the indoor humidity Xa from the indoor humidity sensor 502.
  • the air conditioning control unit 601 calculates the temperature difference ⁇ T between the room temperature Ta and the target temperature Ta_tgt set by the target temperature / humidity input unit 44 as the air conditioning sensible heat load Q1.
  • the air conditioning control unit 601 calculates the air conditioning latent heat load Q2 according to the equations (1) to (3).
  • the air conditioning control unit 601 acquires the power consumption of the indoor equipment from the switchboard or the like.
  • the power consumption of indoor equipment includes the power consumption of air conditioning systems, lighting equipment, personal computers, and displays.
  • the air conditioning control unit 601 acquires the date and time by an internal timer or the like.
  • the outside air temperature, outside air humidity, room temperature, room humidity, air conditioning sensible heat load, air conditioning latent heat load, power consumption of indoor equipment, and date and time are sent from the air conditioning control unit 601 to the learning device 101 and the inference device 201.
  • the inference device 201 infers the open / closed state of the opening of the air conditioning management space by using the learned model stored in the learned model storage device 301.
  • FIG. 6 is a diagram showing the configuration of the learning device 101.
  • the learning device 101 includes an operation input unit 104, a data acquisition unit 102, and a model generation unit 103.
  • the operation input unit 104 inputs the current open / closed state of the opening and outputs it to the control device 600.
  • the data acquisition unit 102 acquires (correct answer) the open / closed state of the opening of the air conditioning management space from the operation input unit 104. For example, the open state is "0" and the closed state is "1".
  • the data acquisition unit 102 acquires data on the heat load amount in the air conditioning management space at the time when the open / closed state of the opening of the air conditioning management space is acquired from the operation input unit 104 from the air conditioning control unit 601.
  • the model generation unit 103 is based on the data on the heat load amount in the air conditioning management space acquired by the data acquisition unit 102 and the learning data in which the open / closed state (correct answer) of the opening of the air conditioning management space is associated with each other. Then, from the data on the heat load in the air conditioning control space, a trained model that infers the open / closed state of the opening of the air conditioning control space is generated.
  • the learning algorithm used by the model generation unit 103 a known algorithm such as supervised learning, unsupervised learning, or reinforcement learning can be used. As an example, a case where a neural network is applied will be described.
  • FIG. 7 is a diagram showing the configuration of a neural network.
  • the model generation unit 103 learns the open / closed state of the opening of the air conditioning management space by, for example, according to a neural network model, by so-called supervised learning.
  • supervised learning refers to a method of learning a feature in the learning data by giving a set of data of an input and a result (label) to the learning device 101, and inferring the result from the input.
  • a neural network is composed of an input layer consisting of a plurality of neurons, an intermediate layer (hidden layer) consisting of a plurality of neurons, and an output layer consisting of a plurality of neurons.
  • the intermediate layer may be one layer or two or more layers.
  • the values are multiplied by the weights W1 (w11 to w16) and input to the intermediate layers (Y1 to Y2). Then, the result is further multiplied by the weight W2 (w21 to w26) and output from the output layer (Z1 to Z3). This output result depends on the values of the weights W1 and W2.
  • the neural network is learning to infer the open / closed state of the opening of the air conditioning management space from the data on the heat load in the air conditioning management space by so-called supervised learning according to the learning data acquired by the data acquisition unit 102. Generate a finished model.
  • the neural network inputs data on the amount of heat load in the air conditioning management space to the input layer, and the result output from the output layer approaches the open / closed state (correct answer) of the opening of the air conditioning management space. Learning is done by adjusting the weights W1 and W2.
  • the model generation unit 103 generates and outputs a trained model by executing the above learning.
  • the trained model storage device 301 stores the trained model output from the model generation unit 103.
  • FIG. 8 is a flowchart showing the learning procedure of the learning device 101.
  • the data acquisition unit 102 acquires (correct answer) the open / closed state of the opening of the air conditioning management space input by the user through the operation input unit 104.
