Methods, apparatus, and storage media for determining user thermal comfort

Abstract

This application relates to the field of thermal comfort monitoring technology, and discloses a method for determining user thermal comfort, including: determining the user's metabolic rate and clothing surface coefficient during sleep; inputting the user's metabolic rate and clothing surface coefficient during sleep into an SPMV model to obtain a comfort value output by the SPMV model; and determining the user's thermal comfort state information to characterize the user's feelings based on the comfort value. This method can accurately determine the user's thermal comfort experience during nighttime sleep through the SPMV model, providing an accurate data basis for air conditioner control during sleep and meeting the user's thermal comfort needs. This application also discloses a device and storage medium for determining user thermal comfort.

Description

Technical Field

[0001] This application relates to the field of thermal comfort monitoring technology, such as a method, apparatus, and storage medium for determining a user's thermal comfort. Background Technology

[0002] As people's living standards continue to improve, smart home appliances are gradually becoming a part of users' lives. Currently, with users' increasing demand for thermal comfort in their environment, air conditioners have become an indispensable smart home appliance for every family.

[0003] Currently, to meet the diverse thermal comfort needs of users, air conditioners typically pre-store a PMV (Predicted Mean Vote) model. This model outputs a thermal comfort value by inputting environmental parameters and the user's vital signs during wakefulness, thus determining the user's current thermal comfort level. However, existing PMV models are based on the user's vital signs during the daytime awakening state, and therefore cannot accurately reflect the user's thermal comfort during sleep at night.

[0004] Therefore, accurately determining a user's thermal comfort level during sleep at night has become a pressing technical problem that needs to be solved. Summary of the Invention

[0005] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0006] This disclosure provides a method, apparatus, and storage medium for determining a user's thermal comfort, thereby providing a method that can accurately obtain a user's thermal comfort experience during nighttime sleep.

[0007] In some embodiments, the method for determining user thermal comfort includes: determining the user's metabolic rate and the surface coefficient of clothing during sleep; inputting the user's metabolic rate and the surface coefficient of clothing during sleep into an SPMV model to obtain a comfort value output by the SPMV model; and determining user thermal comfort state information to characterize the user's feelings based on the comfort value.

[0008] In some embodiments, the device for determining user thermal comfort includes: a first determining module configured to determine the user's metabolic rate and the surface coefficient of clothing during sleep; an input module configured to input the user's metabolic rate and the surface coefficient of clothing during sleep into an SPMV model to obtain a comfort value output by the SPMV model; and a second determining module configured to determine thermal comfort state information of the user to characterize the user's feelings based on the comfort value.

[0009] In some embodiments, the apparatus for determining user thermal comfort includes a processor and a memory storing program instructions, the processor being configured to execute the aforementioned method for determining user thermal comfort when the program instructions are executed.

[0010] In some embodiments, the storage medium includes: storing program instructions that, when executed, perform the aforementioned method for determining user thermal comfort.

[0011] The method, apparatus, and storage medium for determining user thermal comfort provided in this disclosure can achieve the following technical effects: By determining the user's metabolic rate and clothing surface coefficient during sleep; inputting the user's metabolic rate and clothing surface coefficient during sleep into an SPMV model to obtain a comfort value output by the SPMV model; and determining the user's thermal comfort state information to characterize the user's experience based on the comfort value. This solution can accurately determine the user's thermal comfort experience during nighttime sleep through the SPMV model, providing an accurate data basis for air conditioner control during sleep and meeting the user's thermal comfort needs.

[0012] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0013] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0014] Figure 1 This is a schematic diagram of a method for determining user thermal comfort provided in an embodiment of this disclosure;

[0015] Figure 2 This is a schematic diagram of a method for determining a user's thermal comfort state information provided in an embodiment of this disclosure;

[0016] Figure 3 This is a schematic diagram of a method for determining the metabolic rate of a user during sleep, provided in an embodiment of this disclosure.

[0017] Figure 4 This is a schematic diagram of a method for determining user thermal comfort provided in an embodiment of this disclosure;

[0018] Figure 5 This is a schematic diagram of a device for determining user thermal comfort according to an embodiment of this disclosure;

[0019] Figure 6 This is a schematic diagram of a device for determining a user's thermal comfort, provided in an embodiment of this disclosure. Detailed Implementation

[0020] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0021] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0022] Unless otherwise stated, the term "multiple" means two or more.

[0023] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0024] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0025] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0026] In this embodiment of the disclosure, smart home appliances refer to home appliances formed by introducing microprocessors, sensor technology and network communication technology into home appliances. They have the characteristics of intelligent control, intelligent sensing and intelligent application. The operation of smart home appliances often relies on the application and processing of modern technologies such as the Internet of Things, the Internet and electronic chips. For example, smart home appliances can be connected to electronic devices to enable users to remotely control and manage smart home appliances.

[0027] In this embodiment of the disclosure, the terminal device refers to an electronic device with wireless connectivity. The terminal device can communicate with the aforementioned smart home appliances by connecting to the internet, or directly via Bluetooth, Wi-Fi, or other methods. In some embodiments, the terminal device may be, for example, a mobile device, a computer, or an in-vehicle device built into a hovercraft, or any combination thereof. Mobile devices may include, for example, mobile phones, smart home devices, wearable devices, smart mobile devices, virtual reality devices, or any combination thereof. Wearable devices may include, for example, smartwatches, smart bracelets, pedometers, etc.

[0028] Figure 1 This is a schematic diagram of a method for determining user thermal comfort provided in an embodiment of this disclosure; combined with Figure 1 As shown in the embodiments of this disclosure, a method for determining a user's thermal comfort is provided, comprising:

[0029] S11, the air conditioner determines the user's metabolic rate and the surface coefficient of the bedding during sleep.

