CN114636237A

CN114636237A - Method, apparatus and storage medium for constructing thermal comfort model

Info

Publication number: CN114636237A
Application number: CN202210269554.6A
Authority: CN
Inventors: 付光军; 魏伟; 庄杰; 郭鑫; 刘维兵
Original assignee: Qingdao Haier Air Conditioner Gen Corp Ltd; Qingdao Haier Air Conditioning Electric Co Ltd; Haier Smart Home Co Ltd
Current assignee: Qingdao Haier Air Conditioner Gen Corp Ltd; Qingdao Haier Air Conditioning Electric Co Ltd; Haier Smart Home Co Ltd
Priority date: 2022-03-18
Filing date: 2022-03-18
Publication date: 2022-06-17

Abstract

The application relates to the technical field of model construction, and discloses a method for constructing a thermal comfort model, which comprises the following steps: determining the human body metabolic rate and the bedding and clothing surface coefficient of a user in a sleeping state; establishing a PMV model according to the human body metabolic rate and the bedding and clothing surface coefficient in a sleeping state; calculating a first correction amount for correcting the PMV model; and constructing an SPMV model according to the PMV model and the first correction quantity. With this scheme, solved current PMV model and can not characterize the drawback of the thermal comfort degree condition of user under the sleep state at night, promoted the accuracy that the thermal comfort degree of user sleep stage judged, for the user carries out air conditioner control under the sleep state and provides accurate data basis, satisfy the demand of user thermal comfort degree. The application also discloses a device and a storage medium for constructing the thermal comfort model.

Description

Method, apparatus and storage medium for constructing thermal comfort model

Technical Field

The present application relates to the field of model building technologies, and for example, to a method, an apparatus, and a storage medium for building a thermal comfort model.

Background

Along with the continuous improvement of the living standard of people, the intelligent household electrical appliance gradually enters the life of a user. At present, as the requirement of the user on the thermal comfort level of the environment where the user is located is continuously increased, the air conditioner becomes an indispensable intelligent household appliance for each family.

At present, in order to meet the thermal comfort requirements of different users, a PMV (Predicted Mean volume) model is usually pre-stored in the air conditioner, so as to obtain a thermal comfort value output by the PMV model under the condition that environmental parameters and physical sign parameters of the user in an awake state are input into the PMV model, and thus, the air conditioner is controlled to execute a corresponding operation mode in combination with the thermal comfort value output by the PMV model, so as to meet the thermal comfort requirements of the user. However, the PMV model in the prior art is a model established based on physical sign parameters of the user in a daytime awake state, and the model cannot accurately reflect the thermal comfort condition of the user in a night sleep state.

Therefore, how to construct a thermal comfort model capable of reflecting the thermal comfort condition of the user in the night sleep state becomes an urgent technical problem to be solved.

Disclosure of Invention

The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.

The embodiment of the disclosure provides a method, a device and a storage medium for constructing a thermal comfort model, so as to provide a method for constructing the thermal comfort model capable of reflecting the thermal comfort condition of a user in a night sleep state.

In some embodiments, the method for constructing a thermal comfort model comprises: determining the human body metabolic rate and the bedding and clothing surface coefficient of a user in a sleeping state; establishing a PMV model according to the human body metabolic rate and the bedding and clothing surface coefficient in a sleeping state; calculating a first correction amount for correcting the PMV model; and constructing an SPMV model according to the PMV model and the first correction quantity.

In some embodiments, the means for constructing a thermal comfort model comprises: a processor and a memory storing program instructions, the processor being configured to, upon execution of the program instructions, perform the aforementioned method for constructing a thermal comfort model.

In some embodiments, the storage medium comprises: program instructions are stored which, when executed, perform the aforementioned method for constructing a thermal comfort model.

The method, the device and the storage medium for constructing the thermal comfort model provided by the embodiment of the disclosure can realize the following technical effects: after the human body metabolic rate and the bedding and clothing surface coefficient of the user in the sleeping state are determined, a PMV model is established by combining the human body metabolic rate and the bedding and clothing surface coefficient in the sleeping state, and the PMV model is corrected through the calculated first correction quantity, so that the SPMV model capable of reflecting the thermal comfort condition of the user in the sleeping state at night is obtained. With this scheme, solved current PMV model and can not characterize the drawback of the thermal comfort degree condition of user under the sleep state at night, promoted the accuracy that the thermal comfort degree of user sleep stage judged, for the user carries out air conditioner control under the sleep state and provides accurate data basis, satisfy the demand of user thermal comfort degree.

The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.

Drawings

One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:

FIG. 1 is a schematic diagram of a method for constructing a thermal comfort model according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a method for determining a metabolic rate of a human body of a user in a sleep state according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a method for determining surface coefficients of a clothing article according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a method for controlling an air conditioner according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of an apparatus for constructing a thermal comfort model according to an embodiment of the present disclosure;

fig. 6 is a schematic diagram of another apparatus for constructing a thermal comfort model according to an embodiment of the present disclosure.

Detailed Description

So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.

The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.

The term "plurality" means two or more unless otherwise specified.

In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.

The term "and/or" is an associative relationship that describes objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.

The term "correspond" may refer to an association or binding relationship, and a corresponds to B refers to an association or binding relationship between a and B.

