Intelligent air conditioner regulation and control method and device based on comfort model

Abstract

The invention discloses an air conditioner intelligent regulation and control method and device based on a comfort model. The method comprises the steps that firstly, the indoor environment temperature and the human body temperature are collected in real time through a sensor module; then, an environment comfort model to be used in a temperature interval corresponding to the indoor environment temperature is determined, and meanwhile, a human body comfort model to be used in a temperature interval corresponding to the human body temperature is determined; inputting the indoor environment temperature into a to-be-used environment comfort degree model to obtain an indoor environment comfort degree value, and inputting the indoor environment temperature and the human body temperature into a to-be-used human body comfort degree model to obtain a human body comfort degree value; and air conditioner control parameters are determined based on the indoor environment comfort level value and the human body comfort level value. The air conditioner can be controlled according to changes of the indoor environment and changes of the human body temperature of the user, and therefore the experience comfort of the user is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of air conditioning, and in particular relates to an intelligent air conditioning control method and device based on a comfort model. Background Art

[0002] In the field of air-conditioning control, as user demands become increasingly higher, the demand for intelligent control of air-conditioning is also increasing. However, in existing technologies, the control of air-conditioning mainly relies on a single temperature sensor, which controls the switch of the air-conditioning through a set temperature threshold, or provides preset modes based on time or scenes, such as energy-saving mode and sleep mode. However, they lack the ability to accurately perceive and adapt to real-time environmental changes, making it difficult to provide a truly intelligent experience in actual applications, resulting in a low user comfort experience.

[0003] Therefore, how to control the air conditioner in real time according to the changes in the indoor environment to improve the user's experience and comfort is a technical problem to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of the present invention is to solve the technical problem in the prior art that the air conditioner cannot be controlled in real time according to changes in the indoor environment, resulting in a low user experience.

[0005] To achieve the above technical objectives, the present invention provides, on the one hand, an intelligent air conditioning control method based on a comfort model, the method comprising: Collect indoor ambient temperature and human body temperature in real time through sensor modules; Determining an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determining a human comfort model to be used in a temperature range corresponding to the human body temperature; Inputting the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously inputting the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value; Air conditioning control parameters are determined based on the indoor environment comfort value and the human comfort value.

[0006] Furthermore, the air conditioning control parameter is determined based on the indoor environment comfort value and the human comfort value. The air conditioning control parameter is specifically a target temperature. The air conditioning control parameter is determined specifically by the following formula: , Where, is the target temperature, is the first weight, is the second weight, is the third weight, is the human comfort value, is the indoor environmental comfort value, is the compensation amount for the human body, is the environmental compensation amount, Set the temperature for history.

[0007] Furthermore, it includes multiple temperature intervals, which are divided according to the ambient temperature. Each temperature interval corresponds to a working condition, and the working conditions are specifically cold, cool, comfortable, warm and hot. Each temperature interval corresponds to an environmental comfort model and a human comfort model.

[0008] Furthermore, the method further comprises: Obtain a preset number of sample sets for each temperature interval, wherein the sample sets are specifically questionnaire sets; Taking the indoor ambient temperature as input, a regression algorithm is used for each temperature interval to obtain the first regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the first regression curve, and then the first regression curve with the highest confidence in each sample subset is used as the environmental comfort model for the corresponding temperature range.

[0009] Furthermore, after obtaining a preset number of sample sets for each temperature interval, the method further includes: Taking the indoor ambient temperature and human body temperature as input, a regression algorithm is used for each temperature interval to obtain the second regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the second regression curve, and then the second regression curve with the highest confidence in each sample subset is used as the human comfort model for the corresponding temperature range.

[0010] Furthermore, after collecting the indoor environment temperature and human body temperature, the method also includes judging whether the indoor environment temperature and human body temperature are abnormal values ​​according to preset conditions, and the preset conditions specifically include: Condition 1: If the distance between the human body and the air conditioner is greater than the preset distance, the human body temperature collected at that time is an abnormal value; Condition 2: If the human body temperature is less than 20° under cool, comfortable and warm working conditions, the human body temperature collected at that time is an abnormal value; Condition 3: If the human body temperature is less than 10° under cold working conditions, the human body temperature collected at that time is an abnormal value; Condition 4: If the human body temperature is less than 28° or greater than 36.5° under hot working conditions, the human body temperature collected at that time is an abnormal value.