[0030] S12, the air conditioner inputs the user's metabolic rate and the surface coefficient of the bedding during sleep into the SPMV model to obtain the comfort value output by the SPMV model.

[0031] S13, the air conditioner determines the thermal comfort status information of the user to characterize the user's feelings based on the comfort value.

[0032] In this solution, it is understood that the metabolic rate of a user during sleep differs from that during wakefulness. Therefore, the air conditioner can determine the metabolic rate during sleep by obtaining the user's average basal metabolic rate during wakefulness before entering sleep, the percentage decrease in average heart rate during each sleep stage compared to the wakefulness stage before entering sleep, and a second correction factor used to refine the metabolic rate model. Furthermore, the air conditioner can determine the surface coefficient of clothing by obtaining its thermal resistance. Here, the thermal resistance of clothing varies across different seasons, and correspondingly, the heat dissipation area of ​​the clothing also varies.

[0033] Furthermore, after the air conditioner determines the user's metabolic rate and bedding surface coefficient during sleep, it inputs these parameters into the SPMV model to obtain the comfort value output by the SPMV model. Specifically, the SPMV model includes:

[0034]

[0035] Among them, M and I cl Let W represent the metabolic rate, thermal resistance of the clothing, and external mechanical work, respectively, with the external mechanical work being 0. a v, H, and tr represent ambient temperature, wind speed, relative humidity, and mean radiant temperature, respectively, and the mean radiant temperature tr is related to the ambient temperature t. a The values ​​are equal. P a f cl h c t cl These represent the partial pressure of water vapor, the surface coefficient of the clothing, the convective heat transfer coefficient, and the outer surface temperature of the clothing, respectively.

[0036] The SPMV model described above comprehensively considers human body parameters, environmental factors, and other related factors, enabling a more accurate construction of a thermal comfort model associated with user sleep. Compared to the PMV model used in related technologies, it more accurately reflects the actual comfort level of users during sleep. Human body parameters include metabolic rate, clothing thermal resistance, and external mechanical work. Environmental factors include ambient temperature, wind speed, relative humidity, and mean radiant temperature. Other related factors include water vapor partial pressure, clothing surface coefficient, convective heat transfer coefficient, and clothing outer surface temperature.

[0037] Furthermore, given the comfort values ​​output by the SPMV model, the air conditioner can combine these comfort values ​​to determine the user's thermal comfort state information, which characterizes the user's current sensation. Here, the user's thermal comfort state information can include: relatively hot, slightly hot but comfortable, comfortable, slightly cold but comfortable, and relatively cold.

[0038] The method for determining user thermal comfort provided in this disclosure involves determining the user's metabolic rate and the surface coefficient of clothing during sleep; inputting these parameters into an SPMV model to obtain a comfort value output by the SPMV model; and determining the user's thermal comfort state information to characterize the user's experience based on the comfort value. This approach allows for accurate determination of a user's thermal comfort experience during nighttime sleep through the SPMV model, providing a reliable data foundation for controlling the air conditioner while the user is asleep, thus meeting the user's thermal comfort needs.

[0039] Figure 2This is a schematic diagram of a method for determining a user's thermal comfort state information provided in an embodiment of this disclosure; combined with Figure 2 As shown, optionally, in step S13, the air conditioner determines thermal comfort state information of the user to characterize the user's feelings based on the comfort value, including:

[0040] S21, the air conditioner obtains the thermal comfort information database, which stores thermal comfort state information corresponding to different comfort ranges.

[0041] S22, the air conditioner determines the target comfort range to which the comfort value belongs.

[0042] S23, the air conditioner uses the thermal comfort state information matched from the thermal comfort information database that corresponds to the target comfort range as the user's thermal comfort state information.

[0043] In this solution, the air conditioner can obtain a thermal comfort information database. This database stores thermal comfort state information corresponding to different comfort ranges. For example: if the comfort range is [1.5, 2.5], the corresponding thermal comfort state information is "relatively hot"; if the comfort range is [0.5, 1.5], the corresponding thermal comfort state information is "slightly hot but comfortable"; if the comfort range is [-0.5, 0.5], the corresponding thermal comfort state information is "comfortable"; if the comfort range is [-1.5, -0.5], the corresponding thermal comfort state information is "slightly cold but comfortable"; if the comfort range is [-2.5, -1.5], the corresponding thermal comfort state information is "relatively cold". Furthermore, after obtaining the comfort value output by the SPMV model, the air conditioner can determine the target comfort range to which the comfort value belongs. For example, if the comfort value output by the SPMV model is 0.3, then the target comfort range to which the comfort value belongs is [-0.5, 0.5]. Furthermore, the air conditioner can use the thermal comfort state information matched from the thermal comfort information database that corresponds to the target comfort range as the user's thermal comfort state information. With this approach, the user's thermal comfort experience during nighttime sleep can be accurately determined through the comfort values ​​output by the SPMV model, providing a precise data foundation for the air conditioner's environmental control process.

[0044] Figure 3 This is a schematic diagram of a method for determining a user's metabolic rate during sleep, provided in an embodiment of this disclosure; combined with Figure 3 As shown, optionally, in step S11, the air conditioner determines the user's metabolic rate during sleep, including:

[0045] S31, the air conditioner obtains the user's average basal metabolic rate during the waking period before entering the sleep stage, the user's average heart rate during each sleep stage and the percentage decrease during the waking period before entering the sleep stage, and a second correction amount used to correct the metabolic rate model.

