A method and system for human thermal regulation in non-uniform clothing state

Abstract

The application discloses a kind of non-uniformly dressed human body thermal regulation method and system under state, including user interaction device, information acquisition device, intelligent control terminal and air supply execution system;The information acquisition device includes the infrared thermal imager, micro weather meter, black ball temperature sensor arranged in room;The air supply execution system of air conditioning system is arranged in indoor space.The application is automatically identified and calculated by intelligent control terminal, and the local clothing thermal resistance form of user human body under non-uniformly dressed state is constructed, and the human body thermal regulation model of accurate and accurate mapping coupling is constructed, to improve the prediction accuracy of human body thermal physiological response under complex wearing scene, finally realize the closed-loop control of indoor environment temperature with thermal comfort and energy saving.The application aims to provide a precise and personalized thermal comfort protection scheme for personnel in daily dressing, indoor thermal comfort regulation and other scenes.

Description

Technical Field

[0001] This invention relates to the field of human thermal comfort and intelligent temperature control, specifically to a method and system for human thermal regulation under non-uniform clothing conditions. Background Technology

[0002] With the development of indoor thermal environment control technology, people's requirements for indoor thermal comfort and energy efficiency are constantly increasing. In real-life scenarios, the thermal resistance distribution of human clothing generally exhibits significant non-uniformity and dynamic time-varying characteristics. Affected by factors such as clothing coverage ratio, number of layers, draping method, and local exposed area, there are significant differences in the local thermal resistance of clothing in different parts of the human body, which directly leads to significant differentiation in the heat exchange process and thermophysiological response in different areas of the human body.

[0003] Human body thermal regulation models are the core technological foundation for indoor thermal environment simulation and control, and thermal comfort state prediction, and are widely used in building environment optimization, personalized environmental control, and other fields. Existing human body thermal regulation models, when applied to indoor environmental parameter design and control, generally employ simplified clothing thermal resistance representation methods, either fixing the overall thermal resistance of clothing or fixing specific zones. This approach is only suitable for scenarios with uniform clothing coverage and stable wearing conditions. It struggles to accurately represent the time-varying distribution characteristics of localized clothing thermal resistance under non-uniform clothing conditions, and cannot precisely couple localized thermal resistance changes to the corresponding nodes of the human body thermal regulation model. Consequently, the prediction accuracy of localized skin temperature, localized thermal sensation, and overall thermal comfort state is severely insufficient. Ultimately, this results in a mismatch between indoor thermal environment control strategies and the actual thermal needs of the human body, leading to substandard thermal comfort and ineffective energy waste in air conditioning systems. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method and system for human body thermal regulation under non-uniform clothing conditions. This solves the problem that existing methods are unable to adapt to the time-varying distribution characteristics of local clothing thermal resistance under non-uniform clothing conditions, resulting in a mismatch between indoor thermal environment control strategies and the actual thermal needs of the human body, leading to substandard thermal comfort and ineffective energy consumption of the air conditioning system.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a human body thermal regulation system under non-uniform clothing conditions, including a user interaction device, an information acquisition device, an intelligent control terminal, and an air conditioning air supply execution system.

[0006] The information acquisition device includes an infrared thermal imager, a miniature weather instrument, and a black sphere temperature sensor, all arranged in the room.

[0007] The air conditioning supply system is an air conditioning system installed in an indoor space.

[0008] The present invention also has the following technical features:

[0009] The infrared thermal imager is used to monitor the user's body temperature.

[0010] The aforementioned miniature weather instrument is used to monitor indoor air temperature, relative humidity, air velocity, and atmospheric pressure.

[0011] The black sphere temperature sensor is used to monitor indoor radiant temperature.

[0012] The user interaction device is used to collect users' physical characteristics and subjective feelings.

[0013] The intelligent control terminal runs a non-uniform clothing human body thermal regulation model.

[0014] The information acquisition device and the user interaction device will send the acquired information to the intelligent control terminal.

[0015] The intelligent control terminal inputs the acquired information into the non-uniform clothing human thermal regulation model, which is used to calculate and output the user's thermal comfort evaluation results and indoor comfort temperature.

[0016] The intelligent control terminal sends the calculated indoor comfort temperature adjustment command to the air conditioning air supply execution system to adjust the indoor air supply temperature.

[0017] This invention also provides a method for human body thermal regulation under non-uniform clothing conditions, which uses the aforementioned human body thermal regulation system under non-uniform clothing conditions and includes the following steps: Step 1: The user inputs their height into the smart control terminal via the user interaction device. ,weight ,age Body fat percentage Subjective thermal sensation Activity intensity .

[0018] Step 2: The information acquisition device collects thermal imaging temperature data of the user's body with non-uniform clothing. Body size coordinate data Indoor air temperature Indoor relative humidity Indoor radiant temperature Indoor air velocity Indoor atmospheric pressure .

[0019] Step 3: The intelligent control terminal uses a non-uniform clothing human body thermal regulation model to calculate the most comfortable desired indoor temperature for the user in their current clothing state. .

[0020] Step 4: The intelligent control terminal calculates the current indoor temperature. and desired temperature The difference .

[0021] Step 5: When At that time, the intelligent control terminal sends a temperature adjustment command to the air conditioning ventilation system, which then adjusts the indoor ambient temperature to the specified level according to the command. .

[0022] The non-uniform clothing-wearing human thermal regulation model includes: Step 3.1: The non-uniform clothing human body thermoregulation model divides the human body into: Central Node: Central Blood Pool.

[0023] Body parts: head, neck, left chest, right chest, left shoulder, right shoulder, left upper arm, right upper arm, left forearm, right forearm, left hand, right hand, waist, abdomen, left back, right back, left thigh, right thigh, left calf, right calf, left foot, right foot.

[0024] The body is divided into tissue layers: arteries, veins, superficial veins, core, muscles, fat, and skin.

[0025] The central blood pool is divided into body node 1, and then node numbers are assigned sequentially according to the method of "body locality - tissue level", defining the body node index sequence as follows: .

[0026] definition ; indicates the number of body parts divided in the model; definition Represents the total number of human body nodes in the model; Definition , Represents the set of parts corresponding to head error correction; definition , Represents the set of parts corresponding to left-hand error correction; definition , This represents the set of parts corresponding to right-hand error correction.

[0027] Step 3.2: Calculate the required parameters, including environmental parameters, user clothing parameters, and human body parameters.

[0028] The environmental parameters mentioned include: the convective heat transfer coefficient of each local part. Radiative heat transfer coefficient of each local part Evaporative heat transfer coefficient of each local part and the operating temperature of each local part .

[0029] The user clothing parameters include: the non-uniform clothing thermal conditioning model will input the non-uniform clothing thermal imaging temperature distribution data of the human body. and body coordinate data According to the above The body parts are divided into: Local parts i Thermal imaging temperature data .

[0030] Local parts i Clothing size data .

[0031] The human body parameters mentioned include the ratio of the user's total body surface area to that of a standard human body. Surface area of ​​each local part The ratio of the user's input weight to the standard human body weight The ratio of the user's baseline blood flow to the baseline blood flow of a standard human body .

[0032] Step 3.3: The non-uniform clothing human thermal regulation model begins iteration. Calculate the skin temperature of various parts of the human body. .

[0033] Step 3.4: Based on the temperature model of various nodes in the human body According to the body node index sequence Extracting skin temperature from various local areas .

[0034] Step 3.5: Calculate the skin temperature from the model based on the measured skin temperature. Make corrections.

[0035] Step 3.6: Calculate the thermal sensation of each local area based on the corrected skin temperature. .

[0036] Step 3.7: Calculate the overall thermal sensation .

[0037] Step 3.8: Calculate the user's subjective thermal sensation. Human thermal sensation calculated by the model The difference .

[0038] Step 3.9: Based on the difference in human thermal sensation Correcting the human thermal sensation calculated by subsequent models To obtain the final human thermal sensation .

[0039] Step 3.10: Based on the final human thermal sensation Calculate the most comfortable desired indoor temperature .

[0040] Compared with the prior art, the present invention has the following technical effects: (I) This invention automatically identifies and calculates the local thermal resistance of clothing on the user's body under non-uniform clothing conditions through an intelligent control terminal, and constructs a precise mapping and coupling human body thermal regulation model to improve the prediction accuracy of human body thermal physiological response under complex clothing scenarios, and finally achieves closed-loop control of indoor ambient temperature that takes into account both thermal comfort and energy saving.