In the embodiment of the disclosure, the intelligent household appliance is a household appliance formed by introducing a microprocessor, a sensor technology and a network communication technology into the household appliance, and has the characteristics of intelligent control, intelligent sensing and intelligent application, the operation process of the intelligent household appliance usually depends on the application and processing of modern technologies such as internet of things, internet and an electronic chip, for example, the intelligent household appliance can realize the remote control and management of a user on the intelligent household appliance by connecting the intelligent household appliance with the electronic device.

In the embodiment of the present disclosure, the terminal device is an electronic device with a wireless connection function, and the terminal device may be in communication connection with the above intelligent household appliance by connecting to the internet, or may be in communication connection with the above intelligent household appliance directly by means of bluetooth, wifi, and the like. In some embodiments, the terminal device is, for example, a mobile device, a computer, or a vehicle-mounted device built in a floating car, or any combination thereof. The mobile device may include, for example, a cell phone, a smart home device, a wearable device, a smart mobile device, a virtual reality device, or the like, or any combination thereof, wherein the wearable device includes, for example: smart watches, smart bracelets, pedometers, and the like.

FIG. 1 is a schematic diagram of a method for constructing a thermal comfort model according to an embodiment of the present disclosure; as shown in fig. 1, an embodiment of the present disclosure provides a method for constructing a thermal comfort model, including:

and S11, the air conditioner determines the human body metabolic rate and the bedding surface coefficient of the user in the sleep state.

And S12, the air conditioner establishes a PMV model according to the human body metabolic rate and the surface coefficient of the bedding and clothing in the sleeping state.

S13, the air conditioner calculates a first correction amount for correcting the PMV model.

And S14, the air conditioner constructs an SPMV model according to the PMV model and the first correction quantity.

In the scheme, it can be understood that the human body metabolic rate of the user in the sleep state is different from the human body metabolic rate of the user in the waking state. Therefore, the air conditioner can determine the human body metabolic rate in the sleep state by obtaining the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and the second correction quantity for correcting the metabolic rate model. In addition, the air conditioner can also determine the surface coefficient of the bedding and clothing by obtaining the thermal resistance of the bedding and clothing. Here, the thermal resistances of the coveralls in different seasons are different, and accordingly, the heat dissipation areas of the coveralls are also different. Further, after the air conditioner determines the human body metabolic rate and the bedding and clothing surface coefficient of the user in the sleep state, the air conditioner can establish the PMV model by combining the human body metabolic rate and the bedding and clothing surface coefficient in the sleep state. Here, the PMV model established by combining the metabolic rate of the human body and the surface coefficient of the clothing in the sleep state can represent the thermal comfort condition of the user in the sleep state at night to some extent. Further, in order to construct an SPMV model capable of representing the thermal comfort condition of the user in the night sleep state more accurately, a first correction amount for correcting the PMV model needs to be calculated. Here, the first correction amount is a temperature correction amount, and the air conditioner can correct the fluctuation of the PMV model due to the change in the ambient temperature by the first correction amount. Therefore, after the air conditioner calculates the first correction quantity for correcting the PMV model, the SPMV model which can represent the thermal comfort condition of the user in the night sleep state more accurately can be constructed by combining the PMV model and the first correction quantity.

By adopting the method for constructing the thermal comfort model provided by the embodiment of the disclosure, after the human body metabolic rate and the bedding surface coefficient of the user in the sleep state are determined, the PMV model is established by combining the human body metabolic rate and the bedding surface coefficient in the sleep state, and the PMV model is corrected through the calculated first correction quantity, so that the SPMV model capable of reflecting the thermal comfort condition of the user in the night sleep state is obtained. With this scheme, solved current PMV model and can not characterize the drawback of the thermal comfort degree condition of user under the sleep state at night, promoted the accuracy that the thermal comfort degree of user sleep stage judged, for the user carries out air conditioner control under the sleep state and provides accurate data basis, satisfy the demand of user thermal comfort degree.

Optionally, at S14, the air conditioner constructs an SPMV model according to the PMV model and the first correction amount, including:

SPMV＝PMV+b(t)

in the scheme, the air conditioner can combine the PMV model and the first correction quantity to construct the SPMV model. Wherein, b (t) is a first correction amount, the first correction amount is a temperature correction amount, and the first correction amount is used for correcting fluctuation of the PMV model caused by environmental temperature change. The SPMV model comprises:

wherein, M, I_clAnd W respectively represents the metabolic rate, the thermal resistance of the bedding and clothing and the external mechanical work, and the external mechanical work is 0. t is t_aV, H, tr respectively represent the ambient temperature, wind speed, relative humidity and average radiation temperature, and the average radiation temperature tr and the ambient temperature t_aThe values are equal. P_a、f_cl、h_c、t_clRespectively representing the water vapor partial pressure, the surface coefficient of the quilt and the clothes, the heat convection coefficient and the temperature of the outer surface of the clothes.

