Control method for air-conditioning device and air-conditioning device

Abstract

The invention relates to the field of air conditioning, and particularly provides a control method of an air conditioning device and the air conditioning device. The control method is used for controlling at least one air parameter of a target space. The control method comprises the following steps that environment data, air conditioning historical data and air parameter reply historical data are stored in an associated mode; obtaining a user leaving time period and environment data in the user leaving time period; according to the environment data in the user leaving time period, the adjusting capacity information of the air adjusting device on the air parameters in the target space and the change prediction information of the air parameters in the target space when the air adjusting device is closed are determined; and according to the adjusting capacity information and the change prediction information, the time for starting the air conditioning device in advance is set. According to the control method, the working mode of the air conditioning device in the user leaving time period can be more automatically and efficiently set, and the user experience and the service life and energy consumption problems of the air conditioning device are considered.

Description

Technical Field

[0001] This invention relates to the field of air conditioning, specifically to a control method for an air conditioning device and an air conditioning device. Background Technology

[0002] Air conditioning devices can regulate air parameters such as temperature, humidity, cleanliness, and odor, including but not limited to air conditioners, humidifiers, dehumidifiers, air purifiers, fresh air systems, water ion generators, and aromatherapy products.

[0003] Air conditioning devices all have a certain lag in regulating the air. In other words, after setting target air parameters such as temperature, humidity, or concentration, the air conditioning device needs to work for a period of time before these air parameters in the space reach the target values.

[0004] Therefore, for users who need to be away from home for extended periods, if they turn on the air conditioning upon returning, they will usually have to endure an environment where the air parameters are not within the comfortable range for a period of time.

[0005] To address these issues, some existing air conditioning systems offer a preset on-time function, allowing users to pre-set the on-time before leaving home, ensuring the system turns on in advance before their return. However, if users manually set the on-time, it's difficult to accurately determine the exact amount of advance time, and they are prone to forgetting to set it beforehand, resulting in a poor user experience.

[0006] The above applies to situations where users are away for extended periods. In actual use, there are also situations where users are away for short periods. If the air conditioning is automatically turned off when the user leaves and is set to turn on in advance, it will cause unnecessary opening and closing of the air conditioning for short periods, affecting its lifespan and potentially consuming more energy. Summary of the Invention

[0007] Therefore, there is an urgent need in the field to provide a control method for air conditioning devices that can more automatically and efficiently set the operating mode of the air conditioning device during the user's absence period, taking into account both user experience and the lifespan and energy consumption of the air conditioning device.

[0008] To address the aforementioned problems, a first aspect of the present invention provides a control method for an air conditioning device, used to control at least one air parameter of a target space, the control method comprising the following steps:

[0009] The data saving steps involve saving environmental data, air conditioning historical data, and air parameter recovery historical data together. The environmental data refers to the air parameters of the external environment of the target space, the air conditioning historical data refers to the historical data of changes in air parameters when the air conditioning device is running, and the air parameter recovery historical data refers to the historical data of changes in air parameters after the air conditioning device is turned off.

[0010] The data acquisition steps include acquiring the user's departure time period and environmental data within that period.

[0011] The data analysis steps involve determining the air conditioning device's ability to regulate air parameters in the target space based on environmental data during the user's absence period, as well as predicting changes in air parameters in the target space when the air conditioning device is turned off.

[0012] The mode setting process involves setting the time to turn on the air conditioning unit in advance, based on the adjustment capacity information and change prediction information.

[0013] Based on historical air conditioning data and environmental data during the user's absence period, the air conditioning unit's ability to regulate air parameters in the target space can be analyzed. Based on historical air parameter recovery data and environmental data during the user's absence period, the rate at which the target space returns to equilibrium with the outside environment after the air conditioning unit is turned off can be analyzed, and the rate of change can be predicted. Further combining the regulation capacity information and the change prediction information, it can be determined whether, during the user's absence period, if the air conditioning unit is turned off for a specified time and then turned back on, the remaining time is sufficient for air parameters to return to the comfortable range. This allows for a more accurate setting of the time to turn on the air conditioning unit earlier, balancing user experience and energy consumption.