[0041] (II) The method of this invention divides the human body into 22 local areas, monitors the temperature distribution and clothing outline status of each local area in real time, and transmits the user's current thermal image and clothing outline data to an intelligent computing terminal. Using a non-uniform clothing thermal regulation model built into the intelligent computing terminal, the standard deviation of temperature and clothing coverage ratio of each local area are calculated and output. Corresponding to the thermal image area, the system automatically determines the user's clothing status as fully covered, partially covered, or completely exposed for each local area, and then calculates the effective air layer thickness and clothing thermal resistance for each local area. When the model's iterative calculation of the human body's thermal comfort temperature does not match the user's actively input thermal sensation, the signal is fed back to the intelligent control terminal in real time for subsequent calculations and output correction, ultimately outputting an accurate predicted value of the human body's thermal sensation status. When there is a significant difference between the human body's thermal comfort temperature calculated by the intelligent control terminal and the current indoor temperature, the intelligent control terminal will control the personalized thermal comfort regulation system to control the air supply and dynamically adjust parameters such as air supply temperature and humidity. This invention aims to provide a precise and personalized thermal comfort guarantee solution for people in daily clothing and indoor thermal comfort regulation scenarios. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the overall structure of the human body thermal regulation system under non-uniform clothing conditions according to the present invention.

[0043] The meanings of the labels in the attached diagram are as follows: 1-User interaction device; 2-Information acquisition device; 3-Air conditioning air supply execution system.

[0044] 2-1 Infrared thermal imager, 2-2 Miniature meteorological sensor, 2-3 Black sphere temperature sensor.

[0045] The specific content of the present invention will be further explained in detail below with reference to the embodiments. Detailed Implementation

[0046] The following are specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments. All equivalent modifications made based on the technical solutions of this application fall within the protection scope of the present invention.

[0047] Unless otherwise specified, all components in this invention are components known in the prior art.

[0048] Example 1: Following the above technical solutions, such as Figure 1 As shown, a human body thermal regulation system under non-uniform clothing conditions includes a user interaction device, an information acquisition device, an intelligent control terminal, and an air conditioning supply execution system.

[0049] The information acquisition device includes an infrared thermal imager, a miniature weather instrument, and a black sphere temperature sensor, all arranged in the room.

[0050] The air conditioning supply system is an air conditioning system installed in an indoor space.

[0051] The infrared thermal imager is used to monitor the user's body temperature.

[0052] The aforementioned miniature weather instrument is used to monitor indoor air temperature, relative humidity, air velocity, and atmospheric pressure.

[0053] The black sphere temperature sensor is used to monitor indoor radiant temperature.

[0054] The user interaction device is used to collect users' physical characteristics and subjective feelings.

[0055] The intelligent control terminal runs a non-uniform clothing human body thermal regulation model.

[0056] The information acquisition device and the user interaction device will send the acquired information to the intelligent control terminal.

[0057] The intelligent control terminal inputs the acquired information into the non-uniform clothing human thermal regulation model, which is used to calculate and output the user's thermal comfort evaluation results and indoor comfort temperature.

[0058] The intelligent control terminal sends the calculated indoor comfort temperature adjustment command to the air conditioning air supply execution system to adjust the indoor air supply temperature.

[0059] The infrared thermal imager 2-1 is installed indoors to monitor the location of the user throughout the entire indoor activity range, and is used to monitor the user's body surface temperature and body contour range.

[0060] The miniature weather sensor 2-2 is installed in an open indoor location to monitor indoor air temperature, relative humidity, air velocity, and atmospheric pressure.

[0061] The black sphere temperature sensor 2-3 is installed in an open indoor location to monitor indoor radiant temperature.

[0062] The air conditioning supply system 5 is controlled by the intelligent control terminal to provide indoor occupants with a thermally comfortable environment corresponding to their personalized clothing in a local space.

[0063] Example 2: A method for human body thermal regulation under non-uniform clothing conditions, using the human body thermal regulation system under non-uniform clothing conditions described in Example 1, includes the following steps: Step 1: The user inputs their height into the smart control terminal via the user interaction device. ,weight ,age Body fat percentage Subjective thermal sensation Activity intensity .

[0064] Step 2: The information acquisition device collects thermal imaging temperature data of the user's body with non-uniform clothing. Body size coordinate data Indoor air temperature Indoor relative humidity Indoor radiant temperature Indoor air velocity Indoor atmospheric pressure .

[0065] Step 3: The intelligent control terminal uses a non-uniform clothing human body thermal regulation model to calculate the most comfortable desired indoor temperature for the user in their current clothing state. .

[0066] As a preferred embodiment: Step 3 includes: Step 3.1: The non-uniform clothing human body thermoregulation model divides the human body into: Central Node: Central Blood Pool.

[0067] Body parts: head, neck, left chest, right chest, left shoulder, right shoulder, left upper arm, right upper arm, left forearm, right forearm, left hand, right hand, waist, abdomen, left back, right back, left thigh, right thigh, left calf, right calf, left foot, right foot.

[0068] The body is divided into tissue layers: arteries, veins, superficial veins, core, muscles, fat, and skin.

[0069] The central blood pool is divided into body node 1, and then node numbers are assigned sequentially according to the method of "body locality - tissue level", defining the body node index sequence as follows: .

[0070] definition ; indicates the number of body parts divided in the model; definition Represents the total number of human body nodes in the model; Definition , Represents the set of parts corresponding to head error correction; definition , Represents the set of parts corresponding to left-hand error correction; definition , This represents the set of parts corresponding to right-hand error correction.

[0071] The body node index sequence A total of 1 + 22 × 7 = 155 body nodes were defined; the above ; , representing the number of body parts divided by the model; This represents the total number of human body nodes divided by the model; .

[0072] Step 3.2: Calculate the required parameters, including environmental parameters, user clothing parameters, and human body parameters.

[0073] The environmental parameters mentioned include: the convective heat transfer coefficient of each local part. Radiative heat transfer coefficient of each local part Evaporative heat transfer coefficient of each local part and the operating temperature of each local part .

[0074] The user clothing parameters include: the non-uniform clothing thermal conditioning model will input the non-uniform clothing thermal imaging temperature data of the human body. and body coordinate data According to the above The body parts are divided into: Local parts i Thermal imaging temperature data .

[0075] Local parts i Clothing size data .

[0076] The human body parameters mentioned include the ratio of the user's total body surface area to that of a standard human body. Surface area of ​​each local part The ratio of the user's input weight to the standard human body weight The ratio of the user's baseline blood flow to the baseline blood flow of a standard human body .

[0077] Step 3.3: The non-uniform clothing human thermal regulation model begins iteration. Calculate the skin temperature of various parts of the human body. .

[0078] Step 3.4: Based on the temperature model of various nodes in the human body According to the body node index sequence Extracting skin temperature from various local areas .

[0079] Step 3.5: Calculate the skin temperature from the model based on the measured skin temperature. Make corrections.

[0080] Step 3.6: Calculate the thermal sensation of each local area based on the corrected skin temperature. .

[0081] Step 3.7: Calculate the overall thermal sensation .

[0082] Step 3.8: Calculate the user's subjective thermal sensation. Human thermal sensation calculated by the model The difference .

[0083] Step 3.9: Based on the difference in human thermal sensation Correcting the human thermal sensation calculated by subsequent models To obtain the final human thermal sensation .

[0084] Step 3.10: Based on the final human thermal sensation Calculate the most comfortable desired indoor temperature .

[0085] As a preferred embodiment: The convective heat transfer coefficient of each local part in step 3.2 Radiative heat transfer coefficient of each local part Evaporative heat transfer coefficient of each local part Operating temperature of each local part The calculation method is as follows:

[0086]

[0087]

[0088]

[0089] in: : Convective heat transfer coefficients of various local parts of the current user, W / K / m 2 .

[0090] : Radiative heat transfer coefficients of various local parts of the current user, in W / K / m 2 .

[0091] Evaporative heat transfer coefficients of various local parts of the current user, W / (m²) 2 ·℃).

[0092] : Operating temperature of each local part, °C.

[0093] The model provides the standard human body convective heat transfer coefficient under natural conditions, in W / K / m². 2 .

[0094] The model provides the standard human body radiation heat transfer coefficient under natural conditions, in W / K / m². 2 .

[0095] : The current air velocity in the user's environment, in m / s.

[0096] Lewis coefficient, K / kPa.

[0097] : Current ambient air temperature, °C.

[0098] : Current average ambient radiation temperature, °C.

[0099] : Surface area of ​​various body segments, in meters 2 .

[0100] , , , .

[0101] [4.3, 4.6, 3.8, 3.8, 4.0, 4.0, 4.0, 4.0, 4.0, 3.7, 3.7, 7.3, 7.3, 3.9, 3.8, 3.6, 3.6, 4.2, 4.2, 4.8, 4.8, 7.3, 7.3].

[0102] [4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5].

[0103] [0.1027, 0.0514, 0.0770, 0.0770, 0.0171, 0.0171, 0.0342, 0.0514, 0.1113, 0.1113, 0.2226, 0.2226, 0.1113, 0.1113, 0.0599, 0.0599].

[0104] The calculation yielded: [3.7998, 4.0670, 3.3597, 3.3597, 3.5385, 3.5385, 3.0257, 3.1815, 4.4998, 3.3127, 6.5702, 6.5702, 3.4605, 3.3597, 3.7227, 3.8655, 4.2739, 4.2739, 6.5702, 6.5702, 3.4091, 3.4091].