  • the data acquisition unit 102 acquires data on the heat load amount in the air conditioning management space at the time when the open / closed state of the opening of the air conditioning management space input from the user through the operation input unit 104 is acquired from the air conditioning control unit 601. do.
  • step b2 the model generation unit 103 learns that the data regarding the heat load amount in the air conditioning management space acquired by the data acquisition unit 102 and the open / closed state (correct answer) of the opening of the air conditioning management space are associated with each other. Based on the data, a trained model that infers the open / closed state of the opening of the air conditioning control space is generated from the data on the heat load in the air conditioning control space.
  • step b3 the trained model storage device 301 stores the trained model generated by the model generation unit 103.
  • FIG. 9 is a diagram showing the configuration of the inference device 201.
  • the inference device 201 includes a data acquisition unit 202 and an inference unit 203.
  • the data acquisition unit 202 acquires data on the amount of heat load in the air conditioning management space from the air conditioning control unit 601.
  • the inference unit 203 uses the trained model stored in the trained model storage device 301 to open the air harmony management space from the data regarding the heat load in the air balance management space acquired by the data acquisition unit 202. Infer the open / closed state of. That is, the inference unit 203 is inferred from the data on the heat load in the air conditioning management space by inputting the data on the heat load in the air conditioning management space acquired by the data acquisition unit 202 into the trained model. It is possible to output the open / closed state of the opening of the air conditioning control space.
  • FIG. 10 is a flowchart showing the inference procedure of the inference device 201.
  • the data acquisition unit 202 acquires data regarding the amount of heat load in the air conditioning management space from the air conditioning control unit 601.
  • step c2 the inference unit 203 uses the trained model stored in the trained model storage device 301 to perform air balance management from the data on the heat load in the air balance management space acquired by the data acquisition unit 202. Infer the open / closed state of the opening in the space.
  • step c3 the inference unit 203 outputs the open / closed state of the opening of the air conditioning management space obtained by the trained model to the air conditioning control unit 601.
  • step c4 when the opening of the air conditioning control space is closed, the process proceeds to step c5, and when the opening of the air conditioning control space is open, the process proceeds to step c6.
  • step c5 the inference unit 203 notifies the air conditioning control unit 601 that the opening of the air conditioning management space is closed.
  • step c6 the control device 600 notifies the air conditioning control unit 601 that the opening of the air conditioning management space is open.
  • FIG. 11 is a flowchart showing the procedure of air conditioning control according to the first embodiment.
  • the air conditioning control unit 601 starts the normal operation of the air conditioning device 1 and the ventilation device 13 based on the indoor target temperature and the indoor target humidity set by the user through the target temperature / humidity input unit 44.
  • step S102 When the air conditioning control unit 601 receives the notification that the opening of the air conditioning management space is open in step S102, the process proceeds to step S103.
  • step S103 the air conditioning control unit 601 starts dew condensation prevention control.
  • the air conditioning control unit 601 receives the notification that the opening of the air conditioning management space is closed in step S104, the process proceeds to step S105.
  • step S105 the air conditioning control unit 601 causes the air conditioning device 1 and the ventilation device 13 to resume normal operation.
  • the air conditioning control unit 601 restarts the normal operation of the air conditioning device 1 and the ventilation device 13 based on the indoor target temperature and the indoor target humidity set by the user through the target temperature / humidity input unit 44. ..
  • FIG. 12 is a flowchart showing the procedure of the dew condensation prevention control according to the first embodiment.
  • the air conditioning control unit 601 acquires the indoor temperature Ta from the indoor temperature sensor 501 and the indoor humidity Xa from the indoor humidity sensor 502.
  • step S202 when there is a candidate for a combination of the target temperature and the target humidity so that the air conditioning outlet does not condense, the process proceeds to step S203. If there is no candidate for a combination of the target temperature and the target humidity such that the air conditioning outlet does not condense dew, the process proceeds to step S207.