[0011] Furthermore, the sensor module further includes a millimeter wave sensor for determining a human body position, and the method further includes adjusting the air outlet according to the human body position.

[0012] Furthermore, the sensor module further includes a humidity sensor for collecting a humidity value of the indoor environment, and the method further includes activating a dehumidification function according to the humidity value.

[0013] On the other hand, the present invention also provides an intelligent air conditioning control device based on a comfort model, the device comprising: Sensor module, used to collect indoor ambient temperature and human body temperature in real time; a determination module, configured to determine an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determine a human comfort model to be used in a temperature range corresponding to the human body temperature; a comfort module, configured to input the indoor environment temperature into an environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously input the indoor environment temperature and human body temperature into a human body comfort model to be used to obtain a human body comfort value; The control module is used to determine air-conditioning control parameters based on the indoor environment comfort value and the human body comfort value.

[0014] The present invention provides a method and device for intelligent air conditioning control based on a comfort model. Compared to existing technologies, this method first uses a sensor module to collect indoor ambient temperature and human body temperature in real time. It then determines a to-be-used environmental comfort model for the temperature range corresponding to the indoor ambient temperature, and simultaneously determines a to-be-used human body comfort model for the temperature range corresponding to the human body temperature. The indoor ambient temperature is then input into the to-be-used environmental comfort model to obtain an indoor ambient comfort value, and the indoor ambient temperature and human body temperature are simultaneously input into the to-be-used human body comfort model to obtain a human body comfort value. This method can control the air conditioning based on changes in the indoor environment and changes in the user's body temperature, thereby improving the user's comfort experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 1 is a flow chart of an intelligent air conditioning control method based on a comfort model provided in an embodiment of this specification; Figure 2 The figure shows a schematic diagram of the structure of an intelligent air-conditioning control device based on a comfort model provided in an embodiment of this specification. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0018] like Figure 1 The flowchart of the air conditioning intelligent control method based on the comfort model provided in the embodiment of this specification is shown. Although this specification provides the method operation steps or device structure shown in the following embodiments or drawings, the method or device may include more or fewer operation steps or module units after partial merger based on routine or no creative work. In the steps or structures that do not have a necessary causal relationship logically, the execution order of these steps or the module structure of the device is not limited to the execution order or module structure shown in the embodiments or drawings of this specification. When the method or module structure is applied in actual devices, servers or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or drawings (for example, in a parallel processor or multi-threaded processing environment, or even in a distributed processing or server cluster implementation environment).

[0019] The air conditioning intelligent control method based on the comfort model provided in the embodiments of this specification is applied in air conditioning equipment, such as Figure 1 As shown, the method specifically includes the following steps: Step S101: collect indoor ambient temperature and human body temperature in real time through a sensor module.

[0020] Various sensors are deployed on the indoor environment and air conditioning control circuit boards. These sensors collect real-time, multi-dimensional indoor environmental data, including temperature, humidity, light intensity, sound, and human activity. These sensors also monitor the air conditioning's operating parameters. All collected data is transmitted to a processor or server via Wi-Fi.

[0021] The present invention can also update and store family members' habit data, such as temperature preferences and activity patterns, etc. It uses advanced artificial intelligence algorithms combined with thermal comfort algorithms to conduct in-depth analysis of sensor data and reference family members' habit data.

[0022] Step S102: determining an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determining a human comfort model to be used in a temperature range corresponding to the human body temperature.

[0023] In an embodiment of the present application, multiple temperature intervals are included, and the temperature intervals are divided according to the ambient temperature. Each temperature interval corresponds to a working condition, and the working conditions are specifically cold, cool, comfortable, warm and hot. Each temperature interval corresponds to an environmental comfort model and a human comfort model.

