Method and apparatus for controlling air conditioner, air conditioner, storage medium

Abstract

The application relates to the technical field of air conditioners, and discloses a method for controlling an air conditioner, which comprises the following steps: acquiring a current comfort value of an SPMV model associated with a sleep stage of a user; and controlling operation parameters of a fresh air mode associated with the air conditioner according to a matching condition of the comfort value and a preset comfort value. The method can regulate the oxygen content of an environment where the user is located, and improve the comfort of the user in the sleep stage. The application further discloses a device for controlling an air conditioner, an air conditioner and a storage medium.

Description

Technical Field

[0001] This application relates to the field of air conditioner technology, such as a method and apparatus for controlling an air conditioner, an air conditioner, and a storage medium. Background Technology

[0002] Currently, users can get sufficient rest during sleep, and the quality of sleep has a significant impact on their subsequent work and health. While sleeping, users are affected by external environmental factors such as temperature, humidity, light intensity, and noise. To meet users' comfort needs during sleep, air conditioners have sleep modes, which typically regulate indoor temperature.

[0003] Because the sleeping environment is relatively enclosed, the oxygen levels in the enclosed sleeping environment are not very stable when the user is in a state of sleep for a long time. Unstable oxygen levels will have a negative impact on the user's sleep.

[0004] In the process of implementing the embodiments of this disclosure, at least the following problems were found in the related art:

[0005] Sleep mode lacks the ability to regulate the amount of oxygen in the sleep environment, affecting the user's comfort during sleep. Summary of the Invention

[0006] 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.

[0007] This disclosure provides a method, apparatus, air conditioner, and storage medium for controlling an air conditioner to regulate the oxygen level in the user's environment and improve the user's comfort during sleep.

[0008] In some embodiments, the method includes: obtaining the current comfort value of the SPMV model associated with the user during the sleep stage; and controlling the operating parameters of the fresh air mode associated with the air conditioner based on the matching of the comfort value with a preset comfort value.

[0009] In some embodiments, the apparatus includes a processor and a memory storing program instructions, wherein the processor is configured to, when executing the program instructions, perform the aforementioned method for controlling an air conditioner.

[0010] In some embodiments, the air conditioner includes, as described above, a means for controlling the air conditioner.

[0011] In some embodiments, the storage medium stores program instructions that, when executed, perform the aforementioned method for controlling an air conditioner.

[0012] The method, apparatus, air conditioner, and storage medium for controlling an air conditioner provided in this disclosure can achieve the following technical effects:

[0013] The air conditioner controls the operating parameters of the fresh air mode based on the matching between the current comfort value determined by the SPMV model and the preset comfort value, thereby regulating the oxygen content of the user's sleep environment and effectively improving the user's comfort during sleep.

[0014] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0015] 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:

[0016] Figure 1 This is a schematic diagram of a method for controlling an air conditioner provided in an embodiment of this disclosure;

[0017] Figure 2 This is a schematic diagram of another method for controlling an air conditioner provided in an embodiment of this disclosure;

[0018] Figure 3 This is a schematic diagram of another method for controlling an air conditioner provided in an embodiment of this disclosure;

[0019] Figure 4 This is a schematic diagram of another method for controlling an air conditioner provided in an embodiment of this disclosure;

[0020] Figure 5 This is a schematic diagram of a method for constructing a thermal comfort model provided in an embodiment of this disclosure;

[0021] Figure 6 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.

[0022] Figure 7 This is a schematic diagram of a method for determining the surface coefficient of clothing provided in an embodiment of this disclosure;

[0023] Figure 8 This is a schematic diagram of a device for controlling an air conditioner provided in an embodiment of this disclosure;

[0024] Figure 9This is a schematic diagram of another device for controlling an air conditioner provided in an embodiment of this disclosure. Detailed Implementation

[0025] 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.

[0026] 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.

[0027] Unless otherwise stated, the term "multiple" means two or more.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] In the disclosed embodiments, the terminal device refers to an electronic device with wireless connectivity. The terminal device can communicate with the aforementioned smart home appliances via 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.

[0033] Combination Figure 1 As shown in the embodiments of this disclosure, a method for controlling an air conditioner is provided, comprising:

[0034] S01, the air conditioner obtains the current comfort value of the SPMV model associated with the user during the sleep stage.

[0035] S02, the air conditioner controls the operating parameters of the associated fresh air mode based on the matching of the comfort value and the preset comfort value.

[0036] The method for controlling an air conditioner provided in this disclosure controls the operating parameters of the fresh air mode based on the matching between the current comfort value determined by the SPMV model and the preset comfort value, thereby regulating the oxygen content of the user's sleep environment and effectively improving the user's comfort during sleep.