[0105] [4.4216, 4.7189, 3.1584, 3.1584, 0.7019, 0.7019, 1.4038, 2.1057, 4.5675, 3.3127, 0.7019, 0.7019, 4.5675, 4.5675, 2.4566, 2.4566, 4.0000, 4.0000, 6.1521, 6.1521, 3.4091, 3.4091].

[0106] [3.5558, 3.8089, 3.1475, 3.1475, 3.3127, 3.3127, 2.8329, 2.9788, 4.2138, 3.3127, 6.1523, 6.1523, 3.2423, 3.1475, 3.4889, 3.6204, 4.0000, 4.0000, 6.1523, 6.1523, 3.2423, 3.2423].

[0107] [18.0, ...

[0108] As a preferred embodiment: The calculation method for the user clothing parameters in step 3.2 is as follows: The non-uniform clothing thermal regulation model will input the non-uniform clothing thermal imaging temperature data of the human body. and body coordinate data According to the above The body parts are divided into various local parts. i Thermal imaging temperature data and various local parts i Clothing size data .

[0109] Count the number of thermal imaging data points for each local area. Then, based on the aforementioned local parts i Thermal imaging temperature data Calculate each local part i Measured average temperature The calculation method is as follows:

[0110] in: : Number of thermal imaging data points for each local area, in matrix form.

[0111] Local parts i Thermal imaging temperature data, in order to A matrix form based on the number of points in each local area, ℃.

[0112] Local parts i The measured average temperature, ℃.

[0113] [103, 51, 77, 77, 17, 17, 51, 51, 51, 51, 34, 34, 34, 51, 111, 111, 222, 222, 111, 111, 60, 60].

[0114] The calculation yielded: [31.5, 31.0, 24.6, 25.4, 23.0, 23.0, 25.1, 22.5, 31.0, 22.5, 29.9, 30.0, 23.0, 23.0, 23.0, 22.5, 22.5, 22.5, 30.5, 27.4, 27.4].

[0115] Calculate the temperature uniformity coefficient of each local part The calculation method is as follows:

[0116] in: Temperature uniformity coefficient of each local part.

[0117] The calculation yielded: [0.60, 0.70, 1.30, 1.50, 0.60, 0.60, 1.60, 0.50, 0.80, 0.50, 0.90, 0.90, 0.40, 0.40, 0.35, 0.35, 0.30, 0.30, 0.40, 0.80, 1.90, 1.90].

[0118] Calculate the clothing coverage ratio for each local area. The calculation method is as follows:

[0119] in: : lower than the average temperature of this part The number of thermal imaging data points.

[0120] [0, 0, 62, 54, 17, 17, 36, 51, 0, 51, 0, 0, 34, 51, 111, 111, 222, 222, 111, 0, 18, 18].

[0121] The calculation yielded: [0.00, 0.00, 0.81, 0.70, 1.00, 1.00, 0.71, 1.00, 0.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.00, 0.30, 0.30].

[0122] Determine the degree of clothing coverage in that area. Specifically, when and This area is fully covered. When and This area is completely exposed; when This area is partially covered.

[0123] Assessment results: Fully exposed areas: forehead, neck, left forearm, left hand, right hand, right calf.

[0124] Partially covered area: left upper arm ( 0.7), left chest (coverage) 0.8), right chest ( 0.7), left foot (coverage) 0.3), right foot (coverage) 0.3).

[0125] Full coverage areas: left shoulder, right shoulder, left back, right back, waist, abdomen, right upper arm, right forearm, left thigh, right thigh, left calf.

[0126] Based on the height entered by the user ,weight Data to calculate the baseline dimensions of various parts of the user's body. The calculation method is as follows:

[0127] in: , , The model provides the fitting coefficients for the baseline dimensions of local body parts.

[0128] : Height entered by the user, in meters.

[0129] : The user-input weight, in kg.

[0130] , .

[0131] [0.115, 0.050, 0.070, 0.070, 0.065, 0.065, 0.160, 0.160, 0.130, 0.130, 0.095, 0.095, 0.045, 0.050, 0.070, 0.070, 0.240, 0.240, 0.210, 0.210, 0.130, 0.130].

[0132] [0.00015, 0.00010, 0.00060, 0.00060, 0.00030, 0.00030, 0.00010, 0.00010, 0.00010, 0.00010, 0.00010, 0.00010, 0.00140, 0.00160, 0.00060, 0.00060, 0.00010, 0.00010, 0.00010, 0.00010, 0.00020, 0.00020].

[0133] [0.015, 0.008, 0.015, 0.015, 0.010, 0.010, 0.012, 0.012, 0.010, 0.010, 0.008, 0.008, 0.020, 0.020, 0.015, 0.015, 0.015, 0.015, 0.008, 0.008, 0.005, 0.005].

[0134] The calculation yielded: [0.2146, 0.0968, 0.1661, 0.1661, 0.1354, 0.1354, 0.2834, 0.2834, 0.2316, 0.2316, 0.1715, 0.1715, 0.1762, 0.1962, 0.1661, 0.1661, 0.4192, 0.4192, 0.3624, 0.3624, 0.2324, 0.2324].

[0135] Calculate the thermal resistance of clothing at various local areas under non-uniform clothing conditions. The calculation method is as follows:

[0136] in: Thermal resistance of clothing in various local areas, in matrix form, clo.

[0137] Heat flux density at various local locations, W / m 2 .

[0138] : Effective air layer thickness at each local location, in matrix form, in cm.

[0139] : Thermal conductivity of air, in matrix form, W / (m·K).

[0140] The heat flux density of each local part The calculation method is as follows:

[0141] The effective air layer thickness of each local part The calculation method is as follows:

[0142] in: : The maximum fit coefficient of clothing for each local part given by the model.

[0143] : The difference between the clothing size and the reference size for each part of the body, in cm.

[0144] The effective air layer thickness In the calculation method, when the part is fully covered, When the area is completely exposed, .

[0145] The difference between the clothing size and the reference size for each local part The calculation method is as follows:

[0146] [0.15, 0.18, 0.22, 0.22, 0.20, 0.20, 0.25, 0.25, 0.21, 0.21, 0.12, 0.12, 0.24, 0.23, 0.22, 0.22, 0.26, 0.26, 0.23, 0.23, 0.10, 0.10].

[0147] [1.05, 1.05, 1.10, 1.10, 1.08, 1.08, 1.06, 1.06, 1.07, 1.07, 1.03, 1.03, 1.12, 1.15, 1.10, 1.10, 1.09, 1.09, 1.08, 1.08, 1.04, 1.04].

[0148] [0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255, 0.0255].

[0149] [0.2146, 0.0968, 1.3661, 1.3661, 0.9354, 0.9354, 1.2834, 1.0834, 0.2316, 1.0316, 0.1715, 0.1715, 1.6762, 1.6962, 1.3661, 1.3661, 1.4192, 1.4192, 1.1624, 0.3624, 2.2324, 2.2324].

[0150] The calculation yielded: [0.0, 0.0, 1.2, 1.2, 0.8, 0.8, 1.0, 0.8, 0.0, 0.8, 0.0, 0.0, 1.5, 1.5, 1.2, 1.2, 1.0, 1.0, 0.8, 0.0, 2.0, 2.0].

[0151] [0.00, 0.00, 0.15, 0.13, 0.10, 0.10, 0.17, 0.11, 0.00, 0.11, 0.00, 0.00, 0.23, 0.26, 0.20, 0.20, 0.19, 0.19, 0.14, 0.00, 0.16, 0.16].

[0152] [96.5007, 95.1470, 45.2991, 50.7899, 34.8870, 34.8870, 49.5395, 31.3983, 88.4858, 30.6297, 106.2744, 106.2744, 34.6020, 34.3175, 33.7480, 33.7480, 31.9104, 31.9104, 33.4476, 92.9100, 83.2483, 83.2483].

[0153] [0.0000, 0.0000, 1.2439, 1.0174, 2.1510, 2.1510, 0.9890, 2.4955, 0.0000, 2.5652, 0.0000, 0.0000, 1.8419, 1.7865, 1.9800, 1.9800, 2.2490, 2.2490, 2.2503, 0.0000, 0.2619, 0.2619].

[0154] Calculate the thermal resistance area factor of non-uniform clothing in various local areas covered by clothing. The calculation method is as follows:

[0155] in: : Thermal resistance area factor of non-uniform clothing in various local areas covered by clothing.

[0156] The calculation yielded: [1.2600, 1.2600, 1.6456, 1.5754, 1.9268, 1.9268, 1.5666, 2.0336, 1.2600, 2.0552, 1.2600, 1.2600, 1.8310, 1.8138, 1.8738, 1.8738, 1.9572, 1.9572, 1.9576, 1.2600, 1.3412, 1.3412].