[0024] The method further comprises: Obtain a preset number of sample sets for each temperature interval, wherein the sample sets are specifically questionnaire sets; Taking the indoor ambient temperature as input, a regression algorithm is used for each temperature interval to obtain the first regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the first regression curve, and then the first regression curve with the highest confidence in each sample subset is used as the environmental comfort model for the corresponding temperature range.

[0025] Specifically, use the indoor ambient temperature As calculation input, a regression algorithm is used for different temperature ranges. Through K-fold cross validation, the data set, also known as the sample set, is divided into K sample subsets. Training and validation are performed on each subset to obtain the curve with the highest confidence: , , Where, is the first regression curve obtained by the regression algorithm, k and b is the regression coefficient, is the predicted environmental comfort value, is the first regression curve corresponding to the sample subset.

[0026] After obtaining a preset number of sample sets for each temperature interval, the method further includes: Taking the indoor ambient temperature and human body temperature as input, a regression algorithm is used for each temperature interval to obtain the second regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the second regression curve, and then the second regression curve with the highest confidence in each sample subset is used as the human comfort model for the corresponding temperature range.

[0027] Specifically, using human body temperature , indoor ambient temperature As calculation input, a regression algorithm is used for different comfort intervals. Through K-fold cross validation, the data set is divided into K subsets, and training and validation are performed on each subset to obtain the curve with the highest confidence; , , Where, is the second regression curve obtained by the regression algorithm, is the second regression curve corresponding to the sample subset, is the predicted human comfort value.

[0028] After collecting the indoor environment temperature and human body temperature, the method also includes judging whether the indoor environment temperature and human body temperature are abnormal values ​​according to preset conditions, and the preset conditions specifically include: Condition 1: if the distance between the human body and the air conditioner is greater than the preset distance, the human body temperature collected at that time is an abnormal value; Condition 2: if the human body temperature is less than 20° under cool, comfortable and warm working conditions, the human body temperature collected at that time is an abnormal value; Condition 3: if the human body temperature is less than 10° under cold working conditions, the human body temperature collected at that time is an abnormal value; Condition 4: if the human body temperature is less than 28° or greater than 36.5° under hot working conditions, the human body temperature collected at that time is an abnormal value.

[0029] Step S103: input the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously input the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value.

[0030] Specifically, the indoor environmental comfort value The calculation is as follows: , Where, for The environmental comfort model corresponding to the temperature range has a total of 5 temperature ranges.

[0031] Human comfort value The calculation is as follows: , Where, for The human comfort model corresponding to the temperature range has a total of 5 temperature ranges.

[0032] Additionally, the sensor module includes: Infrared sensors: These are placed in different corners of the room to monitor temperature distribution and human activity. They monitor temperature changes in different areas in real time and identify the presence of people in specific areas, providing essential data for regional air conditioning control.

[0033] Millimeter wave sensors: installed on the ceiling or wall of the room and used to determine the position of the human body. The method also includes adjusting the air outlet according to the position of the human body. These sensors can use the penetration of millimeter waves to accurately locate the position and movement trajectory of the human body, thereby dynamically adjusting the air outlet direction and intensity of the air conditioner.

[0034] Sound Sensor: Deployed in the room, it monitors ambient noise and receives voice commands. This sensor automatically adjusts the air conditioner's fan speed and mode based on noise levels. It also supports voice control, allowing users to directly control the air conditioner through voice commands.

[0035] Temperature sensors: Temperature sensors are placed at multiple key locations indoors to monitor indoor temperature in real time. The data from these sensors forms the basis for temperature regulation in the air conditioning system.

[0036] Humidity sensor: This sensor, deployed alongside the temperature sensor, collects real-time humidity readings from the indoor environment. The method also includes activating a dehumidification function based on the humidity readings. This data is used to adjust the air conditioner's dehumidification function to ensure indoor comfort.

[0037] Light sensor: Installed near a window, it measures indoor light intensity. The light sensor's data is used to determine light intensity and adjust the air conditioner's operating mode, particularly to improve cooling performance in bright sunlight.