By adopting the SPMV model, human parameter factors, environmental factors, other related factors and the like can be comprehensively considered, the thermal comfort model related to the sleep of the user can be more accurately constructed, and compared with PMV adopted in the related technology, the thermal comfort model can accurately reflect the actual comfort condition of the user in the sleep state. Wherein, the human body parameter factors comprise metabolic rate, thermal resistance of bedding and clothing and external mechanical work. Environmental factors include ambient temperature, wind speed, relative humidity and average radiation temperature. Other relevant factors include water vapor partial pressure, surface coefficient of clothing, convective heat transfer coefficient, and garment exterior surface temperature.

Alternatively, S13, the air conditioner calculates a first correction amount for correcting the PMV model, including:

b(t)＝at-c

wherein, b (t) is a first correction amount, a is a first proportional coefficient, t is the indoor temperature, and c is a first correction constant.

In this scheme, a plurality of experimental data may be fitted to obtain a calculation formula of the fitted first correction amount. Here, the calculation formula of the fitted first correction amount hasGood linear correlation. As an example, in goodness of fit R²When the value is 0.88, the first scaling factor a is 0.2294, and the first correction constant c is 6.4026. That is, the first correction amount is calculated by b (t) 0.2294 t-6.4026. Therefore, the first correction quantity is closely related to the change situation of the indoor temperature. By the scheme, the first correction quantity can be obtained more accurately, and an accurate data basis is provided for the construction process of the SPMV model.

FIG. 2 is a schematic diagram of a method for determining a metabolic rate of a human body of a user in a sleep state according to an embodiment of the present disclosure; referring to fig. 2, optionally, the air conditioner determines the human body metabolic rate of the user in the sleep state at S11, including:

and S21, the air conditioner obtains the average basal metabolic rate of the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and a second correction quantity for correcting the metabolic rate model.

And S22, the air conditioner determines the human body metabolic rate in the sleep state according to the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and a second correction quantity for correcting the metabolic rate model.

In this embodiment, the average basal metabolic rate of the user during the wake period before entering the sleep stage may be 40W/m². The decreasing ratio of the user's average heart rate at each sleep stage to the awake period before entering the sleep stage can also be obtained in a number of ways:

in the first mode, under the condition that the current indoor temperature is the preset temperature, the air conditioner can obtain the sex information of the user, the sleep cycle information of the user at present and the sleep stage information of the user in the sleep cycle; therefore, the air conditioner can take the descending proportion corresponding to the sex information of the user, the current sleep cycle information of the user and the sleep stage information of the user in the sleep cycle as the descending proportion of the average heart rate of the user in each sleep stage and the waking period before the user enters the sleep stage according to the preset corresponding relation.

In the second mode, when the ambient temperature is 26 ℃, the decreasing ratios of the waking periods before the sleep stages and the average heart rate of the user in each sleep stage and the decreasing ratio of the waking period before the sleep stages are obtained by summarizing the decreasing ratios of the waking periods before the sleep stages and the average heart rate of the user in each sleep stage and the decreasing ratio of the waking period before the sleep stages by combining the summarized table data, which is specifically referred to table 1 and table 2. Here, table 1 shows the decreasing ratio of each sleep stage to the waking period before entering the sleep stage when the ambient temperature is 26 ℃. Table 2 shows the rate of decline of each sleep stage to the wake period prior to entering the sleep stage for a female user at an ambient temperature of 26 ℃. Wherein, W/m²Is a human metabolism unit.

TABLE 1

Male sex	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％

TABLE 2

Female with a pattern of holes	W	N1	N2	N3	R
						First sleep cycle	0	7.65％	10.91％	11.93％	2.83％
Second sleep cycle	3％	14.9％	18.86％	17.81％	12.21％

In tables 1 and 2, W indicates the waking period, N1 indicates the light sleep period, N2/N3 indicates the deep sleep period, and R indicates the rapid eye movement period. The first sleep period is defined as 2.5 hours after the user falls asleep. The second sleep cycle is defined as the duration of other sleep stages after the user enters sleep, except for the first sleep cycle.

From the above experimental data, after the user enters sleep in the environment with the ambient temperature of 26 ℃, in different sleep stages, the average heart rate of the user in each sleep stage has a larger difference from the decrease ratio f of the user in the waking period before entering the sleep stage. This results in a difference in the value of the metabolic rate M. Because the factors influencing the output quantity of the SPMV model comprise the metabolic rate M, the comfort values of the user in different sleep stages obtained according to the SPMV model are necessarily fluctuated, and even the situations that the comfort values exceed the upper comfort threshold or are smaller than the lower comfort threshold occur. Meanwhile, the factors influencing the output quantity of the SPMV model also comprise the ambient temperature, the relative humidity, the wind speed and the like. Therefore, when the metabolic rate M changes and the output quantity of the SPMV model exceeds the preset range, the output quantity of the SPMV model obtained again after regulation is in the preset range by regulating and controlling three parameters of the environmental temperature, the relative humidity and the wind speed, so that the comfort level of the sleep stage of the user is improved. Wherein the preset range is [ comfort level lower limit threshold, comfort level upper limit threshold ]. It should be noted that the comfort level lower threshold and the comfort level upper threshold may be set according to the user's 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 comfort upper threshold, it indicates that the user generates heat sensation. And the larger the difference value between the output quantity of the SPMV model and the comfort degree upper limit threshold value is, the stronger the thermal sensation of the user is. And when the output quantity of the SPMV model is lower than the lower comfort limit threshold, indicating that the user feels cold. And the larger the absolute value of the difference between the output quantity of the SPMV model and the lower limit threshold value of the comfort degree is, the stronger the cold feeling of the user is.