[0014] Optionally, in the mode setting step, it is first determined whether the air conditioning unit needs to be turned off during the user's absence period. If so, the time for turning the air conditioning unit on in advance is set based on the conditioning capacity information and change prediction information. According to the above scheme, it is possible to accurately determine in which situations the air conditioning unit should be temporarily turned off and then turned on in advance when the user is away, and in which situations the air conditioning unit should remain running to ensure that the indoor environment is within a comfortable range when the user returns. Based on this determination, the user experience for both long-term and short-term absences can be effectively considered, as well as the lifespan and energy consumption of the air conditioning unit.

[0015] Optionally, the control method further includes: a model training step of training a model using the environmental data, air conditioning historical data, and air parameter response historical data associated and saved in the data saving step as sample data for model training; in the data analysis step, applying the model to the environmental data during the user's departure period to determine the adjustment ability information and change prediction information. In the above optional technical solution, machine learning can be used to train the model based on the sample data recorded when the air conditioning device is operating normally and turned off, thereby improving the accuracy of model prediction.

[0016] Optionally, the adjustment ability information includes the change curve of air parameters when the air conditioning device operates at a specified output; the change prediction information includes the change curve of air parameters when the air conditioning device is turned off. In the above optional technical solution, recording and predicting the change of air parameters in the target space when the air conditioning device is turned on or off in the form of a change curve can more accurately reflect the change of air parameters. Correspondingly, it can improve the accuracy of time setting, taking into account the comfort experience when the user returns and the operating energy consumption of the air conditioning device.

[0017] Optionally, the specified output is the maximum output of the air conditioning device. Using the maximum output of the air conditioning device as the specified output is an optional setting method, which can reduce the number of opening and closing times of the air conditioning device and improve its service life. In other optional technical solutions, other output values can also be used as the specified output, such as the output value when the energy efficiency ratio (e.g., COP value) of the air conditioning device is relatively high or any other reasonable setting method.

[0018] Optionally, the adjustment ability information includes the time t1 required for the air parameters to change from the environmental balance value to within the comfort range; the change prediction information includes the time t2 required for the air parameters to change from the value at the time of turning off the air conditioning device to the environmental balance value after the air conditioning device is turned off. The environmental balance value is the air parameter value when the indoor and outdoor environments are in balance when the air conditioning device is turned off, corresponding to the environmental parameter.

[0019] Optionally, the duration of the user's departure period is t0. If t0 ≥ t1 + t2, turn off the air conditioning device when the user leaves, and turn on the air conditioning device t1 time in advance before the user returns; if t0 < t1 + t2, turn off the air conditioning device when the user leaves, and turn on the air conditioning device in advance before the air parameters reach the environmental balance value.

[0020] Optionally, the duration of the user's departure period is t0, and t' is a specified duration threshold. If t0 ≥ t1 + t2 and t0 ≥ t1 + t', the air conditioning device is turned off when the user leaves, and the air conditioning device is turned on t1 duration in advance before the user returns. t1 + t2 can more accurately reflect the length of a time period from turning off the air conditioning device for a period of time to turning on the air conditioning device again to bring the air parameters back to the comfortable range. When the user's departure time length is longer than t1 + t2 and t2 ≥ t', it is judged that even if the air parameters change to the environmental equilibrium value, the remaining time is still greater than or equal to t1, which is sufficient for the air parameters to return from the environmental equilibrium value to the comfortable range. Therefore, it is only necessary to turn on the air conditioning device t1 duration in advance. If t2 < t', that is, the air conditioner still does not meet the specified threshold time t' after being turned off for t2 time. In order to ensure the on duration t1 of the air conditioner, the condition t0 ≥ t1 + t' needs to be met at this time. If the above conditions are not met, that is, t0 ≥ t1 + t2 and t0 < t1 + t', the air conditioner is not turned off.

