Air conditioner sleep temperature control method, control device and air conditioner

Abstract

The application provides an air conditioner sleep temperature control method, a control device and an air conditioner, and relates to the technical field of air conditioners. The method comprises the following steps: determining a reference parameter when a user is awake, wherein the reference parameter comprises a reference indoor temperature and reference limb characteristics and reference body surface characteristics of the user; acquiring a current operating parameter, wherein the current operating parameter comprises a current indoor temperature and current limb characteristics and current body surface characteristics of the user; determining a stage in which the user is currently located according to the current operating parameter and the reference parameter, and performing corresponding temperature adjustment according to the determined stage. The method can accurately identify the stage in which the user is located, thereby ensuring that the temperature adjustment effect of the air conditioner on the corresponding stage is adapted to the actual temperature adjustment effect required by the user, and improving the use comfort of the user.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more specifically, to an air conditioning sleep temperature control method, control device, and air conditioner. Background Technology

[0002] With the continuous improvement of residents' quality of life and the popularization of the concept of healthy sleep, sleep quality has become a core life indicator of concern to the public.

[0003] When using an air conditioner, users generally experience two phases: wakefulness and sleep. The sleep phase can be further divided into the stage of falling asleep, light sleep, and deep sleep. Users' temperature sensitivity and needs vary at each stage. Therefore, some air conditioners are equipped with a recognition module that can identify the user's current stage and adjust the temperature accordingly to improve user comfort.

[0004] However, existing air conditioners have low accuracy in identifying the user's stage of life, which can easily lead to misidentification of the stage. This results in a difference between the air conditioner's effect on indoor temperature regulation and the temperature regulation effect required by the user, thereby reducing the user's comfort. Summary of the Invention

[0005] The present invention aims to provide an air conditioning sleep temperature control method, control device, and air conditioner to solve the technical problem that existing air conditioners have low accuracy in identifying the user's current stage, which easily leads to stage misidentification. This results in a difference between the air conditioner's temperature regulation effect on the indoor temperature and the temperature regulation effect required by the user, thereby reducing the user's comfort.

[0006] To address the above problems, this invention provides an air conditioner sleep temperature control method, comprising: Determine the baseline parameters for the user when they are awake, including the baseline indoor temperature, the user's baseline limb characteristics, and the baseline body surface characteristics. Obtain current operating parameters, including current indoor temperature and the user's current limb characteristics and current body surface characteristics; The user's current stage is determined based on the current operating parameters and the baseline parameters, and the temperature is adjusted accordingly based on the determined stage.

[0007] The air conditioning sleep temperature control method provided by this invention determines the parameters of the user in a waking state from different perspectives as benchmark parameters, thereby obtaining benchmark parameters that are adapted to individual user differences and can be evaluated from multiple angles. Furthermore, based on the characterization of the user's activity and existence states according to the current operating parameters, and by comparing the current operating parameters with the benchmark parameters when the user is in a certain state, the current stage of the user can be identified and determined from multiple angles. Specifically, the current indoor temperature can be compared with the benchmark indoor temperature to identify whether the user's current indoor environment is a temperature-comfortable environment, and whether this indoor environment will affect the user's limb characteristics and body surface characteristics, thus determining the current limb characteristics. The accuracy of characterizing the user's activity state using features and current body surface features is enhanced. This includes effectively identifying the user's current external activity state through current limb movement amplitude and frequency; identifying the user's internal respiratory state by comparing the current respiratory rate standard deviation with the baseline respiratory rate standard deviation; identifying the user's internal body temperature state by comparing the current body surface temperature with the baseline body surface temperature; and identifying the user's external physical state through the current body surface contour area. By combining these multiple perspectives simultaneously, the accuracy of identifying the user's current stage is improved, ensuring that the air conditioner's temperature regulation effect at the corresponding stage matches the user's actual temperature regulation needs, thus improving user comfort.

[0008] Optionally, limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine whether the current indoor temperature deviates from the baseline indoor temperature by less than the preset room temperature range; If so, and the user's current limb movement amplitude is micro-movement, the current limb movement frequency is reduced, and the current body surface temperature fluctuates slightly, then the user's current stage is determined to be the sitting stage. If not, and the ratio of the user's current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range, then the user is determined to be in the sitting meditation stage.

[0009] Optionally, limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine if the following conditions are met: the user's current limb movement is a continuous large-amplitude movement, or the current limb movement is a micro-movement, and the current limb movement frequency is greater than the preset sleep frequency; the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range; and the current body surface temperature deviates from the baseline body surface temperature by less than the preset sleep temperature range. If so, then the user is currently in the sleep stage.

[0010] Optionally, limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine whether the following conditions are met: the user's current limb movement amplitude is small, the current limb movement frequency fluctuates, the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is within a preset ratio range, and the fluctuation amplitude of the current body surface temperature is less than the preset light sleep body temperature amplitude. If so, then the user is currently in a light sleep stage.

[0011] Optionally, limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine if the following conditions are met: The ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is less than the lower limit of the preset ratio range; In the initial stage, the user's current limb movement amplitude gradually decreases, and the ratio of the current limb movement frequency to the baseline limb movement frequency remains within a preset frequency ratio range; and, In the later stage, the decrease in the user's current body surface temperature compared to the reference body surface temperature is the current decrease rate, and the decrease in the current body surface temperature compared to the reference body surface temperature during the historical deep sleep stage is the historical decrease rate. The ratio of the current decrease rate to the historical decrease rate is greater than the preset deep sleep ratio. If so, then the user is currently in a deep sleep stage.

[0012] Optionally, limb features include limb tilt angle, and body surface features include body surface contour area; the step of determining the user's current stage based on the current operating parameters and the reference parameters includes: Determine whether the following conditions are met: the increase angle of the user's current limb tilt angle is greater than the first preset angle, and the current body surface area is reduced by at least the first preset body surface percentage. If so, then the user is currently in the out-of-bed stage; And / or, determine whether the following conditions are met: the user's current body surface area increases by at least a second preset body surface percentage, and the current limb tilt angle decreases by more than a second preset angle; If so, then the user is currently in the bed-back stage.

[0013] Optionally, the method further includes: Obtain the change in outdoor temperature relative to the current outdoor temperature over a future preset time period; The target temperature for adjusting the indoor environment is adjusted based on the change in outdoor temperature.

[0014] Optionally, the step of correcting the target temperature of the indoor environment based on the change in outdoor temperature includes: The temperature correction amount is calculated according to the following formula, and the sum of the current target temperature and the temperature correction amount is taken as the new target temperature: T target = α· T outdoor ; In the formula, T target α is the temperature correction amount, in °C; α is the first empirical coefficient, dimensionless. T outdoor The outdoor temperature change over a predetermined period of time, expressed in °C.

[0015] Optionally, the step of obtaining the change in outdoor temperature over a preset future time period relative to the current outdoor temperature includes: Obtain the indoor temperature change over a preset time period, and calculate the outdoor temperature change using the following formula: T outdoor = β· T room ; In the formula, T outdoor The outdoor temperature change over a predetermined period of time is expressed in °C; β is the second empirical coefficient, which is dimensionless. T room This represents the change in indoor temperature over a previously preset time period, expressed in °C.