[0037] Optionally, the preset comfort value can be a fixed value, or it can include an upper comfort threshold and a lower comfort threshold. When the preset comfort value is fixed, the comfort value matches the preset comfort value, meaning the comfort value is equal to the preset comfort value. The comfort value does not match the preset comfort value, meaning the comfort value is not equal to the preset comfort value. When the preset comfort value includes an upper comfort threshold and a lower comfort threshold, the comfort value matches the preset comfort value, meaning the preset comfort value is within a preset range. The comfort value does not match the preset comfort value, meaning the preset comfort value is outside the preset range. The preset range is [lower comfort threshold, upper comfort threshold]. The upper comfort threshold can be 0.3, and the lower comfort threshold can be -0.3. Alternatively, the upper comfort threshold can be 0.5, and the lower comfort threshold can be -0.5. Understandably, since users' comfort needs vary during sleep, the upper and lower comfort thresholds can be set according to the user's comfort needs during sleep.

[0038] Optional, combined Figure 2As shown, when the air conditioner determines that the user has entered a sleep state, it controls the operating parameters of the associated fresh air mode based on the matching between the comfort value and the preset comfort value, including:

[0039] S11: When the current comfort value does not match the preset comfort value, the air conditioner obtains the user's current sleep stage.

[0040] In this step, the air conditioner can obtain the user's current 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 the sleep-onset phase and determines the user's current sleep stage 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. 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 stage. This embodiment of the disclosure does not specifically limit the method by which the air conditioner obtains the user's current sleep stage during the sleep-onset phase.

[0041] S12, the air conditioner adjusts the fresh air volume according to the user's current sleep stage.

[0042] Thus, the user's sleep stages include wakefulness, light sleep, deep sleep, and REM sleep. The oxygen requirements of the sleep environment vary depending on the user's sleep stage. Therefore, the air conditioner obtains the user's current sleep stage and matches the corresponding fresh air volume accordingly, adjusting the fresh air volume accordingly.

[0043] Optional, combined Figure 3 As shown, the air conditioner adjusts the fresh air volume according to the user's current sleep stage, including:

[0044] S21, when the air conditioner is in a light sleep stage, control the air conditioner to run at the first airflow rate.

[0045] S22, when the air conditioner is in deep sleep, control the air conditioner to operate at the second airflow rate.

[0046] S23, when the air conditioner is in the REM sleep stage, the fresh air volume is reduced.

[0047] The first air volume is less than the second air volume.

[0048] Thus, compared to deep sleep, users require less oxygen during light sleep. Therefore, different airflow rates are configured for light and deep sleep. Furthermore, REM sleep and deep sleep occur sequentially, and users are more sensitive to ambient noise during REM sleep. Therefore, the air conditioner reduces the fresh airflow to avoid noise from the fan affecting the user's sleep. Thus, the air conditioner reduces the fresh airflow when the user is in REM sleep. This reduction can be done by lowering the fresh airflow level or even reducing it to zero.

[0049] Specifically, the first air volume is greater than or equal to 15m³. 3 / h (cubic meters per hour) and less than or equal to 20m 3 / h. The second air volume is greater than or equal to 30m³ / h. 3 / h.

[0050] In practical applications, when the air conditioner determines that the user is in a light sleep stage, it controls the air conditioner to operate at 18m. 3 The air conditioner operates at / h. When it determines that the user is in deep sleep, it controls the airflow to increase to 30m. 3 The air conditioner operates at / h. When it determines that the user is in the REM (Rapid Eye Movement) phase, it shuts off the fan.

[0051] Combination Figure 4 As shown in the embodiments of this disclosure, a method for controlling an air conditioner is also provided, comprising:

[0052] S31, when the air conditioner determines that the user has fallen asleep, it controls the air conditioner to turn off the fresh air mode and controls the fan to run at the lowest air volume.

[0053] S32, the air conditioner obtains the current comfort value of the SPMV model associated with the user during the sleep stage.

[0054] S33, the air conditioner controls the operating parameters of the associated fresh air mode based on the matching of the comfort value and the preset comfort value.

[0055] Using the method for controlling an air conditioner provided in this disclosure, the user is in the sleep-inducing stage before entering sleep mode. After entering sleep mode, the user will be affected by indoor noise in their environment. When the indoor noise is high, the user is very likely to switch from sleep to wakefulness. To avoid indoor noise affecting the user's sleep, the air conditioner controls the shut-off of the fresh air mode and controls the fan to operate at the lowest airflow, thereby improving the user's sleep comfort during the sleep-inducing stage.

[0056] Optionally, Figure 5 This is a schematic diagram of a method for constructing a thermal comfort model provided in an embodiment of this disclosure; combined with Figure 5As shown, the SPMV model for the air conditioner is determined in the following manner:

[0057] S41, the air conditioner determines the user's metabolic rate and the surface coefficient of the clothing while the user is sleeping.