[0021] Optionally, the duration of the user's departure period is t0, and t' is a specified duration threshold. If t' < t0 < t1 + t2, then T is determined x and t2(n): Assume T x = T(environment) + nT0, where T(environment) is the environmental equilibrium value, n is a positive integer taking values 0, 1, 2... in sequence, and T0 is a preset step value. Calculate the corresponding t1(n) + t2(n) values for different n values in sequence, and determine T with the value of T(environment) + nT0 corresponding to the t1(n) + t2(n) value closest to t0 x ; if t2(n) > t', the air conditioner is turned off during the user's absence, and the air conditioning device is turned on in advance when the air parameters reach T x ; if t2(n) ≤ t', the air conditioner is not turned off during the user's absence. According to the above optional technical solutions, a reasonable T x value can be obtained efficiently and accurately, reducing the amount of computation. x value, reducing the amount of computation.

[0022] Optionally, the duration of the user's departure period is t0, and t' is a specified duration threshold. If t0 ≤ t', the air conditioning device is not turned off when the user leaves. t' can be, for example, a duration threshold set based on the fact that the air conditioning device is not suitable for high-frequency opening and closing, or can be a duration threshold set considering that the air parameters inside the target space are not suitable for large disturbances. When t0 ≤ t', not turning off the air conditioning device can extend the service life of the air conditioning device or reduce the fluctuation range of the air parameters of the target air, etc.

[0023] Optionally, the target space may have multiple users, and the user departure time period is the time period during which all users leave the target space. This method avoids turning off the air conditioning only because some users are out, thus ensuring the comfort needs of all users within the target space.

[0024] Optionally, the data saving step also includes the identifier of the target space and the identifier of the air conditioning device. Linking and saving the target space, the corresponding air conditioning device, and historical change data allows for more targeted and accurate determination of regulation capacity and change prediction information in subsequent steps. Furthermore, historical data from different target spaces and different air conditioning devices can be cross-referenced, increasing the amount of usable data for model training and enhancing the diversity and effectiveness of its application in different scenarios.

[0025] Optionally, environmental data can be downloaded from an external server and / or detected using sensors installed at the outdoor unit of the air conditioning unit. Downloading predictive amounts of environmental data from an external server can improve the accuracy of future environmental forecasts, thereby enhancing the accuracy of determining regulation capacity and predicting changes. Environmental data obtained using sensors installed at the outdoor unit of the air conditioning unit is more consistent with the actual local environment and, in some application scenarios, is more accurate than values ​​published by external servers such as weather forecasts.

[0026] Optionally, the environmental data includes environmental data related to air parameters from multiple different time periods throughout the day. Using more granular environmental data allows the prediction results to better match the continuous changes in daily environmental data, improving the accuracy of predictions regarding regulatory capacity and change forecasting.

[0027] Optionally, air parameters may be temperature, humidity, air quality index, or concentration of a specific type of substance.

[0028] A second aspect of the present invention provides an air conditioning device for controlling at least one air parameter of a target space, including a memory, a communication unit, a processor, and a control unit. Among them, the memory is associated with and stores environmental data, air conditioning history data, and air parameter recovery history data. The environmental data is the air parameters of the external environment of the target space, the air conditioning history data is the change history data of the air parameters when the air conditioning device is running, and the air parameter recovery history data is the change history data of the air parameters after the air conditioning device is turned off; the communication unit obtains the user's departure time period and the environmental data during the user's departure time period; the processor determines the adjustment ability information of the air conditioning device for the air parameters in the target space and the change prediction information of the air parameters in the target space when the air conditioning device is turned off according to the environmental data during the user's departure time period; the control unit sets the time to turn on the air conditioning device in advance according to the adjustment ability information and the change prediction information. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic flowchart of a control method for an air conditioning device provided in the first embodiment of the present invention.

[0030] Figure 2 It is a specific flowchart of each step of the control method for the air conditioning device provided in the first embodiment of the present invention.

[0031] Figure 3 It is a schematic diagram of a calculation method for calculating each physical quantity when t0 < t1 + t2 based on the temperature change curve when t0 = t1 + t2 in the first embodiment of the present invention.

[0032] Figure 4 It shows an application scenario of the control method for the air conditioning device according to an embodiment of the present invention.

[0033] Figure 5 and Figure 6 It shows a schematic diagram of an interaction process for interacting with a smart home system using text conversations in some embodiments.