[0016] Optionally, the body surface temperature of the said body surface feature can be calculated according to the following formula: T skin =T sc ·γ+T est ·(1-γ); in, T est = Tsc + (T sc - T room )·R clo / R air ; In the formula, T skin Body surface temperature, in °C; T sc γ represents the target measured temperature, in °C; γ is the confidence level, dimensionless; T est Temperature compensation for bedding, in °C; T room R represents the current indoor temperature in °C. clo Thermal resistance of bedding, in meters (m). 2 ·K / W; R air The thermal resistance for indoor natural convection heat transfer is expressed in meters (m). 2 K / W; in: If the proportion of the user's exposed facial area is greater than or equal to the first preset exposed percentage, the temperature of the exposed area of ​​the user's face is detected as the target measured temperature, and the confidence level is 1. And / or, if the proportion of the user's exposed facial area is less than the first preset exposure percentage, and at least one of the user's neck and hands is used as an auxiliary detection part, and the proportion of the exposed area of ​​the auxiliary detection part is greater than or equal to the second preset exposure percentage, then the temperature of the exposed area of ​​the auxiliary temperature measuring part is detected as the target measured temperature, and the confidence level is (0.5, 0.7]. And / or, if the proportion of the user's exposed face area is less than the first preset exposure percentage, and the proportions of the user's exposed neck and hands are both less than the second preset exposure percentage, then the temperature of the bedding is taken as the target measured temperature, and the confidence level is (0.3, 0.5).

[0017] Optionally, the body surface characteristics include body surface temperature; the method further includes: If the number of users is greater than or equal to 2, then obtain the current location of each user; Calculate the distance between two adjacent users based on the current location, and calculate the maximum body surface temperature difference between users based on the current body surface temperature of each user. Determine if the following conditions are met: The spacing is less than the preset spacing; or the maximum body surface temperature difference is less than the preset temperature difference; or the user's body surface detection area is completely blocked; or the user is located outside the air supply range. If so, then execute the undifferentiated air supply mode; If not, then a differentiated air supply mode will be executed: the air supply direction will be directed towards the user with the highest current body surface temperature.

[0018] The present invention also provides a control device capable of performing the above method, the control device comprising: Acquisition module: Used to obtain current running parameters; The determination module is used to determine the baseline parameters when the user is awake, and to determine the current stage of the user based on the current operating parameters and the baseline parameters; Control module: Used to adjust the temperature accordingly based on the determined stage.

[0019] The present invention also provides an air conditioner, including a computer-readable storage medium storing a computer program and a controller, wherein the computer program is read and executed by the controller to implement the above-described method. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0021] Figure 1 This is a first flowchart of the air conditioner sleep temperature control method provided by the present invention; Figure 2 This is a second flowchart of the air conditioner sleep temperature control method provided by the present invention; Figure 3 The third flowchart of the air conditioner sleep temperature control method provided by the present invention; Figure 4 This is a schematic diagram of the control device provided in an embodiment of the present invention.

[0022] Explanation of reference numerals in the attached figures: 41-Acquisition module; 42-Determination module; 43-Control module. Detailed Implementation

[0023] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0024] The air conditioning sleep temperature control method provided by this invention utilizes an air conditioner whose identification module can identify indoor temperature, limb characteristics, and body surface characteristics of the user in the sleep area during operation. Limb characteristics may include limb movement amplitude, limb movement frequency, respiratory rate standard deviation, and limb tilt angle. Body surface characteristics may include body surface temperature and body surface contour area. Specifically, the identification module may include a millimeter-wave radar sensor and an infrared thermal imaging sensor arranged on the air conditioner. The radar sensor is arranged at the lower part of the air conditioner panel, tilted downwards at 15°~30° to reduce high-level blind spots, and can identify the limb characteristics of the user in the sleep area. Its radar signal processing employs adaptive clutter filtering, which can separate the air conditioner compressor vibration frequency band (typically 20~200Hz) from the human breathing / body movement frequency band (0.1~2Hz), reducing vibration interference. The infrared thermal imaging sensor can collect the body surface contour area of ​​the user in the sleep area, the temperature of the bedding in the sleep area, and the body surface temperature of exposed areas of the user in the sleep area, such as the face, neck, and hands, and mark the confidence level related to the body surface temperature based on the actual situation of the user's exposed areas. Specifically, the average temperature of the exposed area of ​​region (ROI) can be extracted as the temperature detection value using a human posture recognition algorithm.

[0025] Figure 1 This is a first flowchart of the air conditioner sleep temperature control method provided by the present invention.

[0026] like Figure 1 As shown, the air conditioner sleep temperature control method includes the following steps: S102 determines the baseline parameters when the user is awake. The baseline parameters include the baseline indoor temperature, the user's baseline limb characteristics, and the baseline body surface characteristics.

[0027] During use, when users are in the same cooling or heating mode, the indoor temperature can represent the ambient temperature of the user's environment. Ambient temperature has a certain impact on the user's limb and body surface characteristics. The amplitude and frequency of limb movements can represent the user's external activity state from the perspective of external limb activity, while the standard deviation of respiratory rate can represent the user's internal activity state from the perspective of internal limb activity. Body surface temperature can represent the user's internal activity state from the perspective of body temperature, while body surface contour area can represent the user's external activity state from the contour area of ​​the user's sleeping area, such as the area where the bed is located. At different stages, the performance of various parameters of the user's limb and body surface characteristics varies. By collecting the above-mentioned multiple parameters and determining the parameters of the user in the waking state from different perspectives as the baseline parameters, a baseline parameter that is adapted to the individual differences of the user and can be evaluated from multiple perspectives can be obtained.

[0028] Specifically, during air conditioner operation, the recognition module can identify whether the user is conscious and awake. If the user is conscious, the average indoor temperature over a preset time period is collected as the baseline indoor temperature. The average values ​​of limb characteristics such as limb movement amplitude, limb movement frequency, respiratory rate standard deviation, and limb tilt angle are collected as baseline limb characteristics. The average values ​​of body surface temperature and body surface area are collected as baseline body surface characteristics. Furthermore, preferably, after the air conditioner stabilizes during its initial operation, it can intelligently collect relevant data for 20-40 minutes (specifically 30 minutes), process this data, and use it as the baseline indoor temperature, baseline limb characteristics, and baseline body surface characteristics for the user.

[0029] S104 obtains the current operating parameters, including the current indoor temperature and the user's current limb characteristics and current body surface characteristics.

[0030] After determining the baseline parameters when the user is awake in step S102, during the subsequent use of the air conditioner, the identification module can identify the indoor temperature of the current time period as the current indoor temperature, the user's limb characteristics of the current time period as the current limb characteristics, and the user's body surface characteristics of the current time period as the current body surface characteristics. The current indoor temperature, current limb characteristics, and current body surface characteristics are used together as the current operating parameters, which can characterize the user's current activity state and existence state from different perspectives.

[0031] S106 determines the user's current stage based on the current operating parameters and reference parameters, and adjusts the temperature accordingly based on the determined stage.

[0032] By representing the user's activity and existence status using current operating parameters, and by comparing the current operating parameters with the baseline parameters of the user in that situation, the current stage of the user can be identified from multiple perspectives. Specifically, the current indoor temperature can be compared with the baseline indoor temperature to identify whether the user's current indoor environment is a comfortable temperature environment and whether this indoor environment will affect the user's limb and body surface characteristics, thus determining the accuracy of the representation of the user's activity status by the current limb and body surface characteristics. The user's current external activity status can be effectively identified by the current limb activity amplitude and frequency, the user's internal respiratory status can be identified by comparing the current respiratory rate standard deviation with the baseline respiratory rate standard deviation, the user's internal body temperature status can be identified by comparing the current body surface temperature with the baseline body surface temperature, and the user's external existence status can be identified by the current body surface contour area. By combining the above identification of multiple states simultaneously, the accuracy of identifying the user's current stage can be improved, thereby ensuring that the air conditioner's temperature regulation effect for the corresponding stage is adapted to the user's actual temperature regulation effect, improving the user's comfort.