  • step S203 the air conditioning control unit 601 calculates the air conditioning sensible heat load Q1 and the air conditioning latent heat load Q2 for each candidate.
  • the air conditioning control unit 601 calculates the temperature difference ⁇ T between the room temperature Ta and the target temperature Ta_tgt set by the target temperature / humidity input unit 44 as the air conditioning sensible heat load Q1.
  • the air conditioning control unit 601 calculates the outside air latent heat load Q2o using the target temperature Ta_tgt set by the target temperature / humidity input unit 44 based on the equation (1).
  • the air conditioning control unit 601 calculates the latent heat load Q2m of the human body according to the equation (2).
  • the air conditioning control unit 601 calculates the sum of the outside air latent heat load Q2o and the human body latent heat load Q2m as the air conditioning latent heat load Q2.
  • step S204 the air conditioning control unit 601 refers to a predetermined table based on the air conditioning sensible heat load Q1 and the air conditioning latent heat load Q2 for each candidate, and refers to the power consumption of the air conditioning device 1 and the ventilation device. The sum Qxy with the power consumption of is obtained.
  • step S205 the air conditioning control unit 601 sets the candidate having the smallest sum Qxy of power consumption as a combination of the indoor target temperature Ta_tgt and the indoor target humidity Xa_tgt.
  • step S206 the air conditioning control unit 601 controls the air conditioning device 1 and the ventilation device 13 based on the combination of the indoor target temperature Ta_tgt and the indoor target humidity Xa_tgt.
  • step S207 the air conditioning control unit 601 stops the circulation of the refrigerant of the air conditioning device 1 and the ventilation device 13, and causes the air conditioning device 1 and the ventilation device 13 to perform an air blowing operation.
  • the air conditioning control unit 601 causes the air conditioning device 1 and the ventilation device 13 to perform the blowing operation by operating the indoor heat exchanger blower 8 and the air supply blower 10.
  • FIG. 13 is a diagram showing the first example of a candidate for a combination of a target temperature and a target humidity so that the air conditioning outlet does not condense dew.
  • the air conditioning control unit 601 sets a candidate for a combination of a target temperature in a plurality of rooms where the air conditioning outlet does not condense and a target humidity in the room based on the detected indoor temperature Ta and the detected indoor humidity Xa.
  • the air conditioning control unit 601 is the air among the four vicinitys (Ta + ⁇ , Xa- ⁇ ), (Ta + ⁇ , Xa + ⁇ ), (Ta- ⁇ , Xa- ⁇ ), and (Ta- ⁇ , Xa + ⁇ ) of (Ta, Xa). If the relative humidity of the diagram is below the 100% curve, set it as a candidate for the combination of the target temperature and the target humidity so that the air conditioning outlet does not condense.
  • ⁇ and ⁇ are predetermined values.
  • the air conditioning equipment can be controlled according to the presence or absence of natural ventilation from the opening of the air conditioning management space.
  • air conditioning control when it is detected that the opening is open, air conditioning control can be executed so as to prevent dew condensation while suppressing power consumption.
  • the user When it is detected that the opening is open, the user may be notified not to forget to close the opening. If it is detected that the opening is closed, the user may be notified to open the opening to prevent virus infection.
  • FIG. 14 is a diagram showing a second example of a candidate combination of a target temperature and a target humidity so that dew condensation does not occur on the air conditioning outlet.
  • the temperature can be set to Tx or less during cooling operation.
  • the air conditioning control unit 601 Based on the detected indoor temperature Ta and the detected indoor humidity Xa, the air conditioning control unit 601 sets candidates for a combination of a plurality of indoor target temperatures and indoor target humidity in which the air conditioning outlet does not condense.