[0046] S32, the air conditioner determines the human metabolic rate during sleep based on the average basal metabolic rate of the user during the waking period before entering the sleep stage, the user's average heart rate during each sleep stage and the percentage decrease during the waking period before entering the sleep stage, and a second correction amount used to correct the metabolic rate model.

[0047] In this embodiment, the average basal metabolic rate of the user during the waking period before entering sleep can be 40 W / m². 2 Furthermore, the percentage decrease in average heart rate during each sleep stage compared to the percentage decrease during wakefulness before entering sleep can be obtained through various methods:

[0048] In the first method, when the current indoor temperature is the preset temperature, the air conditioner can obtain the user's gender information, the user's current sleep cycle information, and the user's sleep stage information within the sleep cycle; thus, the air conditioner can use the decrease ratio corresponding to the user's gender information, the user's current sleep cycle information, and the user's sleep stage information within the sleep cycle as the decrease ratio of the user's average heart rate in each sleep stage to the wakefulness period before entering the sleep stage, according to the preset correspondence.

[0049] In the second method, at an ambient temperature of 26℃, the decrease rate of male and female users during each sleep stage and the wakefulness period before entering sleep can be summarized. Combined with the summarized table data, the decrease rate of average heart rate during each sleep stage and the wakefulness period before entering sleep can be obtained. Please refer to Tables 1 and 2 for details. Table 1 shows the decrease rate of male users during each sleep stage and the wakefulness period before entering sleep at an ambient temperature of 26℃. Table 2 shows the decrease rate of female users during each sleep stage and the wakefulness period before entering sleep at an ambient temperature of 26℃. Wherein, W / m 2 It is the unit of human metabolism.

[0050] Table 1

[0051] male W N1 N2 N3 R First sleep cycle 0 7.13％ 15.66％ 15.83％ 9.62％ Second sleep cycle 12％ 16.05％ 20.91％ 20.9％ 16.03％

[0052] Table 2

[0053]

[0054]

[0055] In Tables 1 and 2, W represents the waking period, N1 represents the light sleep period, N2 / N3 represents the deep sleep period, and R represents the REM sleep period. The first sleep cycle is defined as 2.5 hours after the user falls asleep. The second sleep cycle is defined as the duration of the other sleep stages after the user falls asleep, excluding the first sleep cycle.

[0056] The experimental data above shows that after a user falls asleep in an environment with an ambient temperature of 26℃, the decrease in average heart rate (f) during different sleep stages differs significantly from the decrease during the waking period before falling asleep. This leads to variations in the metabolic rate (M) value. Since the metabolic rate (M) is one of the factors affecting the SPMV model output, the user's comfort value obtained from the SPMV model at different sleep stages will inevitably fluctuate, potentially exceeding the upper comfort threshold or falling below the lower comfort threshold. Meanwhile, factors affecting the SPMV model output also include ambient temperature, relative humidity, and wind speed. Therefore, when the metabolic rate (M) changes and causes the SPMV model output to exceed the preset range, the ambient temperature, relative humidity, and wind speed can be adjusted to bring the adjusted SPMV model output back within the preset range, thereby improving the user's comfort during sleep. The preset range is defined as [lower comfort threshold, upper comfort threshold]. It should be noted that the lower and upper comfort thresholds can be set according to user needs. For example, the lower comfort threshold is -0.3, and the upper comfort threshold is 0.3. Alternatively, the lower comfort threshold is -0.5, and the upper comfort threshold is 0.5. Furthermore, when the SPMV model output is higher than the upper comfort threshold, it indicates that the user experiences heat. The larger the difference between the SPMV model output and the upper comfort threshold, the stronger the user's feeling of heat. When the SPMV model output is lower than the lower comfort threshold, it indicates that the user experiences cold. The larger the absolute value of the difference between the SPMV model output and the lower comfort threshold, the stronger the user's feeling of cold.

[0057] In the third method, the percentage decrease in average heart rate during each sleep stage compared to the percentage decrease during wakefulness before entering sleep can also be determined using the following methods:

[0058] f = C i ·(t-26)+f(26)

[0059] Where f represents the user's average heart rate during each sleep stage and the percentage decrease in heart rate during the waking period before entering sleep; Ci is a third proportionality coefficient, and its value is related to the sleep cycle. In the first sleep cycle, C1 = -0.0086. In the second sleep cycle, C2 = -0.0203. t represents the indoor temperature, which can be obtained through a temperature sensor associated with the air conditioner, or through weather information collected by a terminal device associated with the air conditioner.

[0060] This approach allows for the determination of a more accurate metabolic rate during a user's sleep state by using the average basal metabolic rate during the awake period before entering sleep, the user's average heart rate during each sleep stage and the percentage decrease in heart rate during the awake period before entering sleep, and the second correction factor used to correct the metabolic rate model.

[0061] Optionally, S32, the air conditioner determines the human metabolic rate during sleep based on the user's average basal metabolic rate during the waking period before entering sleep, the user's average heart rate during each sleep stage compared to the percentage decrease during the waking period before entering sleep, and a second correction factor used to correct the metabolic rate model, including:

[0062] M = M B ·[1-c(t)·f]

[0063] Where M is the metabolic rate of the human body during sleep. B The average basal metabolic rate of the user during the waking period before entering the sleep stage is denoted as c(t), which is the second correction factor, and f is the ratio of the decrease in the user's average heart rate during each sleep stage to the decrease during the waking period before entering the sleep stage.