[0033] In this embodiment, limb characteristics include limb movement amplitude, limb movement frequency, and respiratory rate standard deviation, and body surface characteristics include body surface temperature. The user is first effectively identified as being in a seated state using these parameters. Specifically, step S106, which determines the user's current stage based on current operating parameters and baseline parameters, includes: determining whether the deviation of the current indoor temperature from the baseline indoor temperature is less than a preset room temperature range; if yes, and the user's current limb movement amplitude is slight, the current limb movement frequency is reduced, and the current body surface temperature fluctuates slightly, then the user is determined to be in a seated state; if no, and the ratio of the user's current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of a preset ratio range, then the user is determined to be in a seated state.

[0034] First, calculate the actual deviation of the current indoor temperature from the reference indoor temperature and compare it with the preset room temperature range. Specifically, the absolute value of the temperature difference between the current indoor temperature and the reference indoor temperature can be calculated as the actual deviation. The preset room temperature range can be selected as 1~2℃, preferably 2℃. When the actual deviation is less than 2℃, it indicates that the current indoor temperature is close to the reference indoor temperature. When the actual deviation is greater than or equal to 2℃, it indicates that the current indoor temperature is too high or too low.

[0035] Alternatively, the environmental compensation factor A can be calculated based on the indoor ambient temperature using the following formula: A = 1 + 0.1 × (T) room - 24) - 0.05×(RH - 50%); In the formula, A is the environmental compensation factor, which is dimensionless; T room The current indoor temperature is expressed in °C and is dimensionless; RH is the current indoor relative humidity, dimensionless and expressed as a percentage. The preset room temperature range can be selected as 0.1. When A is between 0.9 and 1.1, it indicates that the current indoor temperature is close to the reference indoor temperature; when A < 0.9 or A > 1.1, it indicates that the current indoor temperature is too low or too high.

[0036] When the actual deviation is less than the preset room temperature range, it indicates that the current indoor temperature is close to the benchmark indoor temperature, and the current indoor temperature has little impact on the current body surface temperature. The current body surface temperature accurately represents the user's internal activity state. Correspondingly, the current body surface temperature detected by an infrared thermal imaging sensor is used to identify the user's internal activity state. When the user's current body surface temperature fluctuates slightly, i.e., within a preset time period, the linear regression slope of the current body surface temperature is ≥-0.02℃ / min, it indicates that the user's current body surface temperature is approximately stable, without a downward trend due to reduced metabolism during sleep. Simultaneously, in summary... The system uses radar sensors to detect the current limb movement amplitude and frequency to identify the user's external activity state. When the user's current limb movement amplitude is micro-movement (i.e., the limb movement amplitude is <5cm) and the current limb movement frequency is reduced, it indicates that the user's external activity state is low. By combining multiple parameters such as current indoor temperature, current body surface temperature, current limb movement amplitude, and current limb movement frequency, the system identifies the user's current stage as a sitting stage from multiple perspectives. This effectively identifies the sitting stage, which is similar to the sleep stage and light sleep stage, and accordingly ensures the air conditioner's temperature regulation effect during the sitting stage.

[0037] When the actual deviation exceeds the preset room temperature range, it indicates that the current indoor temperature is too high or too low, affecting the accuracy of the measured current body surface temperature. The standard deviation of the current respiratory rate detected by a radar sensor is compared with the standard deviation of the baseline respiratory rate when the user is awake to identify the user's internal activity state. Specifically, when the ratio of the user's current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range, it indicates that the user's current respiratory rate is approximately stable and has not shown a decreasing trend due to reduced metabolism during sleep. This mitigates the error in identifying the current body surface temperature, accurately determining the user's current stage as a sitting meditation stage based on the current respiratory rate standard deviation. The preset ratio range can be 40% to 80%, with the upper limit specifically set at 80%.

[0038] In this embodiment, limb characteristics include limb movement amplitude, limb movement frequency, and respiratory rate standard deviation, and body surface characteristics include body surface temperature. The user is effectively identified as being in the sleep-inducing stage using these parameters. Specifically, step S106, which determines the user's current stage based on current operating parameters and baseline parameters, includes: determining whether the following conditions are met: the user's current limb movement amplitude is continuous large-amplitude movement, or the current limb movement amplitude is micro-movement; the current limb movement frequency is greater than a preset sleep-inducing frequency; the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of a preset ratio range; and the current body surface temperature deviates from the baseline body surface temperature by less than a preset sleep-inducing temperature range. If so, the user is determined to be in the sleep-inducing stage.

[0039] Determine if the following conditions are met simultaneously: Condition 1: The user's current limb movement amplitude is a continuous large-amplitude movement, such as turning over, with an amplitude >20cm. Or the current limb movement amplitude is a micro-movement, with an amplitude <5cm, and the current limb movement frequency is greater than the preset sleep frequency. The preset sleep frequency can be selected as 2~4 times / min, preferably 3 times / min. Among them, the user is in a high-frequency micro-movement state, and typical manifestations include: (1) sleep twitching, that is, sudden rapid and brief twitching of the fingers, toes or local muscle groups; (2) aimless body micro-adjustment, such as rubbing the sheets with the fingers, overlapping the toes, and turning the head slightly on the pillow. When condition 1 is met, it indicates that the user has a certain degree of external activity and is in a non-static state.

[0040] Condition 2: The ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range, where the preset ratio range can be 40% to 80%, and the upper limit can be 80%. When Condition 2 is met, it indicates that the user's current respiratory rate has not shown a decreasing trend due to the reduced metabolic rate during sleep.

[0041] Condition 3: The deviation of the current body surface temperature from the baseline body surface temperature is less than the preset sleep temperature range. Specifically, the preset sleep temperature range can be 0.2~0.4℃, preferably 0.3℃, meaning the absolute value of the temperature difference between the current body surface temperature and the baseline body surface temperature is <0.3℃. Meeting Condition 3 indicates that the user's current body surface temperature has not yet shown a downward trend due to reduced metabolism during sleep.

[0042] Among them, condition one identifies the user's external activity state through the current limb movement amplitude and current limb movement frequency; condition two identifies the user's internal activity state through the current respiratory rate standard deviation; and condition three identifies the user's internal activity state through the current body surface temperature. When all three conditions are met, the user's activity state can be identified from different perspectives, and the user's current stage can be determined as the sleep stage.

[0043] In this embodiment, limb characteristics include limb movement amplitude, limb movement frequency, and respiratory rate standard deviation, and body surface characteristics include body surface temperature. The user is effectively identified as being in a light sleep stage using these parameters. Specifically, step S106, which determines the user's current stage based on current operating parameters and baseline parameters, includes: determining whether the following conditions are met: the user's current limb movement amplitude is small, the current limb movement frequency fluctuates, the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is within a preset ratio range, and the fluctuation range of the current body surface temperature is less than the preset light sleep temperature range; if so, the user is determined to be in a light sleep stage.