  • the air conditioning control unit 601 is the air among the four vicinitys (Ta + ⁇ , Xa- ⁇ ), (Ta + ⁇ , Xa + ⁇ ), (Ta- ⁇ , Xa- ⁇ ), and (Ta- ⁇ , Xa + ⁇ ) of (Ta, Xa). If the relative humidity of the diagram is below the 100% curve and the upper limit temperature Tx or less that can be set during cooling operation is set as a candidate for the combination of the target temperature and the target humidity so that the air conditioning outlet does not condense. do. However, ⁇ and ⁇ are predetermined values. In the example of FIG. 14, there is no candidate for a combination of the target temperature and the target humidity so that the air conditioning outlet does not condense dew.
  • FIG. 15 is a diagram showing a third example of a candidate combination of a target temperature and a target humidity so that dew condensation does not occur on the air conditioning outlet.
  • the air conditioning control unit 601 sets the target temperature and the target humidity so that the air conditioning outlet does not condense at points on the grid at regular intervals d, where the relative humidity of the air diagram is below the curve of 100%. Set as a candidate for combination.
  • FIG. 16 is a diagram showing the configuration of the air conditioning system 100 of the second embodiment.
  • the difference between the air conditioning system 100 of the second embodiment and the air conditioning system 100 of the first embodiment is that the air conditioning system 100 of the second embodiment does not include the ventilation device 13.
  • FIG. 17 is a diagram showing data regarding the amount of heat load in the air conditioning management space according to the second embodiment.
  • the data regarding the amount of heat load in the air conditioning control space in the second embodiment includes at least one of outside air temperature, outside air humidity, room temperature, room humidity, air conditioning sensible heat load, power consumption of room equipment, and date and time. include.
  • the data regarding the heat load amount in the air conditioning control space does not have the latent heat load for air conditioning.
  • the learning device 101 generates a trained model that infers the open / closed state of the opening of the air conditioning management space from the data related to the heat load shown in FIG.
  • the inference device 201 inputs data regarding the heat load amount shown in FIG. 17 into the trained model, and outputs the open / closed state of the opening of the air conditioning management space.
  • FIG. 18 is a flowchart showing the procedure of the dew condensation prevention control according to the second embodiment.
  • the air conditioning control unit 601 acquires the indoor temperature Ta from the indoor temperature sensor 501 and the indoor humidity Xa from the indoor humidity sensor 502.
  • step S302 when there is a candidate for a combination of the target temperature and the target humidity so that the air conditioning outlet does not condense, the process proceeds to step S303. If there is no candidate for a combination of the target temperature and the target humidity such that the air conditioning outlet does not condense dew, the process proceeds to step S307.
  • step S303 the air conditioning control unit 601 calculates the air conditioning sensible heat load Q1 for each candidate.
  • the air conditioning control unit 601 calculates the temperature difference ⁇ T between the room temperature Ta and the target temperature Ta_tgt set by the target temperature / humidity input unit 44 as the air conditioning sensible heat load Q1.
  • step S304 the air conditioning control unit 601 obtains the power consumption Qx of the air conditioning device 1 for each candidate with reference to a predetermined table based on the air conditioning sensible heat load Q1.
  • step S305 the air conditioning control unit 601 sets the candidate with the minimum power consumption Qx as a combination of the indoor target temperature Ta_tgt and the indoor target humidity Xa_tgt.
  • step S306 the air conditioning control unit 601 controls the air conditioning device 1 based on the combination of the indoor target temperature Ta_tgt and the indoor target humidity Xa_tgt.
  • step S307 the air conditioning control unit 601 causes the air conditioning device 1 to perform a ventilation operation. That is, the air conditioning control unit 601 stops the circulation of the refrigerant in the air conditioning system and operates the blower 8 for the indoor heat exchanger.
  • FIG. 19 is a diagram showing the configuration of the air conditioning system 100 of the third embodiment.
  • the difference between the air conditioning system 100 of the third embodiment and the air conditioning system of the first embodiment is that the air conditioning system 100 of the third embodiment includes an opening detection sensor 801.
  • the opening detection sensor 801 detects the open / closed state of the air conditioning management space and outputs a detection signal indicating the open / closed state to the control panel 500.