[0064] In this embodiment, as can be seen from the above discussion, f = C i ·(t-26)+f(26). Therefore, the metabolic rate of the human body during sleep can also be derived as: M=M B ·{1-c(t)·[(t-26)·C i +f(26)]}。 It should be noted that the aforementioned formula is not applicable to the calculation of metabolic rate during the waking period of the second sleep cycle, nor is it applicable to the calculation of metabolic rate under extreme low or high temperature environments. With this scheme, a more accurate human metabolic rate during the user's sleep state can be determined by the average basal metabolic rate during the waking period before entering the sleep stage, the user's average heart rate during each sleep stage and the percentage decrease during the waking period before entering the sleep stage, and the second correction amount used to correct the metabolic rate model.

[0065] Alternatively, the second correction amount used to modify the metabolic rate model can be determined in the following way:

[0066] C(t) = kt - z

[0067] Where C(t) is the second correction amount, k is the second proportionality coefficient, t is the indoor temperature, and z is the second correction constant.

[0068] In this scheme, multiple experimental data can be fitted to obtain the formula for calculating the fitted second correction. Here, the formula for calculating the fitted second correction exhibits good linear correlation. As an example, with a goodness-of-fit R... 2 With a value of 0.99, the second proportionality coefficient k is 0.425, and the second correction constant z is 9.9283. That is, the formula for calculating the second correction is C(t) = 0.425t - 9.9283. This shows that the second correction is closely related to changes in indoor temperature. This approach allows for a more accurate second correction, providing a reliable data foundation for constructing the human metabolic rate model.

[0069] Optionally, in S11, the air conditioner determines the surface coefficient of the clothing, including:

[0070] f cl =0.75(1+0.2I) cl )

[0071] Among them, f cl For the surface coefficient, I cl For thermal resistance of clothing.

[0072] In this embodiment, the thickness and coverage area of ​​the bedding vary in different seasons, resulting in different thermal resistances. Therefore, the air conditioner can determine the bedding surface coefficient based on the obtained thermal resistance. In another example, the air conditioner can also obtain the current season information and the exposed area of ​​the user while sleeping; and determine the heat dissipation area of ​​the bedding based on the current season information; thereby determining the bedding surface coefficient based on the exposed area of ​​the user while sleeping and the heat dissipation area of ​​the bedding. Specifically, the air conditioner can determine the bedding surface coefficient based on a preset correspondence, using the bedding surface coefficient corresponding to the exposed area of ​​the user while sleeping and the heat dissipation area of ​​the bedding. In another example, the bedding surface coefficient can also be determined by looking up a table. The table to be looked up can store the bedding surface coefficients of the user under different bedding conditions. In an optimized solution, the air conditioner can also obtain the current season information and the exposed area of ​​the user while sleeping; and determine the heat dissipation area of ​​the bedding based on the current season information; thereby using the ratio of the heat dissipation area of ​​the bedding to the exposed area of ​​the user while sleeping as the bedding surface coefficient. In this way, a more accurate bedding surface coefficient can be determined through multiple methods.

[0073] Figure 4 This is a schematic diagram of a method for determining user thermal comfort provided in an embodiment of this disclosure; combined with Figure 4 As shown in the embodiments of this disclosure, a method for determining user thermal comfort is provided, including:

[0074] S41, the air conditioner determines the user's metabolic rate and the surface coefficient of the bedding during sleep.

[0075] S42, the air conditioner constructs an SPMV model.

[0076] S43, the air conditioner inputs the user's metabolic rate and the surface coefficient of the bedding during sleep into the SPMV model to obtain the comfort value output by the SPMV model.

[0077] S44, the air conditioner determines the thermal comfort status information of the user to characterize the user's feelings based on the comfort value.

[0078] In this solution, before the air conditioner inputs the user's metabolic rate and the surface coefficient of the bedding during sleep into the SPMV model, the air conditioner also needs to construct the SPMV model. Specifically, the construction of the SPMV model by the air conditioner includes: obtaining the PMV model and a first correction factor for correcting the PMV model; and determining the SPMV model based on the PMV model and the first correction factor.

[0079] In this solution, the air conditioner can obtain a PMV model. Specifically, the PMV model includes:

[0080]

[0081] In this embodiment, M, I cl Let W represent the metabolic rate, thermal resistance of the clothing, and external mechanical work, respectively, with the external mechanical work being 0. a v, H, and tr represent ambient temperature, wind speed, relative humidity, and mean radiant temperature, respectively, and the mean radiant temperature tr is related to the ambient temperature t. a The values ​​are equal. P a f cl h c t cl These represent the partial pressure of water vapor, the surface coefficient of the clothing, the convective heat transfer coefficient, and the outer surface temperature of the clothing, respectively.

[0082] Specifically, the partial pressure of water vapor P a Based on ambient temperature and relative humidity, the following formula is used for calculation:

[0083]

[0084] Specifically, the convective heat transfer coefficient is determined based on the ambient temperature, mean radiant temperature, and wind speed, and is calculated using the following formula:

[0085]

[0086] Specifically, the surface coefficient of clothing can be determined in several ways:

[0087] The first method: Understandably, the thickness and area covered by bedding vary in different seasons, and consequently, the thermal resistance of the bedding also differs. Therefore, air conditioners can determine the surface coefficient of bedding by combining the obtained thermal resistance.

[0088] The second method: The air conditioner can also obtain current seasonal information and the exposed body parts of the user while sleeping; and determine the heat dissipation area of ​​the clothing based on the current seasonal information; thus, based on the exposed body parts of the user while sleeping and the heat dissipation area of ​​the clothing, determine the corrected surface coefficient of the clothing. Specifically, the air conditioner can determine the surface coefficient of the clothing corresponding to the exposed body parts of the user while sleeping and the heat dissipation area of ​​the clothing according to a preset correspondence.