[0044] Determine if the following conditions are met simultaneously: Condition 1: The user's current limb movement is a small amplitude movement, i.e., the amplitude is between 5cm and 20cm; at the same time, the frequency of the current limb movement fluctuates, that is, the user's limb movement is non-periodic, and the interval between two adjacent limb movements varies between 1 and 5 minutes. When Condition 1 is met, it indicates that the user is only in a state of some small-scale, unconscious external activity.

[0045] Condition 2: The ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is within a preset ratio range, which can be 40% to 80%. When Condition 2 is met, it indicates that the user's current respiratory rate has shown a downward trend due to the reduced metabolic rate during sleep.

[0046] Condition 3: The fluctuation range of the current body surface temperature is less than the preset light sleep body temperature range, which can be 0.1~0.3℃, preferably 0.2℃; that is, the absolute value of the temperature difference between the current body surface temperature and the reference body surface temperature is <0.2℃. When condition 3 is met, it indicates that the user's current body surface temperature has not yet shown a downward trend due to the reduced metabolic rate during sleep.

[0047] Among them, condition one identifies the user's external activity state through the current limb movement amplitude and current limb movement frequency; condition two identifies the user's internal activity state through the current respiratory rate standard deviation; and condition three identifies the user's internal activity state through the current body surface temperature. When all three conditions are met, the user's activity state can be identified from different angles, and the user's current stage can be determined to be the light sleep stage.

[0048] In this embodiment, limb characteristics include limb movement amplitude, limb movement frequency, and respiratory rate standard deviation, and body surface characteristics include body surface temperature. The user's deep sleep stage is effectively identified using these parameters. Specifically, step S106, which determines the user's current stage based on current operating parameters and baseline parameters, includes: determining whether the following conditions are met: the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is less than the lower limit of a preset ratio range; in the early stage, the user's current limb movement amplitude gradually decreases, and the ratio of the current limb movement frequency to the baseline limb movement frequency is within a preset deep sleep frequency range; and in the later stage, the decrease in the user's current body surface temperature compared to the baseline body surface temperature is the current decrease, and the decrease in the current body surface temperature compared to the baseline body surface temperature in historical deep sleep stages is the historical decrease, and the ratio of the current decrease to the historical decrease is greater than a preset deep sleep ratio; if so, the user's current stage is determined to be a deep sleep stage.

[0049] The system checks a preset time period to determine if the following conditions are met simultaneously: Condition 1: The ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is less than the lower limit of a preset ratio range. The preset ratio range can be 40% to 80%, and the lower limit can be 40%. When Condition 1 is met, it indicates that the user's current respiratory rate has shown a significant downward trend due to the reduced metabolic rate during sleep, and the user's breathing has become more regular.

[0050] Condition 2: During the initial stage of the preset time period for detection, specifically 10-20 minutes, the user's current limb movement amplitude gradually decreases, and the ratio of the current limb movement frequency to the baseline limb movement frequency falls within a preset frequency ratio range, specifically 0.4-0.6. Correspondingly, the interval between two consecutive current limb movements is 1.8-2.5 times the interval between two consecutive baseline limb movements. The specific value of the preset frequency ratio range can be dynamically adjusted based on the user's historical sleep onset speed; specifically, higher values ​​are used for those who fall asleep quickly, and lower values ​​are used for those who fall asleep slowly. When Condition 2 is met, it indicates that the user has only a small amount of external activity, and their limb movement tends to be static.

[0051] Condition 3: The detection is performed during the later stages of a preset time period, specifically 8-20 minutes, which can be dynamically adjusted based on historical sleep onset speed. The user's current body surface temperature decreases compared to the baseline body surface temperature (current decrease). The decrease in current body surface temperature compared to the baseline body surface temperature during historical deep sleep phases (historical decrease) is also considered. The ratio of the current decrease to the historical decrease must be greater than a preset deep sleep ratio, specifically 40%-60%, meaning the current decrease exceeds 40%-60% of the historical decrease. Meeting Condition 3 indicates that the user's current body surface temperature has shown a significant downward trend due to reduced metabolism during sleep. For the initial assessment, the current decrease can be compared to 0.3℃; if the current decrease is greater than 0.3℃, Condition 3 is met.

[0052] Among them, condition one identifies the user's internal activity state through the current respiratory rate standard deviation, condition two identifies the user's external activity state through the current limb movement amplitude and current limb movement frequency, and condition three identifies the user's internal activity state through the current body surface temperature. When the above three conditions are met at the same time, the user's activity state can be identified from different angles, and the user's current stage can be determined to be the deep sleep stage.

[0053] In this embodiment, limb features include limb tilt angle, and body surface features include body surface contour area. The user is effectively identified as being in the out-of-bed or return-to-bed stage using these parameters. Specifically, in step S106, which determines the user's current stage based on current operating parameters and baseline parameters, the identification of the out-of-bed stage includes: determining whether the following conditions are met: the user's current limb tilt angle increases by a greater than a first preset angle, and the current body surface contour area decreases by at least a first preset body surface percentage; if so, the user's current stage is determined to be the out-of-bed stage.

[0054] Determine if the following conditions are met simultaneously: Condition 1: The user's current limb tilt angle increases by a greater than a first preset angle. The limb tilt angle specifically refers to the angle between the user's upper limb and lower limb. When the user is lying flat, the limb tilt angle is approximately 0°; when the user is sitting upright, the limb tilt angle is approximately 90°. The first preset angle can be between 40° and 60°, preferably 45°. When the radar sensor detects that the user has sat up, that is, the user's upper limb changes from a lying to an upright position, and the current limb tilt angle is >45°, specifically, the duration for which the current limb tilt angle increases by a greater than the first preset angle can be greater than 3-5 seconds, to indicate that the user has sat up from the bed.

[0055] Specifically, the method can also detect the position of the user's feet, with condition one corresponding to detecting that the feet are off the bed surface, to indicate that the user has sat up and left the bed surface.

[0056] Condition 2: The current body surface area decreases by at least a first preset body surface percentage. Specifically, the first preset body surface percentage can be 60% to 80%, preferably 70%. Within the sleep area that the infrared thermal imaging sensor can detect, when the user's current body surface area decreases, it indicates that the user's limbs have exceeded the sleep area. When the current body surface area decreases by 70%, it indicates that the user has left the bed and left the sleep area.

[0057] Condition 1 identifies the user's external activity state from the perspective of movement by using the current limb tilt angle, and condition 2 identifies the user's external activity state from the perspective of orientation by using the current body surface contour area. When both conditions are met, the user's external activity state can be identified from different angles, and the user's current stage can be determined as the out-of-bed stage.

[0058] Specifically, when the user is identified as being out of bed, the air conditioner enters a "standby hold" state.

[0059] In step S106, which determines the current stage of the user based on the current operating parameters and the baseline parameters, the identification of the return-to-bed stage includes: determining whether the following conditions are met: the current body surface area of ​​the user increases by at least a second preset body surface percentage, and the current limb tilt angle decreases by more than a second preset angle; if so, the current stage of the user is determined to be the return-to-bed stage.

[0060] Determine if the following conditions are met simultaneously: Condition 1: The user's current body surface area increases by at least a second preset body surface percentage. Specifically, the second preset body surface percentage can be 70% to 90%, preferably 80%. Within the sleep area that the infrared thermal imaging sensor can detect, when the user's current body surface area increases, it indicates that the user's limbs have entered the sleep area. When the current body surface area increases by 80%, it indicates that the user has returned to the bed and returned to the sleep area.