  • FIG. 20 is a diagram showing the configuration of the control panel 500 according to the third embodiment.
  • the control panel 500 of the third embodiment does not include the learning device 101, the trained model storage device 301, and the inference device 201.
  • the air conditioning control unit 601 receives a detection signal indicating the open / closed state of the air conditioning management space from the opening detection sensor 801.
  • the air conditioning control unit 601 executes air conditioning control in the same manner as in the first embodiment based on the open / closed state of the air conditioning management space represented by the detection signal.
  • the learning device 101 and the inference device 201 are provided inside the air conditioning system, they may be connected to the air conditioning system through a network and may be devices separate from the air conditioning system. Further, the learning device 101 and the inference device 201 may exist on the cloud server.
  • the model generation unit 103 may learn the opening state of the opening according to the learning data created in the plurality of air conditioning systems.
  • the model generation unit 103 may acquire learning data from a plurality of air conditioning systems used in the same area, or may acquire training data from a plurality of air conditioning systems operating independently in different areas. May be used to learn the opening state of the opening. It is also possible to add or remove an air conditioning system that collects learning data from the target on the way. Further, a learning device that has learned the open / closed state of the opening for one air conditioning system is applied to another air conditioning system, and the open / closed state of the opening is relearned and updated for this other air conditioning system. You may do so.
  • model generation unit 103 As the learning algorithm in which the model generation unit 103 is used, deep learning that learns the extraction of the feature amount itself can also be used, and other known methods such as genetic programming, functional logic programming, or support vector can be used. Machine learning may be executed according to the machine or the like.
  • FIG. 21 is a diagram showing a hardware configuration of the learning device 101, the inference device 201, or the control device 600.
  • the learning device 101, the inference device 201, and the control device 600 can configure the corresponding operation with the hardware or software of the digital circuit.
  • the functions of the learning device 101, the inference device 201, and the control device 600 are realized by using software
  • the learning device 101, the inference device 201, and the control device 600 are, for example, as shown in FIG. 21, the bus 5003.
  • the processor 5002 and the memory 5001 connected by the above are provided, and the program stored in the memory 5001 can be executed by the processor 5002.
  • the inference device infers the open / closed state of the opening of the air conditioning management space from the input data acquired by the data acquisition unit using the trained model. It is not limited.
  • the inference device may infer the open / closed state of the opening of the air conditioning management space from the input data acquired by the data acquisition unit based on rule-based inference or case-based inference.
  • the control device 600 has a plurality of candidates for a combination of indoor target temperature and indoor target humidity in which the air conditioning outlet does not condense when the opening of the air conditioning control space is open. If not, the circulation of the refrigerant of the air conditioning equipment 200 is stopped and the air conditioning equipment 200 is operated by blowing air, but the present invention is not limited to this. In such a case, the control device 600 may also stop the ventilation operation of the air conditioning equipment 200.

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Air Conditioning Control Device (AREA)
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017142013A (ja) * 2016-02-10 2017-08-17 三菱電機株式会社 制御装置、制御システムおよびプログラム
JP2019043279A (ja) * 2017-08-31 2019-03-22 株式会社デンソー 埃濃度検出装置
WO2019087264A1 (ja) * 2017-10-30 2019-05-09 三菱電機株式会社 空気調和装置、制御方法およびプログラム
JP2020079784A (ja) * 2014-03-03 2020-05-28 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ 熱画像処理方法および熱画像処理装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2020079784A (ja) * 2014-03-03 2020-05-28 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ 熱画像処理方法および熱画像処理装置
JP2017142013A (ja) * 2016-02-10 2017-08-17 三菱電機株式会社 制御装置、制御システムおよびプログラム
JP2019043279A (ja) * 2017-08-31 2019-03-22 株式会社デンソー 埃濃度検出装置
WO2019087264A1 (ja) * 2017-10-30 2019-05-09 三菱電機株式会社 空気調和装置、制御方法およびプログラム

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