In a third approach, the decreasing ratio of the user's average heart rate at each sleep stage to the awake period before entering the sleep stage may also be determined by:

f＝C_i·(t-26)+f(26)

wherein f is the decreasing proportion of the average heart rate of the user in each sleep stage to the waking period before entering the sleep stage, and Ci is a third proportionality coefficient, and the numerical value of Ci is associated with the sleep cycle. When the sleep cycle is the first sleep cycle, C₁-0.0086. When the sleep cycle is the second sleep cycle, C₂-0.0203. And t is the indoor temperature, can be obtained by detecting through a temperature sensor associated with the air conditioner, and can also be obtained by acquiring weather information through terminal equipment associated with the air conditioner.

According to the scheme, after the air conditioner obtains the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and the second correction quantity used for correcting the metabolic rate model, the human metabolic rate in the more accurate sleep state can be determined through the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and the second correction quantity used for correcting the metabolic rate model.

Optionally, S22, the air conditioner determining the metabolic rate of the human body in the sleep state according to the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the ratio of the average heart rate of the user in each sleep stage to the decrease of the waking period before the user enters the sleep stage, and a second correction amount for correcting the metabolic rate model, including:

M＝M_B·[1-c(t)·f]

wherein M is the metabolic rate of the human body in the sleep state, M_BThe average basal metabolic rate of the user in the waking period before the sleep stage, c (t) is a second correction quantity, and f is the reduction ratio of the average heart rate of the user in each sleep stage to the waking period before the sleep stage.

In the present embodiment, as can be seen from the above discussion, f ═ C_i(t-26) + f (26). Therefore, it is also possible to deduceThe metabolic rate of the human body in the sleep state is as follows: m is M_B·{1-c(t)·[(t-26)·C_i+f(26)]}. It should be noted that the above formula is not applicable to the calculation of the metabolic rate during the waking period of the second sleep cycle and to the calculation of the metabolic rate in an extremely low temperature or an extremely high temperature environment. According to the scheme, the human body metabolic rate in the sleep state can be determined more accurately through the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage and the second correction quantity for correcting the metabolic rate model.

Alternatively, the second correction amount may be determined by:

C(t)＝kt-z

wherein, C (t) is a second correction amount, k is a second proportionality coefficient, t is the indoor temperature, and z is a second correction constant.

In this embodiment, a plurality of experimental data may be fitted to obtain a calculation formula of the fitted second correction amount. Here, the calculation formula of the fitted second correction amount has good linear correlation. As an example, in goodness of fit R²In the case of 0.99, the second scaling factor k is 0.425, and the second correction constant z is 9.9283. That is, the second correction amount is calculated by the formula c (t) 0.425 t-9.9283. Therefore, the second correction quantity is closely related to the change situation of the indoor temperature. By the scheme, the second correction quantity can be obtained more accurately, and an accurate data basis is provided for the construction process of the human metabolic rate model.

FIG. 3 is a schematic diagram of a method for determining surface coefficients of a clothing article according to an embodiment of the present disclosure; referring to fig. 3, S11, the air conditioner determines the human body metabolic rate and the clothing surface coefficient of the user in the sleep state, including:

s31, the air conditioner obtains the thermal resistance of the bedding and clothing;

and S32, the air conditioner determines the surface coefficient of the bedding and clothing according to the thermal resistance of the bedding and clothing.

Optionally, S32, the air conditioner determining the bedding surface coefficient according to the bedding thermal resistance, including:

f_cl＝0.75(1+0.2I_cl)

wherein f is_clIs the surface coefficient of the bedding and clothing, I_clIs the thermal resistance of the bedding and clothing.

In this embodiment, the thickness and the coverage area of the bedding and clothing are different in different seasons, and accordingly, the thermal resistance of the bedding and clothing is different. Therefore, the air conditioner can determine the bedding surface coefficient by combining the obtained bedding thermal resistance. In another example, the air conditioner can also obtain current season information and an exposed part when the user is in a sleeping state; determining the heat dissipation area of the bedding and clothing according to the current season information; therefore, the surface coefficient of the bedding and clothing is determined according to the exposed part of the user in the sleeping state and the heat dissipation area of the bedding and clothing. Specifically, the air conditioner may determine, as the surface coefficient of the bedding and clothing, a surface coefficient of the bedding and clothing corresponding to an exposed portion and a heat dissipation area of the bedding and clothing when the user is in a sleep state according to a preset correspondence. In another example, the surface coefficients of the bedding pieces may be determined by means of a look-up table. The table to be queried can store the coefficients of the surfaces of the bedding pieces of the users under different bedding pieces. In an optimized scheme, the air conditioner can also obtain the current season information and the exposed area of the user in a sleeping state; determining the heat dissipation area of the bedding and clothing according to the current season information; thereby taking the ratio of the heat dissipation area of the bedding and clothing to the exposed area of the user in the sleeping state as the surface coefficient of the bedding and clothing. In this way, a more accurate surface coefficient of the clothing can be determined in a variety of ways.