[0157] As a preferred embodiment: Step 3.2.3: Calculate the human body parameters required for the model. The calculation method is as follows:

[0158]

[0159]

[0160]

[0161] in: The ratio of a user's total body surface area to that of a standard human body.

[0162] : Surface area of ​​various parts of the user's body, in meters 2 .

[0163] The ratio of the user's input weight to the standard human body weight.

[0164] The ratio of a user's baseline blood flow to the baseline blood flow of a standard human body.

[0165] : Standard human height as defined by the model, in meters (m).

[0166] Standard human body weight, in kg.

[0167] Cardiac index, L / min / m 2 .

[0168] , , .

[0169] The calculation yielded: , , .

[0170] [0.0987, 0.0494, 0.0740, 0.0740, 0.0164, 0.0164, 0.0494, 0.0494, 0.0494, 0.0494, 0.0329, 0.0329, 0.0329, 0.0494, 0.1069, 0.1069, 0.2139, 0.2139, 0.1069, 0.1069, 0.0576, 0.0576].

[0171] As a preferred embodiment: Step 3.3.1: According to the body node index sequence Temperature matrix of various nodes in the human body Extracting the core temperature matrix of various parts of the human body using indexing Skin temperature matrix of different parts of the human body .

[0172] Step 3.3.2: Calculate the thermal signals of each local area. With cold sensation signals The calculation method is as follows:

[0173]

[0174] in: Local thermal signals related to body temperature regulation.

[0175] Local cold sensation signals related to body temperature regulation.

[0176] : Skin sensory coefficients for each local area defined by the model.

[0177] Skin temperature in various local areas Skin set point temperature The difference, in °C, is calculated as follows:

[0178] in: : The skin setpoint temperature given by the model, in °C.

[0179] [0.030, 0.035, 0.060, 0.060, 0.040, 0.040, 0.045, 0.045, 0.040, 0.040, 0.025, 0.025, 0.070, 0.075, 0.060, 0.060, 0.055, 0.055, 0.045, 0.045, 0.025, 0.025].

[0180] [31.1, 32.9, 33.9, 33.9, 33.3, 33.3, 32.4, 32.4, 31.9, 31.9, 29.0, 29.0, 34.9, 34.9, 33.3, 33.3, 32.5, 32.5, 30.8, 30.8, 29.8, 29.8].

[0181] [31.9, 31.3, 34.4, 34.3, 32.8, 32.8, 31.9, 32.4, 31.7, 32.2, 29.1, 29.3, 34.7, 35.8, 34.0, 34.0, 33.5, 33.5, 31.5, 31.0, 29.5, 29.4].

[0182] Steady-state calculation results: [0.8, -1.6, 0.5, 0.4, -0.5, -0.5, -0.5, 0.0, -0.2, 0.3, 0.1, 0.3, -0.2, 0.9, 0.7, 0.7, 1.0, 1.0, 0.7, 0.2, -0.3, -0.4].

[0183] [0.0240, 0.0000, 0.0300, 0.0240, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0120, 0.0025, 0.0075, 0.0000, 0.0675, 0.0420, 0.0420, 0.0550, 0.0550, 0.0315, 0.0090, 0.0000, 0.0000].

[0184] [-0.0240, 0.0000, -0.0300, -0.0240, 0.0000, 0.0000, 0.000, -0.0000, 0.0000, -0.0120, -0.0025, -0.0000, 0.0000, -0.0675, -0.0420, -0.0420, -0.0550, -0.0550, -0.0315, -0.0090, 0.0000, 0.0000].

[0185] Step 3.3.3: Calculate the saturated vapor pressure of the indoor environment. Vapor pressure of skin in various local areas Skin saturated vapor pressure in various local areas The calculation method is as follows:

[0186]

[0187] in: Indoor ambient saturated vapor pressure, kPa.

[0188] : Skin vapor pressure at various local sites, kPa.

[0189] Indoor relative humidity, %.

[0190] .

[0191] Steady-state calculation results: 0.6188.

[0192] [4.7290, 4.5700, 5.4400, 5.4100, 4.9750, 4.9750, 4.7290, 4.8650, 4.6750, 4.8100, 4.0290, 4.0760, 5.5310, 5.8770, 5.3200, 5.3200, 5.1740, 5.1740, 4.6230, 4.4930, 4.1230, 4.1000].

[0193] Calculate the sensible heat loss of human respiration Respiratory latent heat loss Sensible heat loss of skin in various local areas Skin moisture in various local areas Heat loss through skin evaporation in different local areas The calculation method is as follows:

[0194]

[0195]

[0196]

[0197]

[0198] in: Sensible heat loss due to respiration, W.

[0199] Latent heat loss due to respiration, W.

[0200] Sensible heat loss of the skin in various local areas, W.

[0201] : Heat loss through skin evaporation in various local areas, in W.

[0202] : Skin moisture coefficient of various local areas.

[0203] : The skin sweating coefficient given by the model.

[0204] The calculation method for the dry thermal resistance of various local parts is as follows:

[0205] The calculation method for the hygrothermal resistance of various local parts is as follows:

[0206] in: : The vapor permeability efficiency coefficient of clothing defined by the model.

[0207] Atmospheric pressure, kPa.

[0208] Core temperature of various local parts core setpoint temperature The difference, in °C, is calculated as follows:

[0209] in: : The core temperature of various parts of the user's body at present, in °C.

[0210] : Core setpoint temperature of each local part, °C.

[0211] = 16.5 ， 。

[0212] [36.5, ...

[0213] [37.2, 36.1, 36.3, 36.3, 36.5, 36.5, 35.4, 35.4, 34.4, 34.4, 31.3, 31.3, 37.3, 37.3, 36.4, 36.4, 35.7, 35.7, 33.9, 33.9, 32.5, 32.5].

[0214] [0.1006, 0.0252, 0.0452, 0.0452, 0.0435, 0.0435, 0.0338, 0.0338, 0.0385, 0.0385, 0.0311, 0.0311, 0.6310, 0.6310, 0.0258, 0.0258, 0.0364, 0.0364, 0.0382, 0.0382, 0.0558, 0.0558].

[0215] [0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45].

[0216] Steady-state calculation results: 2.14, .

[0217] [1.581, 1.216, 2.203, 2.175, 1.793, 1.793, 1.470, 1.643, 1.400, 1.573, 0.669, 0.669, 2.389, 2.744, 2.076, 2.076, 1.909, 1.909, 1.331, 1.161, 0.793, 0.793].

[0218] [0.085, 0.081, 0.192, 0.185, 0.148, 0.148, 0.097, 0.119, 0.086, 0.112, 0.060, 0.060, 0.239, 0.257, 0.179, 0.179, 0.161, 0.161, 0.082, 0.077, 0.064, 0.064].

[0219] [0.1080, 0.1010, 0.3009, 0.2898, 0.4226, 0.4226, 0.3456, 0.4519, 0.0971, 0.4494, 0.1102, 0.1102, 0.3460, 0.3402, 0.3770, 0.3753, 0.3957, 0.3957, 0.3794, 0.0689, 0.5331, 0.5331].

[0220] [0.5126, 0.4785, 0.6050, 0.6003, 0.5951, 0.5951, 0.6640, 0.6639, 0.4325, 0.6037, 0.2962, 0.2962, 0.6006, 0.6163, 0.5637, 0.5447, 0.5026, 0.5026, 0.3432, 0.2962, 0.5676, 0.5676].

[0221] [0.7, -0.4, -0.2, -0.2, 0.0, 0.0, -1.1, -1.1, -2.1, -2.1, -5.2, -5.2, 0.8, 0.8, -0.1, -0.1, -0.8, -0.8, -2.6, -2.6, -4.0, -4.0].

[0222] [3.764, 2.775, 8.021, 7.524, 1.892, 1.892, 2.729, 3.891, 2.799, 3.591, 0.488, 0.497, 6.217, 11.893, 5.203, 5.203, 8.754, 8.754, 4.236, 3.597, 0.821, 0.821].

[0223] Step 3.3.4: Calculate overall basal metabolic rate basal metabolism of the core layer in various local parts Basal metabolic rate of muscle layers in various local areas Basal metabolic rate of fat layer in various local areas Basic metabolism of skin layers in various local areas The calculation method is as follows:

[0224]

[0225]

[0226]

[0227]

[0228] in: Total basic heat generation, W.

[0229] , , , : These represent the basal metabolic heat production of the core layer, muscle layer, fat layer, and skin layer in each local area, in W.

[0230] , : These are the basal metabolic rate distribution coefficients for the core layer, muscle layer, fat layer, and skin layer of each local part defined in the model.

[0231] 。

[0232] [0.19551, 0.00324, 0.0957, 0.0957, 0.0856, 0.0856, 0.01435, 0.01435, 0.00409, 0.00409, 0.00106, 0.00106, 0.09096, 0.09096, 0.062, 0.062, 0.00623, 0.00623, 0.00211, 0.00211, 0.00125, 0.00125].

[0233] [0.00252, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.04804, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000].