[0038] Step S104: determining air-conditioning control parameters based on the indoor environment comfort value and the human body comfort value.

[0039] Specifically, the air conditioning control parameter is the target temperature, and the air conditioning control parameter is determined by the following formula: , Where, is the target temperature, is the first weight, is the second weight, is the third weight, is the human comfort value, is the indoor environmental comfort value, is the compensation amount for the human body, is the environmental compensation amount, Set the temperature for history.

[0040] Among them, the human body compensation amount has three values ​​according to the indoor ambient temperature. When the indoor ambient temperature is greater than 36.5°, , when the indoor ambient temperature is less than 36°, , when the indoor ambient temperature is not less than 36° and not greater than 36.5°, .

[0041] Environmental compensation amount: , It is a constant value determined by the regression curve of the environmental comfort model.

[0042] Among them, the first weight, the second weight and the third weight all have corresponding initial weights, and the initial weights are different according to different working conditions. Specifically, when the working condition is cold and cool, the initial weight of the first weight is 0.7, the initial weight of the second weight is 0.2 and the initial weight of the third weight is 0.1; when the working condition is comfortable, the initial weight of the first weight is 0.7, the initial weight of the second weight is 0.2 and the initial weight of the third weight is 0.1. The initial weight is 0.4 and the second weight is The initial weight is 0.4 and the third weight is 0.2; when the working condition is warm and hot, the initial weight of the first weight is 0.6, the initial weight of the second weight is 0.3, and the initial weight of the third weight is 0.1; then after determining the initial weight of each weight according to the working condition, the initial weight is corrected by the following formula to obtain the corresponding first weight, second weight, and third weight: , , , Where t is the current time period (hours).

[0043] In addition, the present application solution also includes adjusting the wind speed according to the target temperature to obtain the target wind speed, as shown in the following formula: , Where, is the target wind speed, is the first coefficient, is the second coefficient, is the distance attenuation factor, Set wind speed for historical users.

[0044] The first coefficient is specifically 0.15 multiplied by k, where k is a constant value determined by the regression curve corresponding to the human comfort model. The second coefficient is determined by the following formula: , The third coefficient is determined by the following formula: , Where, d The distance between the human body and the air conditioner.

[0045] In addition, the present application solution can also adjust the wind direction of the air-conditioning outlet according to the target temperature, and update the target temperature according to the dehumidification intensity. Specifically, updating the target temperature according to the dehumidification intensity includes: Determine the target dehumidification intensity based on current humidity and environmental comfort; When the target dehumidification intensity is greater than a preset dehumidification value, the target temperature is updated.

[0046] Specifically, the target dehumidification intensity is determined by the following formula. The target dehumidification intensity is also the target humidity, ranging from 0 to 100%: Target dehumidification intensity = , Where, is the current humidity.

[0047] When the target dehumidification intensity is greater than the preset dehumidification value, for example, 40, the target temperature is updated using the following formula: , Where, is the updated target temperature.

[0048] In addition, this application also includes updating the historical set temperature and historical user-set wind speed, as follows: when hour: , , Where, Set the temperature value for the user, The difference between the temperature value set by the user and the target temperature.

[0049] In an embodiment of the present application, the method further includes periodically updating the environmental comfort model and the human comfort model.

[0050] Based on the above-mentioned air conditioning intelligent control method based on the comfort model, one or more embodiments of this specification also provide a platform and terminal for air conditioning intelligent control based on the comfort model. The platform or terminal may include devices, software, modules, plug-ins, servers, clients, etc. that use the methods described in the embodiments of this specification and are combined with necessary hardware implementation devices. Based on the same innovative concept, the system in one or more embodiments provided in the embodiments of this specification is as described in the following embodiments. Since the implementation scheme and method for solving the problem of the system are similar, the implementation of the specific system in the embodiments of this specification can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. The terms "unit" or "module" used below can be a combination of software and / or hardware that implements the predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware and a combination of software and hardware are also possible and conceived.