[0061] Condition 2: The decrease in the current limb tilt angle is greater than the second preset angle, which can be 30~40°, preferably 35°. When the radar sensor detects that the user has made a lying down action, that is, the user's upper limb changes from an upright position to a lying position, and the current limb tilt angle decreases from >45° to <15°, it indicates that the user has returned to the bed.

[0062] Condition 1 identifies the user's external activity state from a positional perspective by using the current body surface contour area; Condition 2 identifies the user's external activity state from a movement perspective by using the current limb tilt angle; When both conditions are met simultaneously, the user's external activity state can be identified from different angles, and the user's current stage can be determined as the bed-returning stage.

[0063] Specifically, when the user is identified as being in the "returning to bed" stage, the air conditioner quickly reverts to the temperature control strategy used before the user left the bed within 5 minutes.

[0064] In this embodiment, adaptive feedforward compensation can also be performed on the temperature adjustment of the indoor environment based on changes in outdoor temperature, so as to improve the temperature adjustment effect of the air conditioner on the indoor environment and improve the user's comfort; specifically, it includes: obtaining the change in outdoor temperature relative to the current outdoor temperature over a preset period of time in the future; and correcting the target temperature for adjusting the indoor environment based on the change in outdoor temperature.

[0065] Changes in outdoor temperature affect indoor temperature and the air conditioner's temperature regulation effect. By obtaining the trend of outdoor temperature changes over a preset period of time in advance, and specifically calculating the change in outdoor temperature over the preset period of time relative to the current outdoor temperature as the outdoor temperature change, the air conditioner's target temperature for regulating the indoor environment is adjusted based on this outdoor temperature change. This ensures that the indoor environment reaches the adjusted target temperature, and that the target temperature is adapted to the outdoor temperature over the preset period of time, thereby achieving adaptive feedforward compensation and ensuring that the current indoor temperature continuously meets the user's comfort needs.

[0066] In this embodiment, the step of correcting the target temperature for indoor environment based on changes in outdoor temperature includes: calculating the temperature correction amount according to the following formula, and using the sum of the current target temperature and the temperature correction amount as the new target temperature: T target = α· T outdoor ; In the formula, T target α is the temperature correction amount, in °C; α is the first empirical coefficient, dimensionless, which can take values ​​from 0.1 to 0.3, preferably 0.2; T outdoor This represents the outdoor temperature change over a predetermined period of time, expressed in °C. The predetermined period can be 20 to 40 minutes, with 30 minutes being preferred.

[0067] Among them, when T target When the temperature exceeds 0.5℃, the target temperature can be adjusted multiple times. Specifically, the maximum temperature adjustment at a time can be limited to 0.5℃ to avoid the temperature changing too quickly and affecting user comfort.

[0068] In this embodiment, when the outdoor unit of the air conditioner is equipped with a temperature sensor, the outdoor temperature can be collected through the temperature sensor, and the change in outdoor temperature over a preset period of time can be calculated; or when the air conditioner is connected to the Internet, the trend of outdoor temperature change over a preset period of time can be obtained through the cloud API, and the change in outdoor temperature over a preset period of time can be calculated.

[0069] In addition, when the air conditioner is not connected to the network or cannot detect the outdoor temperature, the step of obtaining the change in outdoor temperature relative to the current outdoor temperature over a future preset period may also include: obtaining the change in indoor temperature over a past preset period, and calculating the change in outdoor temperature according to the following formula: T outdoor = β· T room ; In the formula, T outdoor The outdoor temperature change over a predetermined period of time is expressed in °C; β is a second empirical coefficient, dimensionless, with a value range of 1.5 to 2.5, preferably 2. T room This represents the change in indoor temperature over a previously preset time period, expressed in °C.

[0070] Therefore, indoor temperature changes can be obtained without connecting to the internet, thereby improving the functionality of the air conditioner.

[0071] In this embodiment, when using an infrared thermal imaging sensor to detect the user's body surface temperature, the body surface temperature of the body surface characteristics can be calculated according to the following formula: T skin =T sc ·γ+T est ·(1-γ); in, T est = T sc + (T sc - T room )·R clo / R air ; In the formula, T skin Body surface temperature, in °C; T sc γ represents the target measured temperature, in °C; γ is the confidence level, dimensionless; T est Temperature compensation for bedding, in °C; T room R represents the current indoor temperature in °C. clo Thermal resistance of bedding, in meters (m). 2 ·K / W; R air The thermal resistance for indoor natural convection heat transfer is expressed in meters (m). 2 ·K / W.

[0072] Different methods were used to detect body surface temperature depending on the degree of occlusion of the user's exposed area: Scenario 1: If the proportion of the user's exposed facial area is greater than or equal to the first preset exposure percentage, the temperature of the exposed area of ​​the user's face is used as the target measured temperature, with a confidence level of 1. The probability of the user's face being exposed is relatively high, and the accuracy of the surface temperature obtained by detecting the user's face is relatively high. When the proportion of the user's exposed facial area is greater than or equal to the first preset exposure percentage, it indicates that the user's face is less obstructed or completely exposed. A highly accurate surface temperature can be obtained by detecting the user's face, and the corresponding confidence level γ for surface temperature is marked as 1. skin =T sc In this case, the measured user's facial temperature is T.sc The target measured temperature. The first preset exposure percentage can be 40-60%, preferably 50%.

[0073] Scenario 2: If the proportion of the user's exposed face area is less than the first preset exposure percentage, and at least one of the user's neck and hands is used as an auxiliary detection unit, and the proportion of the exposed area of ​​the auxiliary detection unit is greater than or equal to the second preset exposure percentage, then the temperature of the exposed area of ​​the auxiliary temperature measuring unit is used as the target measured temperature, with a confidence level of (0.5, 0.7], preferably 0.6. When the proportion of the user's exposed face area is less than the first preset exposure percentage, it indicates that the user's face is obstructed and the temperature of the user's face cannot be detected; therefore, the proportion of the exposed area of ​​the user's neck and hands is further detected to see if it is greater than or equal to the second preset exposure percentage of the corresponding area. When the proportion of the exposed area of ​​the neck is greater than the second preset exposure percentage of the entire neck area, the neck is used as an auxiliary detection unit, and the temperature of the exposed area of ​​the neck is used as the target measured temperature T. sc Meanwhile, given the relatively low accuracy of neck temperature detection, the confidence level γ related to body surface temperature is set at 0.5–0.7; subsequently, the current indoor temperature T is detected. room And extract the set thermal resistance R of the bedding inside the air conditioner. clo Thermal resistance R of indoor natural convection heat transfer air The value of T is used to calculate the bedding compensation temperature. est And then calculate the body surface temperature T. skin .

[0074] The second preset exposure percentage can be 40-60%, preferably 50%. clo Based on seasonal presets, during summer, R clo Values ​​range from 0.2 to 0.5clo; in winter, R clo Values ​​range from 1.0 to 2.0clo; R air The value ranges from 0.16 to 0.2m. 2 K / W, preferably 0.18m 2 ·K / W.

[0075] Scenario 3: If the proportion of the user's exposed face area is less than the first preset exposure percentage, and the proportions of the user's exposed neck and hands are both less than the second preset exposure percentage, then the temperature of the bedding is used as the target measured temperature, with a confidence level of (0.3, 0.5], preferably 0.4. When the proportion of the user's exposed face area is less than the first preset exposure percentage, it indicates that the user's face is obstructed, and the temperature of the user's face cannot be detected; when the proportions of the exposed neck and hands are both less than the second preset exposure percentage, it indicates that the user's neck and hands are both obstructed, and there is no auxiliary detection unit; in this case, the measured bedding temperature is used as the target measured temperature T. scMeanwhile, given the low accuracy of temperature detection using bedding, the confidence level γ related to body surface temperature is set at 0.3~0.5; subsequently, the current indoor temperature T is measured. room And extract the set thermal resistance R of the bedding inside the air conditioner. clo Thermal resistance R of indoor natural convection heat transfer air The value of T is used to calculate the bedding compensation temperature. est And then calculate the body surface temperature T. skin .