[0234] [0.00127, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.0095, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000].

[0235] [0.00152, 0.00033, 0.000705, 0.000705, 0.000625, 0.000625, 0.00059, 0.00059, 0.00031, 0.00031, 0.00059, 0.00059, 0.001307, 0.001307, 0.000685, 0.000685, 0.0058, 0.0058, 0.00012, 0.00012, 0.00059, 0.00059].

[0236] Steady-state calculation results: 137.0069.

[0237] [26.7862, 0.4439, 13.1116, 13.1116, 11.7278, 11.7278, 1.9660, 1.9660, 0.5604, 0.5604, 0.1452, 0.1452, 12.4621, 12.4621, 8.4944, 8.4944, 0.8536, 0.8536, 0.2891, 0.2891, 0.1713, 0.1713].

[0238] [0.3453, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 6.5810, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000].

[0239] [0.1740, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.3016, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000].

[0240] [0.2083, 0.0452, 0.0966, 0.0966, 0.0856, 0.0856, 0.0808, 0.0808, 0.0425, 0.0425, 0.0425, 0.0425, 0.0808, 0.0808, 0.1791, 0.1791, 0.0938, 0.0938, 0.0795, 0.0795, 0.0164, 0.0164].

[0241] Step 3.3.5: Calculate the heat generated by tremors in each local area. Non-tremor heat production Heat generated by activity in various local parts Total heat generation of the core layer in each local part Total heat production in muscle layers at various local locations Total heat production of fat layers in various local areas Total heat production in the skin layers of various local areas The calculation method is as follows:

[0242]

[0243]

[0244]

[0245]

[0246]

[0247]

[0248] in: , , , : These represent the total heat production (in W) of the core layer, muscle layer, fat layer, and skin layer of each local area.

[0249] Heat generated by tremors in various local areas, W.

[0250] Non-tremor heat production in various local areas, W.

[0251] Heat generated by activity in various local parts, W.

[0252] The heat generation coefficient of each local part defined by the model.

[0253] : The non-tremor heat generation coefficient of each local part defined by the model.

[0254] The metabolic rate distribution coefficient of each local part of the model due to activity.

[0255] The intensity of activity input by the user.

[0256] .

[0257] [0.034, 0.044, 0.0915, 0.0915, 0.0805, 0.0805, 0.001, 0.001, 0.0005, 0.0005, 0.000, 0.000, 0.1513, 0.1513, 0.089, 0.089, 0.0016, 0.0016, 0.0010, 0.0010, 0.000, 0.000].

[0258] [0.000, 0.190, 0.095, 0.095, 0.000, 0.000, 0.215, 0.215, 0.000, 0.000, 0.000, 0.000, 0.095, 0.095, 0.095, 0.095, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000].

[0259] [0.0000, 0.0000, 0.0341, 0.0341, 0.0279, 0.0279, 0.01965, 0.01965, 0.0139, 0.0139, 0.0050, 0.0050, 0.0645, 0.0645, 0.030, 0.030, 0.2010, 0.2010, 0.0990, 0.0990, 0.0050, 0.0050].

[0260] Steady-state calculation results: [0.0134，0.0000，-0.0129，-0.0103，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000]。

[0261] [0.0000，0.0000，-0.0077，-0.0061，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000，-0.1816，-0.1130，-0.1130，0.0000，0.0000，0.0000，0.0000，0.0000，0.0000]。

[0262] [0.0000，0.0000，0.1802，0.1802，0.1318，0.1318，0.0161，0.0161，0.0031，0.0031，0.0012，0.0012，0.3394，0.3394，0.1029，0.1029，0.7720，0.7720，0.2930，0.2930，0.0034，0.0034]。

[0263] [26.7996，0.4439，13.2712，13.2754，11.8596，11.8596，1.9821，1.9821，0.5635，0.5635，0.1464，0.1464，12.8015，12.6199，8.4843，8.4843，1.6256，1.6256，0.5821，0.5821，0.1747，0.1747]。

[0264] [47.3219，0.0000，0.1673，0.1699，0.1318，0.1318，0.0161，0.0161，0.0031，0.0031，0.0012，0.0012，930.1061，0.3394，0.1029，0.1029，0.7720，0.7720，0.2930，0.2930，0.0034，0.0034]。

[0265] [0.1740, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.3016, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000].

[0266] [0.2083, 0.0452, 0.0966, 0.0966, 0.0856, 0.0856, 0.0808, 0.0808, 0.0425, 0.0425, 0.0425, 0.0425, 0.0808, 0.0808, 0.1791, 0.1791, 0.0938, 0.0938, 0.0795, 0.0795, 0.0164, 0.0164].

[0267] Step 3.3.6: Calculate the core layer blood flow in each local area. Muscle layer blood flow Blood flow in the fat layer Skin blood flow The calculation method is as follows:

[0268]

[0269]

[0270]

[0271] in: Blood flow in the core layer of each local area, in L / h.

[0272] Blood flow in the muscle layer at various local locations, in L / h.

[0273] Blood flow in the fat layer of various local areas, in L / h.

[0274] Blood flow in the skin layer at various local locations, in L / h.

[0275] The ratio of a user's baseline blood flow to the baseline blood flow of a standard human body.

[0276] : Vasodilator coefficients for each local area defined in the model.

[0277] : The vasoconstriction coefficient of each local part defined by the model.

[0278] Blood flow coefficient of the core layer in various local areas, L / h.

[0279] Blood flow in the muscle layer at various local locations, in L / h.

[0280] Blood flow in the fat layer of various local areas, in L / h.

[0281] Blood flow in the skin layer at various local locations, in L / h.

[0282] 。

[0283] [0.07, 0.099, 0.058, 0.058, 0.058, 0.058, 0.04, 0.04, 0.037, 0.037, 0.063, 0.063, 0.0355, 0.0355, 0.058, 0.058, 0.0368, 0.0368, 0.0206, 0.0206, 0.0312, 0.0312].

[0284] [0.022, 0.022, 0.064, 0.064, 0.063, 0.063, 0.021, 0.021, 0.021, 0.021, 0.149, 0.149, 0.032, 0.032, 0.068, 0.068, 0.0107, 0.0107, 0.0107, 0.0107, 0.0745, 0.0745].

[0285] [35.25, 15.24, 35.684, 35.684, 35.065, 35.065, 0.904, 0.904, 0.940, 0.940, 0.217, 0.217, 17.298, 17.298, 15.468, 15.468, 1.406, 1.406, 0.164, 0.164, 0.080, 0.080].

[0286] [0.682, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.614, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0287] [0.265, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.219, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0288] [1.75, 0.33, 1.574, 1.574, 0.59, 0.59, 0.91, 0.91, 0.508, 0.508, 1.114, 1.114, 0.878, 0.878, 0.602, 0.602, 1.456, 1.456, 0.326, 0.326, 0.472, 0.472].

[0289] Steady-state calculation results: [35.3038, 15.2583, 35.8707, 35.8729, 35.2204, 35.2204, 0.9189, 0.9189, 0.9438, 0.9438, 0.2183, 0.2183, 17.6106, 17.6106, 15.5750, 15.5750, 2.0715, 2.0715, 0.4161, 0.4161, 0.0830, 0.0830].

[0290] [0.6828, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 12.6291, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000].

[0291] [0.2653, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 2.2217, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000].

[0292] [1.7521, 0.3304, 1.5759, 1.5759, 0.5907, 0.5907, 0.9111, 0.9111, 0.5086, 0.5086, 1.1153, 1.1153, 0.8791, 0.8791, 0.6027, 0.6027, 1.4577, 1.4577, 0.3264, 0.3264, 0.4726, 0.4726].

[0293] Step 3.3.7: Calculate the blood flow of the arteriovenous anastomoses in the hand. Blood flow of arteriovenous anastomoses in the foot The calculation method is as follows:

[0294]

[0295] in: , Blood flow of arteriovenous anastomoses in the hand and foot, L / h.

[0296] Calculate arterial blood flow at various local sites Venous blood flow in various local areas The calculation method is as follows:

[0297]

[0298] in: Arterial blood flow at various local sites, in L / h.

[0299] Arterial blood flow at various local sites, in L / h.

[0300] Specifically, arterial blood flow in various local areas and arterial blood flow in various local areas The calculation is based on the sum of the baseline blood flow of the core, muscles, fat, and skin layers of various parts of the human body; the trunk uses the baseline blood flow; the bilateral upper limbs are calculated based on their own baseline blood flow, with the baseline blood flow of the distal limbs added step by step, and the blood flow of arteriovenous anastomoses uniformly superimposed. The abdominal and bilateral lower limb blood flow is based on the patient's own baseline blood flow, with the baseline blood flow of the distal limbs gradually added, and the blood flow of the arteriovenous anastomoses in the foot uniformly superimposed. Ultimately, this results in an arterial and venous blood flow distribution that conforms to the physiological circulation of the human body.