[0051] Specifically, Figure 2 This is a schematic diagram of the module structure of an embodiment of an intelligent air conditioning control device based on a comfort model provided in this specification. Figure 2 As shown, the air conditioning intelligent control device based on the comfort model provided in this specification includes: Sensor module 201, used to collect indoor ambient temperature and human body temperature in real time; A determination module 202 is configured to determine an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determine a human comfort model to be used in a temperature range corresponding to the human body temperature; The comfort module 203 is configured to input the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously input the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value; The control module 204 is configured to determine air conditioning control parameters based on the indoor environment comfort value and the human body comfort value.

[0052] It should be noted that the above-mentioned system may also include other implementation methods according to the description of the corresponding method embodiment. The specific implementation methods can refer to the description of the above-mentioned corresponding method embodiment, and will not be described one by one here.

[0053] An embodiment of the present application further provides an electronic device, including: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the method provided in the above embodiment.

[0054] The electronic device provided in the embodiment of the present application stores executable instructions of a processor in a memory. When the processor executes the executable instructions, it can first collect the indoor environment temperature and human body temperature in real time through a sensor module; then determine the environmental comfort model to be used in the temperature range corresponding to the indoor environment temperature, and simultaneously determine the human body comfort model to be used in the temperature range corresponding to the human body temperature; then input the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously input the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value; finally, determine the air conditioning control parameters based on the indoor environment comfort value and the human body comfort value. The air conditioning can be controlled according to changes in the indoor environment and changes in the user's body temperature, thereby improving the user's experience comfort.

[0055] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] The methods or devices described in the above embodiments of this specification can implement business logic through computer programs and record them on storage media. The storage media can be read and executed by a computer to achieve the effects of the solutions described in the embodiments of this specification, such as: Collect indoor ambient temperature and human body temperature in real time through sensor modules; Determining an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determining a human comfort model to be used in a temperature range corresponding to the human body temperature; Inputting the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously inputting the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value; Air conditioning control parameters are determined based on the indoor environment comfort value and the human comfort value.

[0057] The storage medium may include a physical device for storing information, typically digitizing the information and then storing it in a medium utilizing electrical, magnetic, or optical means. Examples of such storage media include: devices that store information electrically, such as various types of memory devices like RAM and ROM; devices that store information magnetically, such as hard disks, floppy disks, magnetic tapes, magnetic core memories, bubble memories, and USB flash drives; and devices that store information optically, such as CDs and DVDs. Of course, other types of readable storage media exist, such as quantum memories and graphene memories.

[0058] The embodiments of this specification are not limited to those that must comply with industry communication standards, standard computer resource data update and data storage rules, or the situations described in one or more embodiments of this specification. Certain industry standards or slightly modified implementation plans based on the implementation described in the embodiments using custom methods or embodiments can also achieve the same, equivalent, or similar implementation effects as the above embodiments, or the expected implementation effects after deformation. The embodiments obtained by applying these modified or deformed data acquisition, storage, judgment, processing methods, etc. can still fall within the scope of the optional implementation plans of the embodiments of this specification.

[0059] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel ATMEL AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, the controller can also be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the means for implementing various functions included therein can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0060] The device embodiments described above are merely illustrative. For example, the division of units described is merely a logical functional division. Actual implementations may employ alternative divisions, such as combining or integrating multiple units or plug-ins into another system, or omitting or disabling certain features. Furthermore, the coupling or direct coupling or communication connection shown or discussed between devices or units may be through interfaces, or indirect coupling or communication connection between devices or units may be electrical, mechanical, or otherwise.

[0061] These computer program instructions can also be loaded onto a computer or other programmable resource data updating device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0062] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, since the system embodiments are generally similar to the method embodiments, their description is relatively simple, and relevant parts can be referenced to the partial description of the method embodiments. Throughout this specification, reference to the terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of this specification. In this specification, the schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and integrate the different embodiments or examples, and features of different embodiments or examples, described in this specification, without conflict.