[0089] The third method: The surface coefficient of the clothing can also be determined by looking up a table. The table to be queried can store the surface coefficients of the clothing for different types of clothing.

[0090] The fourth method: The air conditioner can also obtain the current season information and the exposed area of ​​the user when they are sleeping; and determine the heat dissipation area of ​​the clothing based on the current season information; and then use the ratio of the heat dissipation area of ​​the clothing to the exposed area of ​​the user when they are sleeping as the surface coefficient of the clothing.

[0091] In this way, the surface coefficient of the clothing can be determined more accurately through multiple methods.

[0092] Furthermore, in order to obtain a more accurate SPMV model that characterizes the user's thermal comfort during nighttime sleep, it is also necessary to calculate a first correction factor to correct the PMV model. Here, the first correction factor is a temperature correction factor, which the air conditioner can use to correct for fluctuations in the PMV model caused by changes in ambient temperature.

[0093] Optionally, the air conditioner calculates a first correction amount for revising the PMV model, including:

[0094] b(t) = at - c

[0095] Where b(t) is the first correction amount, a is the first proportionality coefficient, t is the indoor temperature, and c is the first correction constant.

[0096] In this scheme, multiple experimental data can be fitted to obtain the formula for calculating the first correction after fitting. Here, the formula for calculating the first correction after fitting exhibits good linear correlation. As an example, when the goodness of fit R... 2With a scaling factor of 0.88, the first proportionality coefficient 'a' is 0.2294, and the first correction constant 'c' is 6.4026. That is, the formula for calculating the first correction is b(t) = 0.2294t - 6.4026. This shows that the first correction is closely related to changes in indoor temperature. This approach allows for a more accurate first correction, providing a reliable data foundation for the construction of the SPMV model.

[0097] Optionally, the air conditioner determines the SPMV model based on the PMV model and the first correction factor, including:

[0098] SPMV = PMV + b(t)

[0099] Where b(t) is the first correction value.

[0100] In this scheme, the air conditioner can combine the PMV model and the first correction factor to determine the SPMV model. Here, b(t) is the first correction factor, which is a temperature correction factor used to correct for fluctuations in the PMV model caused by changes in ambient temperature. The SPMV model includes:

[0101]

[0102] Among them, M and I cl Let W represent the metabolic rate, thermal resistance of the clothing, and external mechanical work, respectively, with the external mechanical work being 0. a v, H, and tr represent ambient temperature, wind speed, relative humidity, and mean radiant temperature, respectively, and the mean radiant temperature tr is related to the ambient temperature t. a The values ​​are equal. P a f cl h c t cl These represent the partial pressure of water vapor, the surface coefficient of the clothing, the convective heat transfer coefficient, and the outer surface temperature of the clothing, respectively.

[0103] The SPMV model described above comprehensively considers human body parameters, environmental factors, and other related factors, enabling a more accurate construction of a thermal comfort model associated with user sleep. Compared to the PMV model used in related technologies, it more accurately reflects the actual comfort level of users during sleep. Human body parameters include metabolic rate, clothing thermal resistance, and external mechanical work. Environmental factors include ambient temperature, wind speed, relative humidity, and mean radiant temperature. Other related factors include water vapor partial pressure, clothing surface coefficient, convective heat transfer coefficient, and clothing outer surface temperature.

[0104] Optionally, embodiments of this disclosure provide a method for controlling an air conditioner, comprising:

[0105] The air conditioner acquires the current sleep state of the user associated with it during the sleep phase. It also acquires the current comfort value from the SPMV model associated with the user. This current comfort value is determined by the SPMV model output. If the current comfort value does not match the preset comfort value, the air conditioner executes an environmental control strategy corresponding to the current sleep state to adjust the current comfort value to match the preset comfort level.

[0106] In this solution, the air conditioner can obtain the user's current sleep state during the sleep stage through a sleep monitoring device that is communicatively connected to the air conditioner. As an example, the sleep monitoring device is a sleep pillow, which detects the user's movement intensity during sleep and determines the user's current sleep state based on the movement intensity. As another example, the sleep monitoring device is a smartwatch, worn on the user's wrist. The smartwatch is equipped with a gyroscope sensor and a heart rate sensor. The gyroscope sensor detects the amplitude and frequency of wrist movements, and the heart rate sensor detects the user's heart rate value. The smartwatch acquires the amplitude and frequency of wrist movements and the heart rate value, analyzes and processes them, and generates the user's current sleep state. This embodiment of the disclosure does not specifically limit the method by which the air conditioner obtains the user's current sleep state during the sleep stage.

[0107] Furthermore, the air conditioner obtains the current comfort value of the user-related SPMV model in the following manner: It acquires the user's vital signs parameters and the environmental parameters of the user's environment. The vital signs parameters and environmental parameters are input into the SPMV model to obtain the SPMV model output, which is then used as the user's current comfort value. The vital signs parameters include metabolic rate and clothing thermal resistance. The environmental parameters include ambient temperature, wind speed, and relative humidity. Understandably, after the air conditioner adjusts one or more of the ambient temperature, wind speed, and / or relative humidity, the updated environmental parameters can be input into the SPMV model to update the user's comfort value.

[0108] The method for controlling an air conditioner provided in this disclosure can accurately determine the user's current comfort level by using the SPMV model output. When the current comfort level does not match a preset comfort level, an environmental control strategy corresponding to the current sleep state is executed to ensure that the adjusted SPMV model output matches the preset comfort level. This allows the air conditioner to dynamically adjust the environment according to the user's comfort needs during sleep. This method improves the accuracy of comfort judgment during sleep and meets the user's comfort requirements.