[0301] Steady-state calculation results: [38.0040, 53.5927, 37.4466, 37.4488, 35.8111, 35.8111, 6.3181, 6.3181, 4.4881, 4.4881, 3.0357, 3.0357, 47.1045, 18.4897, 16.1777, 16.1777, 6.8820, 6.8820, 3.3528, 3.3528, 2.6103, 2.6103].

[0302] [38.0040, 53.5927, 37.4466, 37.4488, 35.8111, 35.8111, 4.6160, 4.6160, 2.7860, 2.7860, 3.0357, 3.0357, 47.1045, 18.4897, 16.1777, 16.1777, 4.8273, 4.8273, 1.2981, 1.2981, 0.5556, 0.5556].

[0303] Step 3.3.8: Simulate body temperature changes based on the model parameter calculation results, and calculate the skin temperature of various local parts of the human body. .

[0304] Constructing a model of blood flow relationships in various local areas : According to the body node index sequence Based on the calculated blood flow parameters , , , , , This follows the blood flow from the local core layer to the muscle, fat, and skin layers, as well as the blood flow coupling between different tissue layers within the same area, and is based on the body node index sequence. The model is filled in to obtain a representation of the blood flow status in each local area.

[0305] Construct a model related to overall blood flow throughout the body Specifically, according to the body node index sequence Based on the calculated blood flow parameters , , , , , Following the logic and locational connections of the human body's blood circulation—from the core nodes of the blood supply system to all peripheral arteries, and from peripheral areas back to the core via veins—and according to the body's node index sequence, this system... By overlaying and filling, a complete model representing the overall blood flow status of the human body is obtained.

[0306] Constructing a whole-body cross-site heat transfer coefficient matrix Specifically, according to the body node index sequence The thermal conductivity matrix across different body tissue levels is obtained by indexing and filling based on the defined thermal conductivity coefficients between different body tissue levels. The unit is W / K; further, according to the step body node index sequence With the defined creation of the whole body heat capacity node matrix model The unit is W / K; specifically, the heat capacity node matrix model According to the defined heat capacity of different body tissue levels, the body node index sequence is used. Perform index population.

[0307] [0.909, 0.909, 1.785, 1.785, 1.643, 1.643, 1.501, 1.501, 0.982, 0.982, 2.183, 2.183, 1.576, 0.613, 1.947, 1.947, 1.234, 1.234, 0.663, 0.663, 1.685, 1.685].

[0308] [1.601, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.081, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0309] [13.222, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 10.374, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0310] [16.008，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0，41.495，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0，0.0]。

[0311] [0，0，0，0，0，0，0.586，0.586，0.383，0.383，1.534，1.534，0，0，0，0，0.405，0.405，0.217，0.217，0.908，0.908]。

[0312] [0，0，0，0，0，0，57.735，57.735，37.768，37.768，16.634，16.634，0，0，0，0，56.006，56.006，27.392，27.392，12.138，12.138]。

[0313] [0，0，0，0，0，0，0.537，0.537，0.351，0.351，0.762，0.762，0，0，0，0，0.413，0.413，0.222，0.222，0.496，0.496]。

[0314] 。

[0315] [0.346，0.090，0.173，0.173，0.16，0.16，0.067，0.067，0.033，0.033，0.016，0.016，0.658，0.216，0.2305，0.2305，0.147，0.147，0.072，0.072，0.019，0.019]。

[0316] [1.156，0.306，0.61，0.61，0.5615，0.5615，0.166，0.166，0.086，0.086，0.036，0.036，2.105，1.017，0.74，0.74，0.372，0.372，0.18，0.18，0.043，0.043]。

[0317] [0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.09, 0.09, 0.054, 0.054, 0.04, 0.04, 0.0001, 0.0001, 0.0001, 0.0001, 0.133, 0.133, 0.09, 0.09, 0.038, 0.038].

[0318] [6.202, 2.030, 13.66, 13.66, 12.46, 12.46, 6.116, 6.116, 4.036, 4.036, 0.554, 0.554, 40.125, 11.253, 10.67, 10.67, 8.495, 8.495, 5.16, 5.16, 0.378, 0.378].

[0319] [0.305, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 7.409, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0320] [0.203, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.947, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0].

[0321] [0.679, 0.209, 0.59, 0.59, 0.538, 0.538, 0.454, 0.454, 0.302, 0.302, 0.317, 0.317, 1.284, 0.908, 0.443, 0.443, 0.534, 0.534, 0.304, 0.304, 0.292, 0.292].

[0322] Establish a state matrix to represent the blood flow heat exchange between all nodes in the human body. This is used to characterize the heat flux rate of blood flow transfer between human nodes. First, by superimposing the blood flow relationship node models of each local part... The model related to the overall blood flow of the whole body This yields an initial matrix, where the physical meaning of each matrix element is the inter-node blood flow heat flux coefficient, expressed in W / K. Then, each row of the matrix is ​​divided by the heat capacity of the corresponding node. Converting the units from W / K to K / s yields the temperature change rate coefficient; finally, multiplying by the time step transforms the continuous differential equation into a discrete iterative form, resulting in a dimensionless coefficient matrix. .

[0323] Establish a state matrix for describing the heat conduction between nodes. This is used to characterize the heat exchange coefficient generated by conduction through tissues at various thermal nodes in the human body. Firstly, it is achieved by superimposing the thermal conductivity coefficients across different parts of the body. This yields the initial thermal conductivity matrix, where the matrix elements are heat flux coefficients in W / K. Then, each row of the matrix is ​​divided by the heat capacity of the corresponding node. The units are converted from W / K to K / s; finally, by multiplying by the time step, the continuous differential equation is transformed into a discrete iterative form, yielding a dimensionless thermal conductivity matrix. .

[0324] Establish a matrix to represent the sensible heat exchange coefficient between the skin and the external environment. It only applies to skin thermal nodes across the entire body. Specifically, it performs assignment operations only on all skin thermal nodes defined in the model, superimposing values ​​based on local body surface area. Divide by dry heat resistance The calculation results yielded the heat flow rate coefficient for heat exchange between the skin and the environment, in W / K; then, the matrix was divided by the heat capacity of the corresponding node. The units are converted from W / K to K / s; finally, by multiplying by the time step, the continuous differential equation is converted into a discrete iterative form, resulting in a dimensionless matrix of heat transfer coefficients between the skin and the environment.

[0325] Establish a matrix to characterize the total heat transfer coupling relationship between all thermal nodes in the human body model. Specifically, firstly, the heat conduction state matrix between the nodes is... and the inter-node blood flow heat exchange state matrix Summing and taking the negative yields a non-diagonal matrix representing the internal thermal coupling between nodes. Then, the internal heat transfer coefficients are summed row-wise to obtain the total heat exchange of each node, and this is superimposed on the sensible heat exchange coefficient matrix between the skin and the external environment. The matrix is ​​then converted to a diagonal matrix, and then superimposed with an identity matrix to complete the numerical discretization, resulting in a diagonal matrix. Finally, the off-diagonal heat transfer terms and diagonal heat exchange terms are integrated into the complete matrix representing the total heat transfer coupling relationship matrix between all thermal nodes in the human body model. This allows for iterative solutions to the transient temperatures of various thermal nodes in the human body.

[0326] Establish a matrix of net heat changes at all nodes of the human body. Specifically, according to the body node index sequence The core layer is filled sequentially with the total heat generated. Total heat production in muscle layers at various local locations Total heat production of fat layers in various local areas Total heat production in the skin layers of various local areas Subtract the sensible heat loss from respiration at the core nodes of the chest. Respiratory latent heat loss Heat loss through sweat evaporation at points on the skin. Finally, by dividing by the corresponding heat capacity of each node... Then multiply by the time step to complete the unit conversion, and obtain the net temperature change matrix of each thermal node within a unit time step. The unit is K / s.

[0327] Establish a temperature reference matrix for heat exchange between the skin and the external environment at various local sites. Specifically, the operating temperature Index sequence by body node Fill the skin node operation temperature boundary condition model Based on the elements corresponding to the skin area, a boundary model with a specific temperature value is constructed on the skin area to provide a temperature reference for heat exchange between the skin and the external environment, with the unit being °C.

[0328] Update the temperature model of each node in the human body The calculation method is as follows:

[0329] Specifically, the current temperature of each node in the body The model and the sensible heat exchange coefficient matrix between the skin and the external environment Temperature reference matrix for heat exchange between skin and external environment in various local areas Net heat change matrix of all nodes in the human body Integrate.

[0330] The inverse matrix of the total heat transfer coupling relationship between all thermal nodes of the human body model. Perform matrix multiplication to calculate the latest temperature of all thermal nodes in the body after one time step. Use the latest temperature... Overwrite the original temperature value to complete a dynamic update of human body temperature, simulating the thermal response process of the human body over time. The calculation process comprehensively considers the temperature state between various nodes of the human body, the heat transfer of the skin, and the heat generation and dissipation of various parts of the body.