[0063] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. An intelligent air conditioning control method based on a comfort model, characterized in that: The method comprises: Collect indoor ambient temperature and human body temperature in real time through sensor modules; Determining an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determining a human comfort model to be used in a temperature range corresponding to the human body temperature; Inputting the indoor environment temperature into the environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously inputting the indoor environment temperature and human body temperature into the human body comfort model to be used to obtain a human body comfort value; Air conditioning control parameters are determined based on the indoor environment comfort value and the human comfort value.

2. The air conditioning intelligent control method based on the comfort model according to claim 1, characterized in that: The air conditioning control parameter is determined based on the indoor environment comfort value and the human comfort value. The air conditioning control parameter is specifically the target temperature. The air conditioning control parameter is determined specifically by the following formula: ， Where, is the target temperature, is the first weight, is the second weight, is the third weight, is the human comfort value, is the indoor environmental comfort value, is the compensation amount for the human body, is the environmental compensation amount, Set the temperature for history.

3. The air conditioning intelligent control method based on the comfort model according to claim 1, characterized in that: It includes multiple temperature intervals, which are divided according to the ambient temperature. Each temperature interval corresponds to a working condition, which are cold, cool, comfortable, warm and hot. Each temperature interval corresponds to an environmental comfort model and a human comfort model.

4. The air conditioning intelligent control method based on the comfort model according to claim 3, characterized in that: The method further comprises: Obtain a preset number of sample sets for each temperature interval, wherein the sample sets are specifically questionnaire sets; Taking the indoor ambient temperature as input, a regression algorithm is used for each temperature interval to obtain a first regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the first regression curve, and then the first regression curve with the highest confidence in each sample subset is used as the environmental comfort model for the corresponding temperature range.

5. The air conditioning intelligent control method based on the comfort model according to claim 4, characterized in that: After obtaining a preset number of sample sets for each temperature interval, the method further includes: Taking the indoor ambient temperature and human body temperature as input, a regression algorithm is used for each temperature interval to obtain the second regression curve; The sample set corresponding to each temperature range is divided into K sample subsets through K-fold cross validation; Training and verification are performed on each sample subset in the corresponding temperature range based on the second regression curve, and then the second regression curve with the highest confidence in each sample subset is used as the human comfort model for the corresponding temperature range.

6. The air conditioning intelligent control method based on the comfort model according to claim 3, characterized in that: After collecting the indoor environment temperature and human body temperature, the method also includes judging whether the indoor environment temperature and human body temperature are abnormal values ​​according to preset conditions, and the preset conditions specifically include: Condition 1: if the distance between the human body and the air conditioner is greater than the preset distance, the human body temperature collected at that time is an abnormal value; Condition 2: if the human body temperature is less than 20° under cool, comfortable and warm working conditions, the human body temperature collected at that time is an abnormal value; Condition 3: if the human body temperature is less than 10° under cold working conditions, the human body temperature collected at that time is an abnormal value; Condition 4: if the human body temperature is less than 28° or greater than 36.5° under hot working conditions, the human body temperature collected at that time is an abnormal value.

7. The air conditioning intelligent control method based on the comfort model according to claim 1, characterized in that: The sensor module further includes a millimeter wave sensor for determining a human body position, and the method further includes adjusting the air outlet according to the human body position.

8. The air conditioning intelligent control method based on the comfort model according to claim 1, characterized in that: The sensor module further includes a humidity sensor for collecting a humidity value of an indoor environment, and the method further includes activating a dehumidification function according to the humidity value.

9. An intelligent air conditioning control device based on a comfort model, characterized in that: The device comprises: Sensor module, used to collect indoor ambient temperature and human body temperature in real time; a determination module, configured to determine an environmental comfort model to be used in a temperature range corresponding to the indoor environmental temperature, and simultaneously determine a human comfort model to be used in a temperature range corresponding to the human body temperature; a comfort module, configured to input the indoor environment temperature into an environmental comfort model to be used to obtain an indoor environment comfort value, and simultaneously input the indoor environment temperature and human body temperature into a human body comfort model to be used to obtain a human body comfort value; The control module is used to determine air-conditioning control parameters based on the indoor environment comfort value and the human body comfort value.

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