[0109] Optionally, the air conditioner executes an environmental control strategy corresponding to the current sleep state, including:

[0110] When the user is asleep in the current sleep state, the air conditioner obtains the user's sleep migration state and the sleep period associated with the current sleep state; based on the sleep migration state and sleep period, the air conditioner adjusts the temperature and humidity values ​​and / or fan speed of the user's associated environment.

[0111] In this embodiment, sleep migration state refers to the user's transition between adjacent sleep stages within a certain sleep period. A sleep period refers to the sleep cycle the user is in during sleep. A complete sleep cycle consists of sequentially occurring wakefulness, light sleep, deep sleep, and REM sleep. The duration of wakefulness, light sleep, deep sleep, and REM sleep varies within different sleep cycles. Wakefulness, light sleep, deep sleep, and REM sleep represent different sleep stages. Thus, this method acquires the user's sleep migration state and current sleep stage in real time, and based on the aforementioned sleep migration state and sleep stage, adjusts the temperature, humidity, and / or wind speed of the user's environment accordingly to ensure that the adjusted SPMV model output is within a preset range, thereby meeting the user's comfort requirements during sleep stages.

[0112] Optionally, when the current comfort level exceeds the upper limit threshold, the air conditioner adjusts the temperature and humidity levels and / or fan speed of the user's environment based on sleep migration status and sleep stage, including:

[0113] When the air conditioner is in sleep transition mode (meaning it's switching to sleep mode and is in the first sleep cycle), the fan speed is increased. When the air conditioner is in sleep mode (meaning it's in the second sleep cycle) and in sleep transition mode (meaning it remains in the current sleep stage), the ambient temperature is lowered and the fan speed is reduced.

[0114] Thus, when a sleep cycle is confirmed and the user is in the first sleep cycle, it indicates that the user has entered a sleep stage. Extensive experiments have shown that adjusting the fan speed reduces the updated SPMV model output more quickly than adjusting ambient temperature and humidity. Therefore, when the user is asleep, the air conditioner increases the fan speed to rapidly regulate the SPMV model output. When the user remains in the current sleep stage and is in the second sleep cycle, it indicates relatively stable sleep and a slight decrease in body temperature. To reduce noise from the fan and minimize disruption to the user's sleep, the air conditioner reduces the fan speed. Simultaneously, to keep the SPMV model output within a preset range, the air conditioner regulates the ambient temperature.

[0115] Optionally, controlling the fan to increase the wind speed includes: controlling the fan to increase from the initial wind speed at a first preset rate of change. Controlling the fan to decrease the wind speed includes: controlling the fan to decrease the wind speed at a second preset rate of change until it returns to the initial wind speed; wherein the first preset rate of change is greater than or equal to 0.3 m / s and less than or equal to 0.5 m / s, and the second preset rate of change is greater than or equal to 0.3 m / s and less than or equal to 0.5 m / s.

[0116] Thus, the fan will generate noise during operation, especially in scenarios where the fan operates at high wind speeds. To reduce the impact of fan noise on users' sleep, the air conditioner can be set with a preset fan speed range. Furthermore, if the fan speed is increased or decreased too rapidly during control, it will affect the user's sleep. Therefore, a first preset rate of change can be set to allow the fan speed to increase or decrease gradually. The aforementioned preset fan speed range is [0.1, 1.2] meters per second.

[0117] Optionally, when the current comfort level is below the lower comfort threshold, the air conditioner adjusts the temperature and humidity levels and / or fan speed of the user's environment based on sleep migration status and sleep stage, including:

[0118] When the air conditioner is in sleep transition mode (indicating a sleep cycle change) and in sleep period mode (indicating the first sleep cycle), the fan speed is reduced to maintain the ambient temperature and humidity levels. When the air conditioner is in sleep period mode (indicating the second sleep cycle) and in sleep transition mode (indicating continued sleep state), the fan speed is increased.

[0119] Thus, when the current comfort value is below the lower comfort threshold, it indicates that the SPMV model output is too low. When the air conditioner determines that the user has switched to a sleep cycle and is in the second sleep cycle, it can adjust the output by reducing the fan speed. Simultaneously, the air conditioner maintains a constant ambient temperature and humidity. When it is determined that the user is in the second sleep cycle and remains in the current sleep stage, in order to reduce the SPMV model output from the lower comfort threshold to within a preset range, the air conditioner controls the fan speed to increase.

[0120] Optionally, when the current comfort value is less than the lower comfort threshold, the air conditioner adjusts the temperature and humidity values ​​and / or fan speed of the user's associated environment based on sleep migration status and sleep stage, including:

[0121] When the air conditioner is in sleep transition mode (indicating a sleep cycle) and in sleep period mode (indicating the first sleep cycle), it controls the fan speed to decrease and maintains the ambient temperature and humidity. When the air conditioner is in sleep period mode (indicating the second sleep cycle) and in sleep transition mode (indicating continued sleep period), it controls the fan speed to increase. The air conditioner then acquires a new current comfort value. If the new current comfort value is greater than the upper comfort threshold, the air conditioner controls the ambient temperature to decrease by a first preset temperature change amount. If the new current comfort value is less than the lower comfort threshold, the air conditioner controls the ambient temperature to increase by a second preset temperature change amount and controls the ambient relative humidity to within a preset relative humidity range. The preset relative humidity range is [50%RH, 65%RH].