Optionally, S12, the air conditioner establishes a PMV model according to the metabolic rate of the human body and the surface coefficient of the bedding and clothing in the sleep state, including:

in this embodiment, M, I_clAnd W respectively represents the metabolic rate, the thermal resistance of the bedding and clothing and the external mechanical work, and the external mechanical work is 0. t is t_aV, H, tr respectively represent the ambient temperature, wind speed, relative humidity and average radiation temperature, and the average radiation temperature tr and the ambient temperature t_aEqual in value。P_a、f_cl、h_c、t_clRespectively representing the water vapor partial pressure, the surface coefficient of the quilt and the clothes, the heat convection coefficient and the temperature of the outer surface of the clothes. Specifically, the partial pressure P of water vapor_aAccording to the determination of the ambient temperature and the relative humidity, the following formula is adopted for calculation:

specifically, the convective heat transfer coefficient is determined according to the ambient temperature, the average radiant temperature and the wind speed, and is specifically calculated by adopting the following formula:

specifically, the temperature of the outer surface of the garment is calculated by adopting the following formula:

t_cl＝35.7-0.0275(M-W)-0.155I_cl[(M-W)-3.05(5.73-0.007(M-W)-P_a)-

0.42{(M-W)-58.15}-0.0173M(5.87-P_a)-0.0014M(34-t_a)]

by the scheme, the air conditioner can establish the PMV model by combining the human body metabolic rate and the bedding and clothing surface coefficient in the sleeping state.

FIG. 4 is a schematic diagram of a method for controlling an air conditioner according to an embodiment of the present disclosure; as shown in fig. 4, an embodiment of the present disclosure provides a method for controlling an air conditioner, including:

and S41, the air conditioner acquires the current sleep state of the user associated with the air conditioner in the sleep stage.

S42, the air conditioner obtains the current comfort value of the user-associated SPMV model. The current comfort value is determined by the SPMV model output.

And S43, executing an environment control strategy corresponding to the current sleep state according to the current sleep state under the condition that the current comfort value is not matched with the preset comfort value by the air conditioner, so that the adjusted current comfort value is matched with the preset comfort value.

In the scheme, the air conditioner can acquire the current sleep state of the user in the sleep stage through the sleep monitoring equipment in communication connection with the air conditioner. As an example, the sleep monitoring device is a sleep pillow, which detects the exercise intensity of the user in the sleep stage and determines the current sleep state of the user according to the exercise intensity. As one example, the sleep monitoring device is a smart watch, and the smart watch is worn on the user's wrist. The smart watch is provided with a gyroscope sensor and a heart rate sensor, the gyroscope sensor is used for detecting the action amplitude and frequency of the wrist, and the heart rate sensor is used for detecting the heart rate value of the user. The smart watch acquires the action amplitude, frequency and heart rate value of the wrist, analyzes and processes the action amplitude, frequency and heart rate value, and generates the current sleep state of the user. As for the way in which the air conditioner acquires the current sleep state of the user in the sleep stage, the embodiment of the present disclosure may not specifically limit this.

Further, the air conditioner obtains the current comfort value of the user-associated SPMV model in the following manner: and acquiring physical sign parameters of the user and environmental parameters of the environment where the user is located. And inputting the physical sign parameters and the environmental parameters into the SPMV model to obtain the output quantity of the SPMV model, and taking the output quantity of the SPMV model as the current comfort value of the user. Wherein, the physical sign parameters comprise metabolic rate and quilt and clothing thermal resistance. The environmental parameters include ambient temperature, wind speed, and relative humidity. It will be appreciated that after the air conditioner has adjusted one or more of the ambient temperature, wind speed, and/or relative humidity, the updated ambient parameters may be input to the SPMV model to enable an update to the comfort value of the user.

By adopting the method for controlling the air conditioner provided by the embodiment of the disclosure, the current comfort value of the user can be accurately obtained through the output quantity of the SPMV model, and when the current comfort value is not matched with the preset comfort value, the environment control strategy corresponding to the current sleep state is executed, so that the output quantity of the SPMV model obtained after regulation and control can be matched with the preset comfort value, and the air conditioner can dynamically regulate and control the environment according to the comfort requirement of the sleep stage of the user. The method improves the accuracy of comfort judgment of the user in the sleep stage, and meets the comfort requirement of the user.

Optionally, at S43, the air conditioner executes an environment control policy corresponding to the current sleep state according to the current sleep state, where the environment control policy includes:

the method comprises the steps that under the condition that a current sleep state represents that a user falls asleep, an air conditioner acquires a sleep transition state of the user and a sleep period associated with the current sleep state; the air conditioner adjusts the temperature, humidity and/or wind speed of the environment associated with the user according to the sleep transition state and the sleep period.

In this embodiment, the sleep transition state indicates that the user switches between adjacent sleep stages within a certain sleep period. The sleep period indicates a sleep cycle in which the user sleeps. A complete sleep cycle consists of a time sequential succession of waking, light, deep and rapid eye movements. The duration of waking, light sleep, deep sleep and rapid eye movements differ among different sleep cycles. Waking, light sleep, deep sleep and rapid eye movements represent different sleep stages. Therefore, the method obtains the sleep transition state and the sleep period of the user in the sleep stage in real time, and correspondingly regulates and controls the temperature, humidity and/or wind speed of the environment where the user is located according to the sleep transition state and the sleep period, so that the output quantity of the SPMV model obtained after regulation and control is within a preset range, and the comfort requirement of the user in the sleep stage is met.