[0076] In identifying the exposed area of ​​a user's face, the temperature standard deviation can also be used for auxiliary identification. If the temperature standard deviation of a certain area is low, specifically less than 0.1℃, it indicates that the area is an obstructed area.

[0077] In this embodiment, during the detection of body surface temperature, if the infrared thermal imaging sensor displays abnormally high local temperatures (e.g., >37.5℃) or drastic temperature fluctuations (changes >0.8℃ within 1 minute), and the radar sensor detects minute vibrations inconsistent with human breathing rates (e.g., a pet's breathing rate of 60 breaths / minute vs. a human's 12-20 breaths / minute), an anti-interference re-detection is triggered: temperature control is paused for 3 minutes, data is re-acquired, and median filtering is used to remove abnormal pixel blocks. If two consecutive re-detections are still abnormal, an "interference alarm" is output, and the sleep stage is temporarily determined solely by radar data to reduce the impact of external thermal interference on stage determination.

[0078] In this embodiment, when the air conditioner compressor starts (vibration peak > 0.1g), the radar data is marked as low confidence, and the infrared data is temporarily prioritized; this is reversed after the vibration stops. When the infrared thermal imaging sensor detects a sudden decrease of more than 50% in the facial ROI area (e.g., when the user rolls over face down), the weight of the infrared data is reduced, and the radar data becomes the primary data source until the face is exposed again. Dynamic weighting of the infrared thermal imaging sensor and the radar sensor ensures the accuracy of the detection of limb and body surface features through mutual assistance.

[0079] In this embodiment, for multi-user scenarios, airflow can be adjusted to be either undifferentiated or differentiated based on the user's current location, body surface temperature, and obstruction status to ensure temperature comfort for all users. Specifically, body surface features include body surface temperature; the method further includes: if the number of users is greater than or equal to 2, obtaining the current location of each user; calculating the distance between two adjacent users based on their current locations, and calculating the maximum body surface temperature difference between users based on their current body surface temperatures; determining whether the following conditions are met: the distance is less than a preset distance; or the maximum body surface temperature difference is less than a preset temperature difference; or all user body surface detection areas are obstructed; or a user is located outside the airflow range; if yes, then an undifferentiated airflow mode is executed; if no, then a differentiated airflow mode is executed: the airflow direction is directed towards the user with the highest current body surface temperature.

[0080] The recognition module can identify the number of users within the sleep area. When the number of users is equal to 1, it is in single-user mode; when the number of users is greater than or equal to 2, it is in multi-user mode. In multi-user mode, it can continue to collect the current position and current body surface temperature of each user. Specifically, the current position can be the coordinates of the user's face or neck relative to the air conditioner, and the distance between any two adjacent users and the maximum body surface temperature difference between the current body surface temperatures of each user can be calculated. Then, it continues to determine whether at least one of the following conditions is met: Condition 1: The spacing is less than the preset spacing, where the preset spacing can be 30~50cm, preferably 40cm; when the spacing between any two adjacent users is less than the preset spacing, it indicates that the spacing between users is small, approximately close together, and can be treated as a single user.

[0081] Condition 2: The maximum body surface temperature difference is less than the preset temperature difference, wherein the preset temperature difference can be 0.7~0.9℃, preferably 0.8℃; among the multiple current body surface temperatures of each user, the difference between the maximum and minimum values ​​is the maximum body surface temperature difference. When the maximum body surface temperature difference is less than the preset temperature difference, it indicates that the difference in body surface temperature between users is small.

[0082] Condition 3: There are users whose body surface detection areas are completely obscured, that is, there are users who are completely covered by bedding.

[0083] Condition 4: There are users located outside the air supply range; that is, the angle between the users is greater than the effective coverage area of ​​the air guide plate (e.g., one is in front left and the other is behind right).

[0084] When any one of the above four conditions is met, the non-differentiated air supply mode is executed. Specifically, at this time, no biased air supply is performed, but a uniform and gentle airflow is used: the left and right air guides are fixed in the middle position (0°), the fan speed is reduced by one level, and the dual-zone windless mode can be turned on at the same time.

[0085] If none of the above four conditions are met, such as all users being within the effective coverage area of ​​the air guide plate and not being completely blocked, the distance between users being greater than or equal to the preset distance, and the maximum body surface temperature difference of users being greater than or equal to the preset temperature difference, then the differentiated air supply mode will be executed. The left and right air guide doors will be controlled to direct the main airflow direction towards the user with the higher current body surface temperature. At the same time, the fan speed will be set to medium speed, and the windless air guide plate (diffuser hole) will be opened on the side of the user with the lower temperature to reduce the local wind speed.

[0086] In this embodiment, if the user prefers to use airflow and the temperature difference is <0.5℃, an ultra-slow airflow of 0.2° / second can be used to avoid a noticeable wind sensation.

[0087] In this embodiment, the air conditioner is pre-stored with temperature regulation models corresponding to each stage when it leaves the factory. The specific model structure is as follows: a 3-layer MLP is used (8 nodes in the input layer, 16 nodes in the hidden layer + ReLU, and 1 node in the output layer). The input features include: current sleep stage (one-hot: falling asleep / light sleep / deep sleep), body surface temperature of the exposed area (estimated value if occluded, with confidence level), indoor temperature, indoor relative humidity, temperature change rate (the rate of change of room temperature in the past 10 minutes), estimated value of thermal resistance of bedding (estimated online by the area covered by the blanket and the temperature gradient in the infrared image), user age group (20-35, 36-50, 51-65, >65, as discrete feature embedding), historical manual adjustment records (average temperature adjustment deviation of the same sleep stage in the past 3 days), and output: body surface temperature of the target exposed area (continuous value, range 33℃~36.5℃).

[0088] In this embodiment, the method also includes an online learning mechanism (correcting causal logic): Specifically, after the air conditioner runs continuously for N days (N≥5), the following are recorded: the actual sleep stage sequence, the user's manual adjustment behavior (temperature adjustment range, time), the indoor and outdoor temperatures at the same time, and whether the user lifts the blanket / adds clothes (detected by radar micro-motion and infrared area change).

[0089] Simultaneously, Bayesian optimization correction is performed: the model bias term b (initially 0) is corrected using Bayesian optimization. ; In the formula, b new b is the corrected bias term, in °C; 'b' is the uncorrected bias term, in °C; 'sigh' (deviation) is the direction sign and is dimensionless; T room The current indoor temperature is expressed in °C; μ room The average indoor temperature is the historical value, in °C; σ room The historical indoor temperature standard deviation is expressed in °C.

[0090] At the same time, update the user's temperature drop slope threshold during deep sleep according to the following formula: δ deep-new = 0.8×δ deep-old + 0.2×ΔT skin-actual ; In the formula, δ deep-new The temperature drop slope threshold updated for the user's deep sleep phase, in °C / min; δ deep-old The temperature drop slope threshold before the user's deep sleep phase is updated, in °C / min; ΔT skin-actual The decrease in the user's current body surface temperature compared to the baseline body surface temperature is the current decrease rate, expressed in degrees Celsius (°C).