[0331] Step 3.3.9: Determine the skin temperature of different parts of the body If the degree of change is less than 0.5 degrees Celsius, return to step 3.3.1 to continue iterating; if it is, proceed to step 3.4.

[0332] Extraction results: [31.9, 31.3, 34.4, 34.3, 32.8, 32.8, 31.9, 32.4, 31.7, 32.2, 29.1, 29.3, 34.7, 35.8, 34.0, 34.0, 33.5, 33.5, 31.5, 31.0, 29.5, 29.4].

[0333] As a preferred embodiment: Step 3.5: Calculate the skin temperature from the model based on the measured skin temperature. The correction was made, and the calculation process is as follows: The measured average temperature of each body part calculated according to step 3.2.2 According to the body node index sequence Extract the average temperature of the actual forehead skin surface using thermal imaging. The actual average temperature of the skin surface of the left hand in thermal imaging. The actual average temperature of the skin surface of the right hand in thermal imaging. .

[0334] Extraction results: , , .

[0335] According to the body node index sequence Extracting forehead skin temperature calculated by the model Left hand skin temperature Right hand skin temperature .

[0336] Extraction results: , , .

[0337] The error between the calculated results of the skin temperature model for the forehead, left hand, and right hand and the actual average thermal imaging temperature of the skin surface was calculated. , , The calculation method is as follows:

[0338]

[0339]

[0340] , , .

[0341] The calculated results of the forehead skin temperature model are consistent with the actual average thermal imaging temperature of the forehead skin surface. Used to correct the skin temperature calculation results for the forehead, neck, left chest, right chest, left shoulder, right shoulder, waist, abdomen, left back, and right back in the model output. The correction method is as follows:

[0342] in: : The set of parts corresponding to head error correction; ={1, 2, 3, 4, 5, 6, 13, 14, 15, 16}.

[0343] The head error given by the model for the first... u Correction factors for each part.

[0344] [1.0, 0.9, 0.8, 0.8, 0.7, 0.7, 0.5, 0.5, 0.4, 0.4].

[0345] Calculation results: [31.50, 30.94, 32.48, 32.48, 34.12, 34.02, 33.80, 33.80, 34.54, 35.64].

[0346] The error between the calculated left-hand skin temperature model and the actual average thermal imaging temperature of the left-hand skin surface. The following correction method is used to correct the calculated skin temperature of the left upper arm, left forearm, left hand, left thigh, left calf, and left foot in the model:

[0347] in: : The set of parts corresponding to left-hand error correction; ={7, 9, 11, 17, 19, 21}.

[0348] The left-hand error given by the model for the first... u Correction factors for each part.

[0349] [0.9, 0.8, 1.0, 0.5, 0.4, 0.3].

[0350] Calculation results: [32.42, 32.54, 29.90, 33.90, 31.82, 29.74].

[0351] The error between the calculated right-hand skin temperature model and the actual average thermal imaging temperature of the right-hand skin surface. The following correction method is used to correct the skin temperature calculation results for the right upper arm, right forearm, right hand, right thigh, left calf, right calf, and right foot in the model:

[0352] in: The set of parts corresponding to right-hand error correction.

[0353] The right-handed error given by the model for the first... w Correction factors for each part.

[0354] [0.9, 0.8, 1.0, 0.5, 0.4, 0.3].

[0355] Calculation results: [32.83, 32.96, 30.00, 33.85, 31.28, 29.61].

[0356] As a preferred embodiment: The calculation method for step 3.6 is as follows:

[0357] in: Reference neutral skin temperature for various local areas.

[0358] : Local deviation weighting coefficients for each local part.

[0359] [31.50, 30.94, 34.12, 34.02, 32.48, 32.48, 32.54, 32.96, 32.42, 32.83, 29.90, 30.00, 34.54, 35.64, 33.80, 33.80, 33.90, 33.85, 31.82, 31.28, 29.74, 29.61].

[0360] [32.00, 31.80, 34.20, 34.20, 33.00, 33.00, 32.80, 32.80, 32.50, 32.50, 30.50, 30.50, 34.50, 35.50, 34.00, 34.00, 33.60, 33.60, 32.00, 32.00, 30.20, 30.20].

[0361] [1.50, 1.40, 1.05, 1.05, 0.75, 0.75, 0.70, 0.70, 0.90, 0.90, 0.85, 0.85, 1.00, 1.15, 0.85, 0.85, 0.50, 0.50, 0.50, 0.50, 0.85, 0.85].

[0362] Calculation results: [-0.750, -1.204, -0.084, -0.189, -0.390, -0.390, -0.182, 0.112, -0.072, 0.297, -0.510, -0.425, 0.040, 0.161, -0.170, -0.170, 0.150, 0.125, -0.009, -0.360, -0.391, -0.502].

[0363] As a preferred embodiment: Step 3.7: Calculate the overall thermal sensation The calculation method is as follows:

[0364] in: : No. i A localized area feels hot.

[0365] : No. l A localized area feels hot.

[0366] : No. i The region and the first l The magnitude of local thermal sensation differences between regions.

[0367] : The set of paired local regions that need to be compared .

[0368] : No. i Weighting coefficients for local regions of an individual's body.

[0369] : Correction coefficient for local thermal sensation difference.

[0370] Local region difference weighting coefficient.

[0371] [0.120, 0.080, 0.055, 0.055, 0.028, 0.028, 0.028, 0.050, 0.022, 0.045, 0.045, 0.050, 0.065, 0.050, 0.050, 0.032, 0.032, 0.022, 0.048, 0.030, 0.030].

[0372] 0.30 ， 0.00433.

[0373] Calculation results: -0.2231.

[0374] The overall thermal sensation It depends not only on the thermal sensation of each part The average level also depends on whether there is significant unevenness between different parts. The local part region pairing set This involves selecting two local regions from all local areas of the human body to form a pair, used to describe the difference in thermal sensation or skin temperature between the two locations. Specifically, the overall thermal sensation prediction result is obtained by weighted fusion of the local thermal sensation prediction results of each local area of ​​the human body, and corrected by incorporating the degree of difference in local thermal sensation; wherein, the weighting coefficient is determined based on the area and thermal sensitivity of the local area of ​​the human body, and the difference correction coefficient is determined based on the degree of influence of the difference in thermal sensation of different local areas on the overall thermal sensation.

[0375] As a preferred embodiment: Step 3.8: Calculate the user's subjective thermal sensation. Human thermal sensation calculated by the model The difference The calculation method is as follows:

[0376] in: The difference between the subjective thermal sensation input by the user and the thermal sensation of the human body calculated by the model.

[0377] The overall thermal sensation obtained from model calculations.

[0378] The subjective thermal sensation input by the user during the system initialization phase is used to correct the overall thermal sensation calculated by the subsequent model. -0.3.

[0379] Calculation results: -0.0769.

[0380] Step 3.9: Based on the difference in human thermal sensation Correcting the human thermal sensation calculated by subsequent models To obtain the final human thermal sensation The correction method is as follows:

[0381] in: The final output of the non-uniform clothing human thermal regulation model is the human thermal sensation.

[0382] Thermal sensation correction factor; .

[0383] Calculation results: -0.278.

[0384] Step 3.10: According to Calculate the most comfortable desired indoor temperature The calculation method is as follows:

[0385] in: : The most comfortable indoor temperature under the current asymmetrical clothing condition, in °C.

[0386] , Based on ambient temperature User subjective heat perception voting data The fitted regression coefficients are related as follows:

[0387] The calculation yielded: 0.1 ， -2.1 ， twenty one 。

[0388] Step 4: The intelligent control terminal calculates the current indoor temperature. and desired temperature The difference .

[0389] The calculation method is as follows:

[0390] in: Current indoor temperature and desired temperature The difference , ℃.

[0391] : The current indoor space temperature obtained by the information collection device, in °C.

[0392] : The most comfortable indoor temperature for the user under the current conditions, calculated and output by the non-uniform clothing human thermal regulation model, in °C.

[0393] Calculation results: .

[0394] Step 5: When At that time, the intelligent control terminal sends a temperature adjustment command to the air conditioning ventilation system, which then adjusts the indoor ambient temperature to the specified level according to the command. .

[0395] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions conceived by those skilled in the art within the scope of the technology disclosed in the present invention without creative effort are covered within the scope of protection of the present invention.

Claims

1. A human body thermal regulation system under non-uniform clothing conditions, characterized in that, Includes user interaction devices, information collection devices, intelligent control terminals, and air conditioning supply execution systems; The information acquisition device includes an infrared thermal imager, a miniature weather instrument, and a black sphere temperature sensor arranged in the room. The air conditioning supply system is an air conditioning system installed in an indoor space.