[0122] Thus, experiments revealed that, with wind speed and relative humidity remaining constant, the change in the SPMV model output is positively correlated with the change in temperature. Specifically, a 1°C increase in temperature results in an approximately 0.5–0.6% increase in the SPMV model output, and a 1°C decrease results in an approximately 0.5–0.6% decrease in the SPMV model output. Based on this experimental data, when the current comfort value is greater than the upper comfort threshold, the air conditioner controls the ambient temperature to decrease by a first preset temperature change, causing a slight decrease in the SPMV model output. When the current comfort value is less than the lower comfort threshold, the air conditioner controls the ambient temperature to increase by a second preset temperature change and controls the relative humidity to within a preset range, thereby regulating both the SPMV model output and ensuring that the adjusted relative humidity meets the user's comfort requirements.

[0123] Optionally, embodiments of this disclosure also provide a method for controlling an air conditioner, comprising:

[0124] The air conditioner obtains the current sleep state of the user associated with it during the sleep stage; the air conditioner obtains the current comfort value of the SPMV model associated with the user; if the current comfort value does not match the preset comfort value, the air conditioner obtains the priority of the user's associated environmental parameters, including wind speed, relative humidity, and temperature, so as to adjust the user's associated environment according to the priority of the environmental parameters.

[0125] In this embodiment, since many factors affect the output of the SPMV model, the air conditioner can preset the priority of environmental parameters to balance the control efficiency and energy consumption of the air conditioner. As one example, the priorities, from highest to lowest, are wind speed, relative humidity, and temperature. As another example, the priorities, from highest to lowest, are wind speed, temperature, and relative humidity. Understandably, since adjusting wind speed has a greater impact on the output of the SPMV model than adjusting temperature and humidity, and since the rise and fall of ambient temperature and relative humidity require time, wind speed is determined to be the highest priority. The air conditioner executes an environmental control strategy corresponding to the current sleep state to match the adjusted current comfort value with the preset comfort level.

[0126] The method for controlling an air conditioner provided in this disclosure effectively improves the accuracy of comfort judgment during user sleep and enhances the environmental control efficiency of the air conditioner, while also reducing energy consumption. Understandably, this involves three types of environmental parameters: wind speed, temperature, and relative humidity. During actual control, if only one environmental parameter is adjusted, the output of the SPMV model may not fall within the preset comfort range. Therefore, the output of the SPMV model can be adjusted by adjusting the other two environmental parameters or any one of the other two. Specifically, excessive wind speed will affect user sleep; therefore, a preset wind speed range is set to 0.1 m / s to 1.2 m / s. Excessively high or low relative humidity will cause user discomfort; therefore, a preset relative humidity range is set to 40% to 70%.

[0127] In practical applications, the air conditioner and the sleep pillow are connected in communication, with the sleep pillow transmitting the user's current sleep state to the air conditioner in real time. The initial fan speed is 0.1 m / s. The first preset rate of change is 0.3 m / s. The lower and upper comfort thresholds are -0.3 and 0.3, respectively. The specific method for controlling the air conditioner is as follows:

[0128] The air conditioner acquires the current environmental parameters and inputs them into the SPMV model, which outputs a value of 0.4. Therefore, the current comfort value is determined to be greater than the upper comfort threshold. The air conditioner receives a sleep signal from the sleep pillow, which carries the sleep transition state and the user's current sleep stage. The sleep transition state indicates a sleep switch is in progress, and the current sleep stage is the first sleep cycle. Based on the initial fan speed, the air conditioner increases the fan speed by 0.4 m / s at a first preset rate and operates at this speed for 5 minutes. The air conditioner maintains constant ambient temperature and humidity. The air conditioner receives a new sleep signal from the sleep pillow; the new sleep transition state is "not transitioned," and the new sleep stage is the second sleep cycle. Since the change in the SPMV model output is positively correlated with the change in ambient temperature, the air conditioner lowers the ambient temperature value ΔT and controls the fan to reduce the fan speed back to the initial speed. The air conditioner re-acquires the SPMV model output, which is now 0.18. Therefore, the current environmental parameters are determined to meet the user's comfort requirements.

[0129] Figure 5 This is a schematic diagram of a device for determining user thermal comfort provided in an embodiment of this disclosure; combined with Figure 5 As shown, this disclosure provides an apparatus for determining a user's thermal comfort, including a first determining module 51, an input module 52, and a second determining module 53. The first determining module 51 is configured to determine the user's metabolic rate and the surface coefficient of clothing during sleep; the input module 52 is configured to input the user's metabolic rate and the surface coefficient of clothing during sleep into an SPMV model to obtain a comfort value output by the SPMV model; the second determining module 53 is configured to determine, based on the comfort value, information characterizing the user's thermal comfort state.

[0130] The apparatus for determining user thermal comfort provided in this embodiment determines the user's metabolic rate and the surface coefficient of clothing during sleep. These parameters are then input into an SPMV model to obtain a comfort value output by the SPMV model. Based on this comfort value, the user's thermal comfort status information, representing their sensations, is determined. This approach allows for accurate determination of a user's thermal comfort during nighttime sleep through the SPMV model, providing a reliable data foundation for controlling the air conditioner while the user is asleep, thus meeting the user's thermal comfort needs.

[0131] Figure 6 This is a schematic diagram of a device for determining user thermal comfort provided in an embodiment of this disclosure; combined with Figure 6As shown, this disclosure provides an apparatus for determining user thermal comfort, including a processor 100 and a memory 101. Optionally, the apparatus may further include a communication interface 102 and a bus 103. The processor 100, communication interface 102, and memory 101 can communicate with each other via the bus 103. The communication interface 102 can be used for information transmission. The processor 100 can call logical instructions in the memory 101 to execute the method for determining user thermal comfort described in the above embodiment.