Optionally, when the current comfort value is greater than the comfort upper threshold, the air conditioner adjusts the temperature, humidity, and/or wind speed of the environment associated with the user according to the sleep transition state and the sleep period, including:

and controlling the fan to increase the wind speed under the condition that the sleep transition state represents sleep switching and the sleep period represents a first sleep period. And when the air conditioner is in the second sleep cycle in the sleep period and the sleep transition state indicates that the air conditioner is continuously in the current sleep stage, reducing the temperature value of the environment and controlling the fan to reduce the air speed.

Thus, when a sleep switch is determined and the user is in the first sleep cycle, it is indicated that the user has entered a sleep stage. Through a large number of experiments, compared with the adjustment of the ambient temperature and humidity value, the adjustment of the wind speed can enable the output quantity of the updated SPMV model to be reduced more quickly. Therefore, the air conditioner controls the fan to increase the wind speed under the condition that the user enters the sleep stage, so that the output quantity of the SPMV model is quickly regulated and controlled. And when the user is determined to be continuously in the current sleep stage and the user is in the second sleep cycle, the user is stable in sleep, and the temperature of the user is reduced greatly. In order to reduce the interference of the noise generated by the running of the fan to the sleep of a user, the air conditioner controls the fan to reduce the air speed. Meanwhile, in order to keep the output quantity of the SPMV model within a preset range, the air conditioner regulates and controls the ambient temperature.

Optionally, controlling the wind turbine to increase the wind speed comprises: the fan is controlled to increase from the initial wind speed at a first preset rate of change. Controlling the fan to reduce the wind speed, comprising: controlling the fan to reduce the wind speed at a second preset change rate until the wind speed is reduced to the initial wind speed; wherein the first predetermined rate of change is greater than or equal to 0.3 meters per second and less than or equal to 0.5 meters per second. The second predetermined rate of change is greater than or equal to 0.3 meters per second and less than or equal to 0.5 meters per second.

Thus, the fan may generate noise during operation, particularly in scenarios where the fan is operating at higher wind speeds. In order to reduce the influence of fan operation noise on the sleep of a user, the air conditioner can set a preset air speed range of the air speed of the fan. Meanwhile, in the process of controlling the fan to increase the wind speed and decrease the wind speed, if the increase speed or the decrease speed is too fast, the sleep of the user is influenced. Thus, a first preset rate of change may be set to slow the wind up or down. The preset wind speed range is [0.1,1.2] m/s.

Optionally, when the current comfort value is smaller than the lower comfort threshold, the air conditioner adjusts the temperature, humidity, and/or wind speed of the environment associated with the user according to the sleep transition state and the sleep period, including:

and the air conditioner controls the fan to reduce the wind speed and keep the temperature and humidity value of the environment under the condition that the sleep transition state represents sleep switching and the sleep period represents a first sleep period. And the air conditioner controls the fan to increase the wind speed under the condition that the sleep period represents that the air conditioner is in the second sleep period and the sleep transition state represents that the air conditioner is continuously in the current sleep stage.

Thus, when the current comfort value is smaller than the lower comfort threshold, the output quantity of the SPMV model is low. When the air conditioner determines that the user is in the second sleep period after switching to sleep, the air conditioner can regulate and control the output quantity by reducing the wind speed. Meanwhile, the air conditioner keeps the temperature and humidity value of the environment unchanged. And when the user is determined to be in the second sleep period and the user is continuously in the current sleep stage, the air conditioner controls the fan to increase the wind speed in order to reduce the output quantity of the SPMV model from the lower limit threshold of the comfort level to the preset range.

Optionally, when the current comfort value is smaller than the lower comfort threshold, the air conditioner adjusts the temperature, humidity and/or wind speed of the environment associated with the user according to the sleep transition state and the sleep period, including:

and the air conditioner controls the fan to reduce the wind speed and keep the temperature and humidity value of the environment under the condition that the sleep transition state represents sleep switching and the sleep period represents a first sleep period. And the air conditioner controls the fan to increase the wind speed under the condition that the sleep period represents that the air conditioner is in the second sleep period and the sleep transition state represents that the air conditioner is continuously in the current sleep stage. The air conditioner reacquires a new current comfort value. And the air conditioner controls the temperature of the environment to be reduced by a first preset temperature variation under the condition that the new current comfort value is greater than the comfort upper limit threshold value. And under the condition that the new current comfort value is smaller than the comfort lower limit threshold value, the air conditioner controls the temperature of the environment to rise by a second preset temperature variation and controls the relative humidity of the environment to be within a preset relative humidity range. Wherein the predetermined relative humidity range is [ 50% RH, 65% RH ].