[0091] The present invention will be further described in detail below with reference to specific embodiments.

[0092] Example 1: In single-user mode, the air conditioner is installed in the bedroom, and the user is a 35-year-old male. When the air conditioner is turned on for the first time, the baseline parameters of the user in the first 30 minutes of waking state are collected: baseline body surface temperature is 36.2℃, baseline limb movement frequency is 4 times / min, that is, the baseline interval between two limb movements is 15 seconds.

[0093] At 22:30, the radar sensor detected an interval of 35 seconds between two limb movements (>2 times the baseline interval); monitoring began. At 22:42 (12 minutes later), the infrared thermal imaging sensor detected that the user's facial temperature dropped from 36.2℃ to 35.7℃ (a decrease of 0.5℃), exceeding the decrease in the user's historical deep sleep stage (the default threshold of 0.4℃ was used for the first use), thus determining that the user had entered a deep sleep stage. The model output a target exposure temperature of 34.6℃, which is 1.1℃ higher than the current 35.7℃. The system lowered the set temperature at a rate of 0.4℃ / 10 ​​minutes (from 26℃ to 24.2℃) while monitoring the user's facial temperature, maintaining it at 34.6±0.2℃. If the radar sensor detected turning over during this period, the system temporarily switched to the temperature adjustment mode corresponding to the light sleep stage, adjusting the target temperature upward by 0.3℃ to 34.9℃.

[0094] Example 2: Dual-sensor interlock verification to prevent false judgments Scenario A: A user is sitting quietly on a sofa looking at their phone. The radar sensor shows reduced micro-movements, but the infrared thermal imaging sensor detects the user's facial temperature at 35.9℃ (close to the baseline of 36.0℃) with no decreasing trend (slope -0.01℃ / min). The current indoor temperature is 24℃, which is normal. The system determines the user is in a sitting state, a false positive, and does not activate sleep mode.

[0095] Scenario B: A pet cat jumps onto the bed. The infrared thermal imaging sensor detects a localized high-temperature block of 38°C in the sleeping area, and the radar sensor detects a vibration of 50 times / min. The system triggers anti-interference re-detection: pause for 3 minutes, re-acquire data, and after median filtering, the abnormal block disappears and normal detection resumes. If the abnormality persists, an interference warning is output and only the radar sensor is used to maintain a coarse judgment.

[0096] The user was sleeping on their side with their face buried in the pillow. Infrared detection showed an 80% decrease in the facial ROI area, and the blanket covered up to the chin, obscuring the neck and hands. The user's confidence level was α=0.4. Thermal resistance compensation was enabled: bedding surface temperature 29.5℃, room temperature 24℃, estimated bedding thermal resistance 1.2 clo=0.186m. 2K / W, calculated bedding compensation temperature ≈35.0℃, further calculated body surface temperature ≈33℃; the system determined it to be deep sleep stage, target exposure temperature 34.5℃, the actual temperature control effect is consistent with the user's subjective comfort.

[0097] Example 3: Online Learning and Adaptive Compensation User A used the system for 7 consecutive nights. The system recorded that during the deep sleep phase each night, the user manually increased the set temperature by 0.5℃, and the indoor temperature was below 22℃ (below the historical average of 24℃). The Bayesian optimization determined that the user preferred a warm environment and increased the target exposure temperature during the deep sleep phase from the default 34.5℃ to 34.8℃. From the 8th night onwards, the user no longer manually adjusted the temperature.

[0098] One night, the outdoor temperature suddenly dropped from 25°C to 15°C. The system predicted a 2°C drop in temperature over the next 30 minutes. Based on the feedforward formula ( T target =0.2×2=0.4℃), the target exposure temperature was adjusted from 34.8℃ to 35.2℃ in advance; the actual exposure temperature fluctuation was only 0.25℃, which was imperceptible to the user.

[0099] At 3:00 AM, the user got up to use the restroom. The radar sensor detected the user sitting up and then standing, while the infrared thermal imaging sensor detected an 80% reduction in body surface area, indicating the user was in the process of getting out of bed. The system maintained the current set temperature of 24℃. Ten minutes later, the user returned to lying down. The radar sensor detected the lying down movement, and the infrared thermal imaging sensor detected the body surface area recovering. Within 2 minutes, the system restored the set temperature from 24℃ to the pre-get-out-of-bed temperature of 23.5℃, without the user experiencing any temperature shock.

[0100] Example 4: Differentiated air supply for multiple users Two users on a double bed are 50cm apart horizontally, with an angle of 15° (both within the coverage area of ​​the air guide). User A's facial temperature is 35.5℃, and User B's facial temperature is 34.2℃. In differentiated airflow mode, the system points the air guide towards User A (15° direction), the fan runs at medium speed, and the air guide on User B's side is open without any wind. After 20 minutes, the maximum surface temperature difference between the two users decreases to 0.3℃, and the system switches to non-differentiated airflow mode, restoring uniform airflow (the air guide returns to the center, and the fan speed drops one level). If the angle between the two users is 60° (User A 30° to the left, User B 30° to the right), exceeding the single-direction capability, the system switches to non-differentiated airflow mode. The system does not perform air sweeping but instead fixes the air guide in the center position (0°), reduces the fan speed to low, and simultaneously activates dual-zone windless mode to avoid thermal shock.

[0101] Figure 2 This is a second flowchart of the air conditioner sleep temperature control method provided by the present invention. Figure 2 As shown, the method includes the following steps: S201 determines the baseline parameters for the user when the user is awake. The baseline parameters include the baseline room temperature, the user's baseline limb movement amplitude, baseline limb movement frequency, baseline respiratory rate standard deviation, and baseline body surface temperature.

[0102] S202 Obtains current operating parameters, including current indoor temperature, current limb movement amplitude, current limb movement frequency, current respiratory rate standard deviation, and current body surface temperature.

[0103] S203 Determine whether the deviation of the current indoor temperature from the benchmark indoor temperature is less than the preset room temperature range; if yes, proceed to step S204; if no, proceed to step S206.

[0104] S204 Determine whether the following conditions are met: the user's current limb movement amplitude is micro-movement, the current limb movement frequency is reduced, and the current body surface temperature fluctuates slightly; if yes, proceed to step S205; if no, return to step S203.

[0105] S205 determines that the user is currently in a sitting phase; S206 determines whether the following condition is met: the ratio of the user's current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range; if yes, proceed to step S205; if no, return to step S203.

[0106] Figure 3 This is the third flowchart of the air conditioner sleep temperature control method provided by the present invention. Figure 3 As shown, the method includes the following steps: S301 determines that the proportion of the user's exposed facial area is greater than or equal to the first preset exposed percentage; if yes, then proceed to step S302; if no, then proceed to step S303.

[0107] S302 uses the temperature of the exposed area of ​​the user's face as the target measured temperature, with a confidence level of 1.

[0108] S303 determines whether at least one of the user's neck or hand is used as an auxiliary detection part; if yes, proceed to step S304; if no, proceed to step S305.

[0109] S304 uses the temperature of the exposed area of ​​the auxiliary temperature measuring unit as the target measured temperature, with a confidence level of (0.5, 0.7).

[0110] S305 uses the temperature of the bedding as the target measured temperature, with a confidence level of (0.3, 0.5).