[0058] S42, the air conditioner establishes a PMV (Predicted Mean Vote) model based on the human metabolic rate and the surface coefficient of clothing during sleep.

[0059] S43, the air conditioner calculates the first correction amount used to correct the PMV model.

[0060] S44, the air conditioner constructs an SPMV model based on the PMV model and the first correction.

[0061] 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 average basal metabolic rate of the user during wakefulness before falling asleep and a second correction factor used to modify 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 ​​clothing also differs. Further, after determining the user's metabolic rate and surface coefficient of clothing during sleep, the air conditioner can establish a PMV model combining these two factors, which can characterize the user's thermal comfort during nighttime sleep to a certain extent. Further, to construct a more accurate SPMV model that characterizes the user's thermal comfort during nighttime sleep, a first correction factor used to modify the PMV model needs to be calculated. Here, the first correction factor is a temperature correction factor, which the air conditioner uses to correct fluctuations in the PMV model caused by changes in ambient temperature. In this way, after the air conditioner calculates the first correction amount used to correct the PMV model, the PMV model and the first correction amount can be combined to construct a more accurate SPMV model that can characterize the user's thermal comfort during nighttime sleep.

[0062] In this way, after determining the human metabolic rate and bedding surface coefficient during sleep, a PMV model is established by combining the human metabolic rate and bedding surface coefficient during the sleep state. The PMV model is then corrected using a calculated first correction factor to obtain a SPMV model that reflects the user's thermal comfort during nighttime sleep. This approach overcomes the limitation of existing PMV models in failing to characterize the user's thermal comfort during nighttime sleep, improves the accuracy of thermal comfort assessment during sleep, and provides an accurate data foundation for air conditioner control during sleep, thus meeting the user's thermal comfort needs.

[0063] Optionally, the air conditioner constructs an SPMV model based on the PMV model and the first correction factor, including:

[0064] SPMV = PMV + b(t)

[0065] Where b(t) is the first correction value.

[0066] In this scheme, the air conditioner can combine the PMV model and the first correction factor to construct 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:

[0067]

[0068] 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.

[0069] 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.

[0070] Optionally, the air conditioner calculates a first correction amount for revising the PMV model, including:

[0071] b(t) = at - c

[0072] 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.

[0073] 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... 2 With 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.

[0074] Figure 6 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 6 As shown, optionally, the air conditioner determines the user's metabolic rate during sleep, including:

[0075] S51, 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.

[0076] S52, 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.

[0077] 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:

[0078] 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.

[0079] 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.

[0080] Table 1

[0081] 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％

[0082] Table 2

[0083] female 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％

[0084] 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.

[0085] 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:

[0086] f = C i ·(t-26)+f(26)

[0087] 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.

[0088] This approach allows for the determination of a more accurate human metabolic rate during sleep by obtaining the user's average basal metabolic rate during the waking period before entering sleep, the user's average heart rate during each sleep stage and the percentage decrease in heart rate during the waking period before entering sleep, and the second correction factor used to modify the metabolic rate model.

[0089] Optionally, 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:

[0090] M = M B ·[1-c(t)·f]

[0091] 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.

[0092] 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 sleep can be determined by 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 the second correction amount used to correct the metabolic rate model.

[0093] In the aforementioned embodiments, when the user is in the sleep stage, 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 is 1. Therefore, the user's metabolic rate during sleep can be calculated using the following formula: M = M B ·[1-c(t)].

[0094] Alternatively, the second correction amount can be determined in the following way:

[0095] C(t) = kt - z

[0096] 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.

[0097] 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 When the value is 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).

[0098] =0.425t - 9.9283. This shows that the second correction factor is closely related to changes in indoor temperature. This method allows for a more accurate second correction factor, providing a reliable data foundation for constructing the human metabolic rate model.

[0099] Figure 7 This is a schematic diagram of a method for determining the surface coefficient of clothing provided in an embodiment of this disclosure; combined with Figure 7 As shown, the air conditioner determines the user's metabolic rate and the surface coefficient of clothing during sleep, including:

[0100] S61, the air conditioner obtains the thermal resistance of the clothing.

[0101] S62, the air conditioner determines the surface coefficient of the clothing based on the thermal resistance of the clothing.

[0102] Optionally, S62, the air conditioner determines the surface coefficient of the clothing based on the thermal resistance of the clothing, including:

[0103] f cl =0.75(1+0.2I) cl )

[0104] Among them, f cl I is the surface coefficient of the clothing. cl For thermal resistance of clothing.

[0105] 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 corresponding to the exposed area of ​​the user while sleeping and the heat dissipation area of ​​the bedding according to a preset correspondence. 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 corresponding to the user in different seasons. 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 corrected bedding surface coefficient. This allows for the determination of more accurate fabric surface coefficients through various methods.