2. The human body thermal regulation system under non-uniform clothing conditions as described in claim 1, characterized in that, The infrared thermal imager is used to monitor the user's body temperature; The aforementioned miniature weather instrument is used to monitor indoor air temperature, relative humidity, air velocity, and atmospheric pressure; The aforementioned black sphere temperature sensor is used to monitor indoor radiant temperature; The user interaction device is used to collect the user's physical characteristics and subjective feelings. The intelligent control terminal runs a non-uniform clothing human body thermal regulation model; The information acquisition device and the user interaction device will send the acquired information to the intelligent control terminal. The intelligent control terminal inputs the acquired information into the non-uniform clothing human thermal regulation model, which is used to calculate and output the user's thermal comfort evaluation results and indoor comfort temperature. The intelligent control terminal sends the calculated indoor comfort temperature adjustment command to the air conditioning air supply execution system to adjust the indoor air supply temperature.

3. A method for human body thermal regulation under non-uniform clothing conditions, characterized in that, The process, employing the human body thermal regulation system under non-uniform clothing conditions as described in claim 1 or 2, includes the following steps: Step 1: The user inputs their height into the smart control terminal via the user interaction device. ,weight ,age Body fat percentage Subjective thermal sensation Activity intensity ; Step 2: The information acquisition device collects thermal imaging temperature data of the user's body with non-uniform clothing. Body size coordinate data Indoor air temperature Indoor relative humidity Indoor radiant temperature Indoor air velocity Indoor atmospheric pressure ; Step 3: The intelligent control terminal uses a non-uniform clothing human body thermal regulation model to calculate the most comfortable desired indoor temperature for the user in their current clothing state. ; Step 4: The intelligent control terminal calculates the current indoor temperature. and desired temperature The difference ; Step 5: When At that time, the intelligent control terminal sends a temperature adjustment command to the air conditioning ventilation system, which then adjusts the indoor ambient temperature to the specified level according to the command. .

4. The method as described in claim 3, characterized in that, Step 3 includes: Step 3.1: The non-uniform clothing human body thermoregulation model divides the human body into: Central Node: Central Blood Pool; Body parts: head, neck, left chest, right chest, left shoulder, right shoulder, left upper arm, right upper arm, left forearm, right forearm, left hand, right hand, waist, abdomen, left back, right back, left thigh, right thigh, left calf, right calf, left foot, right foot; The body is divided into tissue layers: arteries, veins, superficial veins, core, muscles, fat, and skin; The central blood pool is divided into body node 1, and then node numbers are assigned sequentially according to the "body locality - tissue level" method, defining the body node index sequence as follows: ; definition ; indicates the number of body parts divided in the model; definition Represents the total number of human body nodes in the model; Definition , Represents the set of parts corresponding to head error correction; definition , Represents the set of parts corresponding to left-hand error correction; definition , This represents the set of parts corresponding to right-hand error correction; Step 3.2: Calculate the required parameters, including environmental parameters, user clothing parameters, and human body parameters; Step 3.3: The non-uniform clothing human thermal regulation model begins iteration. Calculate the skin temperature of various parts of the human body. ; Step 3.4: Based on the temperature model of various nodes in the human body According to the body node index sequence Extracting skin temperature from various local areas ; Step 3.5: Calculate the skin temperature from the model based on the measured skin temperature. Make corrections; Step 3.6: Calculate the thermal sensation of each local area based on the corrected skin temperature. ; Step 3.7: Calculate the overall thermal sensation ; Step 3.8: Calculate the user's subjective thermal sensation. Human thermal sensation calculated by the model The difference ; Step 3.9: Based on the difference in human thermal sensation Correcting the human thermal sensation calculated by subsequent models To obtain the final human thermal sensation ; Step 3.10: Based on the final human thermal sensation Calculate the most comfortable desired indoor temperature .

5. The method as described in claim 4, characterized in that, In step 3.2, the environmental parameters include: the convective heat transfer coefficient of each local part. Radiative heat transfer coefficient of each local part Evaporative heat transfer coefficient of each local part and the operating temperature of each local part ; The user clothing parameters include: the non-uniform clothing thermal conditioning model will input the non-uniform clothing thermal imaging temperature distribution data of the human body. and body coordinate data According to the above The body parts are divided into: Local parts i Thermal imaging temperature data ; Local parts i Clothing size data ; The human body parameters mentioned include the ratio of the user's total body surface area to that of a standard human body. Surface area of ​​each local part The ratio of the user's input weight to the standard human body weight The ratio of the user's baseline blood flow to the baseline blood flow of a standard human body .

6. The method as described in claim 4, characterized in that, Step 3.3 specifically includes: Step 3.3.1: According to the body node index sequence Temperature models at various points in the human body Extracting core temperatures from various parts of the human body using a central index and skin temperature in different parts of the body ; Step 3.3.2: Calculate the thermal signals of each local area. With cold sensation signals ; Step 3.3.3: Calculate the saturated vapor pressure of the indoor environment. Vapor pressure of skin in various local areas Skin saturated vapor pressure in various local areas ; Step 3.3.4: Calculate overall basal metabolic rate basal metabolism of the core layer in various local parts Basal metabolic rate of muscle layers in various local areas Basal metabolic rate of fat layer in various local areas Basic metabolism of skin layers in various local areas ; Step 3.3.5: Calculate the heat generated by tremors in each local area. Non-tremor heat production Heat generated by activity in various local parts Total heat generation of the core layer in each local part Total heat production in muscle layers at various local locations Total heat production of fat layers in various local areas Total heat production in the skin layers of various local areas ; Step 3.3.6: Calculate the core layer blood flow in each local area. Muscle layer blood flow Blood flow in the fat layer Skin blood flow ; Step 3.3.7: Calculate the blood flow of the arteriovenous anastomoses in the hand. Blood flow of arteriovenous anastomoses in the foot ; Step 3.3.8: Simulate body temperature changes based on the model parameter calculation results, and calculate the skin temperature of various local parts of the human body. ; Step 3.3.9: Determine the skin temperature of different parts of the body If the degree of change is less than 0.5 degrees Celsius, return to step 3.3.1 to continue iterating; if it is, proceed to step 3.

4.

7. The method as described in claim 4, characterized in that, Step 3.5: Calculate the skin temperature from the model based on the measured skin temperature. The correction was made, and the calculation process is as follows: The average thermal imaging temperature of the surface of each body part calculated according to step 3.2 According to the body node index sequence Extract the average temperature of the actual forehead skin surface using thermal imaging. The actual average temperature of the skin surface of the left hand in thermal imaging. The actual average temperature of the skin surface of the right hand in thermal imaging. ; According to the body node index sequence Extracting forehead skin temperature calculated by the model Left hand skin temperature Right hand skin temperature ; Error between the model calculation results for forehead, left hand, and right hand skin temperature and the actual average thermal imaging temperature of the forehead skin surface. , , ; The error between the calculated forehead skin temperature model and the actual average thermal imaging temperature of the forehead skin surface. Used to correct the skin temperature calculation results for the forehead, neck, left chest, right chest, left shoulder, right shoulder, waist, abdomen, left back, and right back in the model output. ; The error between the calculated left-hand skin temperature model and the actual average thermal imaging temperature of the left-hand skin surface. The calculated skin temperature results for the left upper arm, left forearm, left hand, left thigh, left calf, and left foot were used to correct the model. The error between the calculated right-hand skin temperature model and the actual average thermal imaging temperature of the right-hand skin surface. The calculated skin temperature results for the right upper arm, right forearm, right hand, right thigh, left calf, right calf, and right foot were used to correct the model.

8. The method as described in claim 4, characterized in that, The calculation method for step 3.6 is as follows: in: Reference neutral skin temperature for various local areas; : Local deviation weighting coefficients for each local part.

9. The method as described in claim 4, characterized in that, Step 3.7: Calculate the overall thermal sensation The calculation method is as follows: in: Location i Localized thermal sensation; : No. l A localized area of ​​heat sensation; : No. i The region and the first l The magnitude of local thermal sensation differences between regions; : A set of paired local regions that need to be compared; : No. i Weighting coefficients for local regions of an individual's body; : Correction coefficient for local thermal sensation differences; Local region difference weighting coefficient.

10. The method as described in claim 4, characterized in that, Step 3.8: Calculate the user's subjective thermal sensation. Human thermal sensation calculated by the model The difference The calculation method is as follows: in: The difference between the subjective thermal sensation input by the user and the human thermal sensation calculated by the model; The overall thermal sensation obtained from model calculations; The subjective thermal sensation input by the user during the system initialization phase is used to correct the overall thermal sensation calculated by the subsequent model. Step 3.9: Based on the difference in human thermal sensation Correcting the human thermal sensation calculated by subsequent models The correction method is as follows: in: The final output of the non-uniform clothing human thermal regulation model is the human thermal sensation. Thermal sensation correction factor; Step 3.10: Based on the final human thermal sensation Calculate the most comfortable desired indoor temperature The calculation method is as follows: in: The most comfortable desired indoor temperature under the current asymmetrical clothing condition, in °C; , Based on ambient temperature User subjective heat perception voting data The fitted regression coefficients are related as follows: 。

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