[0132] Furthermore, the logic instructions in the aforementioned memory 101 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0133] The memory 101, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 100 executes functional applications and data processing by running the program instructions / modules stored in the memory 101, that is, it implements the method for determining user thermal comfort in the above embodiments.

[0134] The memory 101 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 101 may include high-speed random access memory and may also include non-volatile memory.

[0135] This disclosure provides an air conditioner that includes the aforementioned device for determining a user's thermal comfort.

[0136] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described method for determining user thermal comfort.

[0137] This disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions that, when executed by a computer, cause the computer to perform the above-described method for determining user thermal comfort.

[0138] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0139] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0140] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0141] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0142] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for determining a user thermal comfort, characterized in that, The method comprises the following steps: determining the metabolic rate of the user in the sleep state and the clothing surface coefficient; inputting the metabolic rate of the user in the sleep state and the clothing surface coefficient into an SPMV model to obtain a comfort value output by the SPMV model; determining, according to the comfort value, the thermal comfort state information of the user for representing the user's feeling; the determination of the metabolic rate of the user in the sleep state comprises: obtaining the average basal metabolic rate of the user in the wake period before entering the sleep stage, the average heart rate of the user in each sleep stage, the drop ratio of the average heart rate of the user in each sleep stage to the wake period before entering the sleep stage, and a second correction quantity for correcting the metabolic rate model; determining, according to the average basal metabolic rate of the user in the wake period before entering the sleep stage, the average heart rate of the user in each sleep stage, the drop ratio of the average heart rate of the user in each sleep stage to the wake period before entering the sleep stage, and the second correction quantity for correcting the metabolic rate model, the metabolic rate of the user in the sleep state comprises: the SPMV model comprises: Wherein, M is the metabolic rate of the human body in sleep state, M B is the average basal metabolic rate of the user in the wake period before entering the sleep stage, f is the average heart rate of the user in each sleep stage and the reduction ratio before entering the sleep stage, W is the external mechanical work, t a is the ambient temperature, P a is the water vapor partial pressure, f cl is the clothing surface coefficient, h c is the convective heat transfer coefficient, t cl is the clothing outer surface temperature, and b(t) is the first correction amount. the second correction quantity for correcting the metabolic rate model is determined by the following method: wherein C(t) is the second correction quantity, k is a second proportional coefficient, t is the indoor temperature, and z is a second normal number; the air conditioner calculates a first correction quantity for correcting the PMV model, comprising: b(t) = at-c wherein b(t) is the first correction quantity, a is a first proportional coefficient, t is the indoor temperature, and c is a first normal number.

2. The method of claim 1, wherein, the determination, according to the comfort value, of the thermal comfort state information of the user for representing the user's feeling comprises: obtaining a thermal comfort information library, wherein different comfort intervals correspond to respective thermal comfort state information; determining a target comfort interval to which the comfort value belongs; taking the thermal comfort state information corresponding to the target comfort interval matched in the thermal comfort information library as the thermal comfort state information of the user.

3. The method of claim 1, wherein, determining the clothing surface coefficient comprises: where f cl is the surface coefficient of the garment, I cl is the thermal resistance of the garment.

4. The method of claim 1, wherein, before inputting the metabolic rate of the user in the sleep state and the clothing surface coefficient into the SPMV model, the method further comprises: constructing an SPMV model; wherein the SPMV model is obtained by correcting a PMV model.

5. An apparatus for determining a user thermal comfort, characterized in that, The method comprises the following steps: a first determination module configured to determine the metabolic rate of the user in the sleep state and the clothing surface coefficient; an input module configured to input the metabolic rate of the user in the sleep state and the clothing surface coefficient into an SPMV model to obtain a comfort value output by the SPMV model; a second determination module configured to determine, according to the comfort value, the thermal comfort state information of the user for representing the user's feeling; the determination of the metabolic rate of the user in the sleep state comprises: obtaining the average basal metabolic rate of the user in the wake period before entering the sleep stage, the average heart rate of the user in each sleep stage, the drop ratio of the average heart rate of the user in each sleep stage to the wake period before entering the sleep stage, and a second correction quantity for correcting the metabolic rate model; determining, according to the average basal metabolic rate of the user in the wake period before entering the sleep stage, the average heart rate of the user in each sleep stage, the drop ratio of the average heart rate of the user in each sleep stage to the wake period before entering the sleep stage, and the second correction quantity for correcting the metabolic rate model, the metabolic rate of the user in the sleep state comprises: The SPMV model comprises: Wherein, M is the metabolic rate of the human body in sleep state, M B is the average basal metabolic rate of the user in the wake period before entering the sleep stage, f is the average heart rate of the user in each sleep stage and the reduction ratio before entering the sleep stage, W is the external mechanical work, t a is the ambient temperature, P a is the water vapor partial pressure, f cl is the clothing surface coefficient, h c is the convective heat transfer coefficient, t cl is the clothing outer surface temperature, and b(t) is the first correction amount. A second correction quantity for correcting the metabolic rate model is determined by: wherein C(t) is the second correction quantity, k is a second proportional coefficient, t is the indoor temperature, and z is a second correction constant; The air conditioner calculates a first correction quantity for correcting the PMV model, comprising: b(t) = at - c wherein b(t) is the first correction quantity, a is a first proportional coefficient, t is the indoor temperature, and c is a first correction constant.

6. An apparatus for determining user thermal comfort, comprising a processor and a memory having stored program instructions, characterized in that, The processor is configured to execute, when running the program instructions, the method for determining user thermal comfort according to any one of claims 1 to 4.

7. A storage medium storing program instructions, characterized in that, The program instructions, when running, execute the method for determining user thermal comfort according to any one of claims 1 to 4.

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