[0111] This embodiment also provides a control device capable of executing the above-described method, such as... Figure 4As shown, the control device includes: an acquisition module 41 for acquiring current operating parameters; a determination module 42 for determining a reference parameter when the user is awake, and determining the current stage of the user based on the current operating parameters and the reference parameter; and a control module 43 for adjusting the temperature accordingly based on the determined stage.

[0112] This embodiment also provides an air conditioner, including a computer-readable storage medium storing a computer program and a controller, wherein the computer program is read and executed by the controller to implement the above method.

[0113] Both the control device and the air conditioner are capable of performing the above method and possess all the beneficial effects of the method, which will not be elaborated here.

[0114] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling sleep temperature in an air conditioner, characterized in that, include: Determine the baseline parameters for the user when they are awake, including the baseline indoor temperature, the user's baseline limb characteristics, and the baseline body surface characteristics. Obtain current operating parameters, including current indoor temperature and the user's current limb characteristics and current body surface characteristics; The user's current stage is determined based on the current operating parameters and the baseline parameters, and the temperature is adjusted accordingly based on the determined stage.

2. The method according to claim 1, characterized in that, Limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine whether the current indoor temperature deviates from the baseline indoor temperature by less than the preset room temperature range; If so, and the user's current limb movement amplitude is micro-movement, the current limb movement frequency is reduced, and the current body surface temperature fluctuates slightly, then the user's current stage is determined to be the sitting stage. If not, and the ratio of the user's current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range, then the user is determined to be in the sitting meditation stage.

3. The method according to claim 1, characterized in that, Limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine if the following conditions are met: the user's current limb movement is a continuous large-amplitude movement, or the current limb movement is a micro-movement, and the current limb movement frequency is greater than the preset sleep frequency; the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is greater than the upper limit of the preset ratio range; and the current body surface temperature deviates from the baseline body surface temperature by less than the preset sleep temperature range. If so, then the user is currently in the sleep stage.

4. The method according to claim 1, characterized in that, Limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine whether the following conditions are met: the user's current limb movement amplitude is small, the current limb movement frequency fluctuates, the ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is within a preset ratio range, and the fluctuation amplitude of the current body surface temperature is less than the preset light sleep body temperature amplitude. If so, then the user is currently in a light sleep stage.

5. The method according to claim 1, characterized in that, Limb characteristics include limb movement amplitude, limb movement frequency, and standard deviation of respiratory rate; body surface characteristics include body surface temperature; the step of determining the user's current stage based on the current operating parameters and the baseline parameters includes: Determine if the following conditions are met: The ratio of the current respiratory rate standard deviation to the baseline respiratory rate standard deviation is less than the lower limit of the preset ratio range; In the initial stage, the user's current limb movement amplitude gradually decreases, and the ratio of the current limb movement frequency to the baseline limb movement frequency remains within a preset frequency ratio range; and, In the later stage, the decrease in the user's current body surface temperature compared to the reference body surface temperature is the current decrease rate, and the decrease in the current body surface temperature compared to the reference body surface temperature during the historical deep sleep stage is the historical decrease rate. The ratio of the current decrease rate to the historical decrease rate is greater than the preset deep sleep ratio. If so, then the user is currently in a deep sleep stage.

6. The method according to claim 1, characterized in that, Limb features include limb tilt angle, and body surface features include body surface contour area; the step of determining the user's current stage based on the current operating parameters and the reference parameters includes: Determine whether the following conditions are met: the increase angle of the user's current limb tilt angle is greater than the first preset angle, and the current body surface area is reduced by at least the first preset body surface percentage. If so, then the user is currently in the out-of-bed stage; And / or, determine whether the following conditions are met: the user's current body surface area increases by at least a second preset body surface percentage, and the current limb tilt angle decreases by more than a second preset angle; If so, then the user is currently in the bed-back stage.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Obtain the change in outdoor temperature relative to the current outdoor temperature over a future preset time period; The target temperature for adjusting the indoor environment is adjusted based on the change in outdoor temperature.

8. The method according to claim 7, characterized in that, The step of adjusting the target temperature of the indoor environment based on the outdoor temperature change includes: The temperature correction amount is calculated according to the following formula, and the sum of the current target temperature and the temperature correction amount is taken as the new target temperature: T target = α· T outdoor ; In the formula, T target α is the temperature correction amount, in °C; α is the first empirical coefficient, dimensionless. T outdoor The outdoor temperature change over a predetermined period of time, expressed in °C.

9. The method according to claim 8, characterized in that, The step of obtaining the change in outdoor temperature relative to the current outdoor temperature over a preset future time period includes: Obtain the indoor temperature change over a preset time period, and calculate the outdoor temperature change using the following formula: T outdoor = β· T room ; In the formula, T outdoor The outdoor temperature change over a predetermined period of time is expressed in °C; β is the second empirical coefficient, which is dimensionless. T room This represents the change in indoor temperature over a previously preset time period, expressed in °C.

10. The method according to any one of claims 1-6, characterized in that, The body surface temperature of the aforementioned body surface characteristics is calculated using the following formula: T skin =T sc ·g+T est ·(1-c); in, T est = T sc + (T sc - T room )·R clo / R air ; In the formula, T skin Body surface temperature, in °C; T sc γ represents the target measured temperature, in °C; γ is the confidence level, dimensionless; T est Temperature compensation for bedding, in °C; T room R represents the current indoor temperature, in °C. clo Thermal resistance of bedding, in meters (m). 2 ·K / W; R air The thermal resistance for indoor natural convection heat transfer is expressed in meters (m). 2 K / W; in: If the proportion of the user's exposed facial area is greater than or equal to the first preset exposed percentage, the temperature of the exposed area of ​​the user's face is detected as the target measured temperature, and the confidence level is 1. And / or, if the proportion of the user's exposed facial area is less than the first preset exposure percentage, and at least one of the user's neck and hands is used as an auxiliary detection part, and the proportion of the exposed area of ​​the auxiliary detection part is greater than or equal to the second preset exposure percentage, then the temperature of the exposed area of ​​the auxiliary temperature measuring part is detected as the target measured temperature, and the confidence level is (0.5, 0.7]. And / or, if the proportion of the user's exposed face area is less than the first preset exposure percentage, and the proportions of the user's exposed neck and hands are both less than the second preset exposure percentage, then the temperature of the bedding is taken as the target measured temperature, and the confidence level is (0.3, 0.5).

11. The method according to claim 1, characterized in that, Body surface characteristics include body surface temperature; the method further includes: If the number of users is greater than or equal to 2, then obtain the current location of each user; Calculate the distance between two adjacent users based on the current location, and calculate the maximum body surface temperature difference between users based on the current body surface temperature of each user. Determine if the following conditions are met: The spacing is less than the preset spacing; or the maximum body surface temperature difference is less than the preset temperature difference; or the user's body surface detection area is completely blocked; or the user is located outside the air supply range. If so, then execute the undifferentiated air supply mode; If not, then a differentiated air supply mode will be executed: the air supply direction will be directed towards the user with the highest current body surface temperature.

12. A control device, characterized in that, The control device is capable of performing the method according to any one of claims 1-11, wherein the control device comprises: Acquisition module: Used to obtain current running parameters; The determination module is used to determine the baseline parameters when the user is awake, and to determine the current stage of the user based on the current operating parameters and the baseline parameters; Control module: Used to adjust the temperature accordingly based on the determined stage.

13. An air conditioner, characterized in that, The method includes a computer-readable storage medium storing a computer program, which is read and executed by the controller to implement the method as described in any one of claims 1-11.

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