Thus, experiments show that under the condition that the wind speed and the relative humidity are kept unchanged, the variation of the output quantity of the SPMV model is in positive correlation with the variation of the temperature. Specifically, the temperature rises by 1 ℃, and the output rise amplitude of the SPMV model is about 0.5-0.6. The temperature is reduced by 1 ℃, and the output reduction amplitude of the SPMV model is about 0.5-0.6. Based on the above experimental data, when the current comfort value of the air conditioner is greater than the comfort upper limit threshold, the temperature of the environment is controlled to be reduced by a first preset temperature variation, so that the output quantity of the SPMV model is reduced in a small range. When the current comfort value is smaller than the lower limit threshold of the comfort level, the temperature of the control environment rises by the second preset temperature change amount, and the relative humidity of the control environment is within the range of the preset relative humidity, so that the output quantity of the SPMV model is regulated and controlled, and the regulated and controlled relative humidity meets the comfort level requirement of the user.

Optionally, an embodiment of the present disclosure further provides a method for controlling an air conditioner, including:

the air conditioner acquires the current sleep state of a user associated with the air conditioner in a sleep stage; the air conditioner obtains a current comfort value of an SPMV model associated with a user; the air conditioner obtains the priority of the environmental parameters associated with the user under the condition that the current comfort value is not matched with the preset comfort value, wherein the environmental parameters comprise wind speed, relative humidity and temperature, so that the environment associated with the user is regulated and controlled according to the priority of the environmental parameters.

In this embodiment, because the number of factors affecting the output of the SPMV model is large, the air conditioner can preset the priority of the environmental parameter in order to give consideration to the regulation efficiency and the energy consumption of the air conditioner. As an example, the priority is wind speed, relative humidity, temperature from high to low. As another example, the priority is wind speed, temperature, relative humidity from high to low. It can be understood that, since the variation of the output quantity of the SPMV model by the adjusted wind speed is higher than the variation of the output quantity of the SPMV model by the adjusted temperature and humidity, and the rise and fall of the ambient temperature and the relative humidity require time, the wind speed is determined as the highest priority; and the air conditioner executes an environment control strategy corresponding to the current sleep state according to the current sleep state so as to enable the adjusted current comfort value to be matched with the preset comfort level.

By adopting the method for controlling the air conditioner, the accuracy of comfort level judgment of the user in the sleep stage is effectively improved, and the environment regulation and control efficiency of the air conditioner is improved. And reduces energy consumption. It is understood that three types of environmental parameters are wind speed, temperature, and relative humidity. In the actual regulation and control process of the air conditioner, if only one of the environmental parameters is regulated and controlled, the output quantity of the SPMV model cannot fall within the preset comfort level range, and other two environmental parameters can be regulated and controlled or any one of the other two environmental parameters can be regulated and controlled so as to regulate and control the output quantity of the SPMV model. Specifically, the sleep of the user is affected by the large wind speed, so that the preset wind speed range is set to be 0.1-1.2 m/s. The relative humidity is too high or too low, which causes discomfort to the user, and the preset relative humidity range is set to be 40% -70%.

In practical application, the air conditioner is in communication connection with the sleep pillow, and the sleep pillow transmits the current sleep state of the user to the air conditioner in real time. The initial wind speed of the fan is 0.1 m/s. The first predetermined rate of change is 0.3 m/s. The comfort lower threshold and the comfort upper threshold are respectively-0.3 and 0.3. The method for controlling the air conditioner is specifically as follows:

the air conditioner acquires the current environmental parameters and inputs the current environmental parameters into the SPMV model, and the output quantity of the SPMV model is 0.4. Thus, it is determined that the current comfort value is greater than the upper comfort threshold. The air conditioner receives a sleep signal sent by the sleep pillow, and the sleep signal carries a sleep transition state and a current sleep period of a user. The sleep transition state is to perform a sleep handover and the current sleep period is the first sleep cycle. The air conditioner increases the wind speed value by 0.4m/s at a first preset change rate on the basis of the initial wind speed and continuously operates at the wind speed for 5 minutes. And the air conditioner keeps the ambient temperature and humidity unchanged. And the air conditioner receives a new sleep signal sent by the sleep pillow again, the new sleep transition state is not transition, and the new sleep period is a second sleep period. Because the variable quantity of the output quantity of the SPMV model is in positive correlation with the variable quantity of the environment temperature, the air conditioner reduces the temperature value delta T of the environment and controls the fan to reduce the wind speed to the initial wind speed. The output quantity of the air conditioner reacquiring the SPMV model is 0.18. From this, it is determined that the current environmental parameter meets the comfort needs of the user.

FIG. 5 is a schematic diagram of an apparatus for constructing a thermal comfort model according to an embodiment of the present disclosure; as shown in fig. 5, an apparatus for constructing a thermal comfort model according to an embodiment of the present disclosure includes a determining module 51, a building module 52, a calculating module 53, and a constructing module 54. The determination module 51 is configured to determine the human body metabolic rate and the clothing surface coefficient of the user in the sleep state; the establishing module 52 is configured to establish a PMV model according to the human body metabolic rate and the surface coefficient of the bedding and clothing in the sleep state; the calculation module 53 is configured to calculate a first correction amount for correcting the PMV model, and the construction module 54 is configured to construct the SPMV model based on the PMV model and the first correction amount.