[0106] Specifically, the air conditioner establishes a PMV model based on the human metabolic rate and the surface coefficient of clothing during sleep, including:

[0107]

[0108] 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. Specifically, the partial pressure of water vapor P... a Based on ambient temperature and relative humidity, the following formula is used for calculation:

[0109]

[0110] 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:

[0111]

[0112] Specifically, the outer surface temperature of clothing is calculated using the following formula:

[0113] t cl =35.7 - 0.0275 (MW) - 0.155 I cl [(MW)-3.05(5.73-0.007(MW)-P a )-

[0114] 0.42{(MW)-58.15}-0.0173M(5.87-P a -0.0014M(34-t) a )]

[0115] With this approach, the air conditioner can combine the human metabolic rate during sleep with the surface coefficient of bedding to establish a PMV model.

[0116] Combination Figure 8 As shown, this embodiment of the disclosure provides an apparatus for controlling an air conditioner, including an acquisition module 21 and an execution module 22. The acquisition module 21 is configured to acquire the current comfort value of the SPMV model associated with the user during the sleep stage; the execution module 22 is configured to control the operating parameters of the fresh air mode associated with the air conditioner based on the matching of the comfort value with a preset comfort value.

[0117] Using the device for controlling an air conditioner provided in this embodiment, the air conditioner controls the operating parameters of the fresh air mode based on the matching of the current comfort value determined by the SPMV model with the preset comfort value, thereby regulating the oxygen content of the user's sleep environment and effectively improving the user's comfort during sleep.

[0118] Combination Figure 9 As shown, this disclosure provides an apparatus for controlling an air conditioner, 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 controlling the air conditioner described in the above embodiment.

[0119] 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.

[0120] 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 controlling the air conditioner in the above embodiments.

[0121] 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.

[0122] This disclosure provides an air conditioner that includes the above-described device for controlling the air conditioner.

[0123] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described method for controlling an air conditioner.

[0124] 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 controlling an air conditioner.

[0125] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 controlling an air conditioner, characterized in that, include: Obtain the current comfort value of the SPMV model associated with the user during the sleep stage; Based on the matching between the comfort value and the preset comfort value, the operating parameters of the fresh air mode associated with the air conditioner are controlled; Wherein, when it is determined that the user has entered a sleep state, controlling the operating parameters of the air conditioner's associated fresh air mode based on the matching of the comfort value and the preset comfort value includes: If the current comfort value does not match the preset comfort value, the user's current sleep stage is obtained; Adjust the fresh air volume of the air conditioner according to the user's current sleep stage; The SPMV model is determined as follows: Determine the user's metabolic rate and the surface coefficient of the clothing during sleep; A PMV model is established based on the human metabolic rate and back surface coefficient during the sleep state. Calculate the first correction amount used to correct the PMV model; Based on the PMV model and the first correction amount, construct the SPMV model; The step of constructing the SPMV model based on the PMV model and the first correction amount includes: SPMV = PMV + b(t) Where b(t) is the first correction amount; The calculation of the first correction amount used to correct the PMV model includes: b(t) = at - c Where a is the first proportionality coefficient, t is the indoor temperature, and c is the first correction constant.

2. The method according to claim 1, characterized in that, Adjusting the fresh air volume of the air conditioner according to the user's current sleep stage includes: When the current sleep stage indicates that the person is in a light sleep stage, the air conditioner is controlled to operate at a first airflow rate. When the current sleep stage indicates that the person is in deep sleep, the air conditioner is controlled to operate at the second airflow rate. If the current sleep stage indicates that the patient is in the REM sleep stage, reduce the fresh air volume. Wherein, the first air volume is less than the second air volume.

3. The method according to claim 1, characterized in that, Before obtaining the current comfort value of the SPMV model associated with the user during the sleep stage, the method further includes: Once it is determined that the user has fallen asleep, the air conditioner is controlled to turn off the fresh air mode and the fan is controlled to run at the lowest airflow.

4. The method according to claim 1, characterized in that, Determining the user's metabolic rate during sleep includes: 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 for correcting the metabolic rate model are obtained. The metabolic rate of the human body during sleep is determined based on the average basal metabolic rate of the user during the waking period before entering the sleep stage, the decrease ratio of the user's average heart rate during each sleep stage to the waking period before entering the sleep stage, and a second correction amount used to correct the metabolic rate model.

5. A device for controlling an air conditioner, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute, when running the program instructions, the method for controlling an air conditioner as described in any one of claims 1 to 4.

6. An air conditioner, characterized in that, Includes the device for controlling an air conditioner as described in claim 5.

7. A storage medium storing program instructions, characterized in that, When the program instructions are executed, they perform the method for controlling an air conditioner as described in any one of claims 1 to 4.

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