By adopting the device for constructing the thermal comfort model provided by the embodiment of the disclosure, after the human body metabolic rate and the bedding and clothing surface coefficient of the user in the sleeping state are determined, the PMV model is established by combining the human body metabolic rate and the bedding and clothing surface coefficient in the sleeping state, and the PMV model is corrected by the calculated first correction amount, so that the SPMV model capable of reflecting the thermal comfort condition of the user in the sleeping state at night is obtained. With this scheme, solved current PMV model and can not characterize the drawback of the thermal comfort degree condition of user under the sleep state at night, promoted the accuracy that the thermal comfort degree of user sleep stage judged, for the user carries out air conditioner control under the sleep state and provides accurate data basis, satisfy the demand of user thermal comfort degree.

Fig. 6 is a schematic diagram of another apparatus for constructing a thermal comfort model according to an embodiment of the disclosure; as shown in fig. 6, an apparatus for constructing a thermal comfort model according to an embodiment of the present disclosure includes a processor (processor)100 and a memory (memory) 101. Optionally, the apparatus may also include a Communication Interface (Communication Interface)102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other via a bus 103. The communication interface 102 may be used for information transfer. The processor 100 may invoke logic instructions in the memory 101 to perform the method for building a thermal comfort model of the above embodiments.

In addition, the logic instructions in the memory 101 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products.

The memory 101, which is a computer-readable storage medium, may be used for storing software programs, computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes functional applications and data processing, i.e. implements the method for building a thermal comfort model in the above embodiments, by executing program instructions/modules stored in the memory 101.

The memory 101 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. In addition, the memory 101 may include a high-speed random access memory, and may also include a nonvolatile memory.

The embodiment of the disclosure provides an air conditioner, which comprises the device for constructing the thermal comfort model.

By adopting the air conditioner provided by the embodiment of the disclosure, after the human body metabolic rate and the bedding and clothing surface coefficient of the user in the sleeping state are determined, the PMV model is established by combining the human body metabolic rate and the bedding and clothing surface coefficient in the sleeping state, and the PMV model is corrected by the calculated first correction amount, so that the SPMV model capable of reflecting the thermal comfort condition of the user in the sleeping state at night is obtained. With this scheme, solved current PMV model and can not characterize the drawback of the thermal comfort degree condition of user under the sleep state at night, promoted the accuracy that the thermal comfort degree of user sleep stage judged, for the user carries out air conditioner control under the sleep state and provides accurate data basis, satisfy the demand of user thermal comfort degree.

Embodiments of the present disclosure provide a computer-readable storage medium having stored thereon computer-executable instructions configured to perform the above-described method for constructing a thermal comfort model.

Embodiments of the present disclosure provide a computer program product comprising a computer program stored on a computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the above-described method for building a thermal comfort model.

The computer-readable storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.

The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes, and may also be a transient storage medium.

The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.

Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Claims

1. A method for constructing a thermal comfort model, comprising:

determining the human body metabolic rate and the bedding and clothing surface coefficient of a user in a sleeping state;

establishing a PMV model according to the human body metabolic rate and the bedding and clothing surface coefficient in the sleeping state;

calculating a first correction amount for correcting the PMV model;

and constructing the SPMV model according to the PMV model and the first correction quantity.

2. The method of claim 1, wherein constructing the SPMV model based on the PMV model and the first correction quantity comprises:

SPMV＝PMV+b(t)

wherein b (t) is a first correction amount.

3. The method of claim 1, wherein calculating a first correction amount for correcting the PMV model comprises:

b(t)＝at-c

4. The method of claim 1, wherein determining the human body metabolic rate of the user in the sleep state comprises:

obtaining the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the descending proportion of the average heart rate of the user in each sleep stage to the waking period before the user enters the sleep stage, and a second correction quantity for correcting a metabolic rate model;

and determining the human body metabolic rate in the sleep state according to the average basal metabolic rate of the user in the waking period before the sleep stage, the reduction ratio of the average heart rate of the user in each sleep stage to the waking period before the sleep stage and a second correction quantity for correcting the metabolic rate model.

5. The method of claim 4, wherein determining the metabolic rate of the human body in the sleep state according to the average basal metabolic rate of the user in the waking period before the user enters the sleep stage, the ratio of the average heart rate of the user in each sleep stage to the decrease of the user in the waking period before the user enters the sleep stage, and a second correction amount for correcting the metabolic rate model comprises:

M＝M_B·[1-c(t)·f]

6. The method of claim 5, wherein the second correction amount is determined by:

C(t)＝kt-z

7. The method of claim 1, wherein determining the surface coefficients of the clothing comprises:

f_cl＝0.75(1+0.2I_cl)

8. The method of claim 1, wherein establishing a PMV model based on the metabolic rate of the human body and the surface coefficients of the bedding and clothing in the sleep state comprises:

wherein M is the metabolic rate of the human body in the sleep state, W is the external mechanical work, P_aIs the partial pressure of water vapor, t_aIs the ambient temperature, f_clIs the coefficient of the surface, t_clIs the temperature of the outer surface of the garment, h_cIs the convective heat transfer coefficient.

9. An apparatus for constructing a thermal comfort model, comprising a processor and a memory having stored program instructions, characterized in that the processor is configured to perform the method for constructing a thermal comfort model according to any of claims 1 to 8 when executing the program instructions.

10. A storage medium storing program instructions, characterized in that the program instructions, when executed, perform a method for constructing a thermal comfort model according to any of claims 1 to 8.