[0034] Figure 7 It shows another application scenario of the control method for the air conditioning device according to an embodiment of the present invention.

[0035] Figure 8 It shows the time relationship of multiple users leaving and returning in a case in the form of a timing diagram.

[0036] Figure 9 It shows another application scenario of the control method for the air conditioning device according to an embodiment of the present invention.

[0037] Figure 10 is Figure 9Timing diagram of the on / off states of different air conditioning devices in application scenarios.

[0038] Figure label:

[0039] 1-Air conditioning unit; 1a-Air conditioner; 1b-Air purifier; 1c-Humidifier; 2-Control center; 3-Sound pickup device; 100-Smart home system. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] <First Implementation Method>

[0042] The first aspect of this invention provides a control method for an air conditioning device, which can be an air conditioner, humidifier, dehumidifier, air purifier, fresh air system, water ion generator, aromatherapy device, etc. In this embodiment, an air conditioner is used as an example. An air conditioner can at least regulate the temperature in a room. In other embodiments, an air conditioner can also be used to regulate air parameters such as temperature and air cleanliness. For ease of explanation, this embodiment only uses an air conditioner for temperature regulation as an example.

[0043] refer to Figure 1 The air conditioning control method provided in this embodiment includes the following steps:

[0044] Data saving step S1 involves saving environmental data, historical air conditioning data, and historical air parameter recovery data together.

[0045] Data acquisition step S2: Acquire the user's departure time period and the environmental data within the user's departure time period.

[0046] In data analysis step S3, based on environmental data during the user's absence period, the system determines the air conditioning device's ability to regulate air parameters in the target space, as well as the predicted changes in air parameters in the target space when the air conditioning device is turned off.

[0047] In mode setting step S4, based on the adjustment capacity information and change prediction information, the time for turning on the air conditioning device in advance is set.

[0048] The data saving step S1 is executed multiple times or routinely during the trial operation or normal operation phases, thereby providing rich sample data for the data analysis step S3. The data acquisition step S2 can be executed in response to detecting user departure, and its order of occurrence with the data saving step S1 is not limited. The data analysis step S3 is executed after at least a portion of the data saving step S1 and the data acquisition step S2 have been completed. The mode setting step S4 occurs after the data analysis step S3. Of course, in other embodiments, the order of occurrence of the various steps may not be limited.

[0049] In this embodiment, the target space can be one or more rooms indoors. In other embodiments, the target space can also be any space whose air parameters can be adjusted by an air conditioning device; the present invention is not limited thereto.

[0050] In this embodiment, the historical air conditioning data stored during the air conditioner's operation can be used as sample data. Combined with environmental data from the period the user was away, the air conditioner's temperature control capability can be analyzed. Furthermore, based on the historical data of air parameter recovery recorded when the air conditioner is turned off, combined with environmental data from the period the user was away, the rate at which the target space returns to equilibrium with the outside environment after the air conditioner is turned off can be analyzed, allowing for prediction of the room's insulation capability. By further combining the air conditioner's temperature control capability and the room's insulation capability, the time to turn on the air conditioner earlier can be set more accurately, balancing user experience and energy consumption.

[0051] Figure 2 This is a detailed flowchart illustrating each step of the control method for the air conditioning device provided in this embodiment. The following references... Figure 1 and Figure 2 The control method provided in this embodiment will be described in detail.

[0052] <Data saving step S1>

[0053] In the data storage step S1 of this embodiment, the environmental data refers to the air parameters of the external environment of the target space, specifically the external ambient temperature. The air conditioning history data refers to the historical data of air parameter changes when the air conditioning device is running, specifically the temperature rise (heating) or fall (cooling) curve when the air conditioner is running. The air parameter recovery history data refers to the historical data of air parameter changes after the air conditioning device is turned off, specifically the temperature change curve inside the room after the air conditioner is turned off, i.e., the historical data of the insulation capacity curve.

[0054] In this embodiment, the environmental data can be the external ambient temperature data for various future time periods corresponding to the installation location of the air conditioning device, as published in weather forecasts. In other embodiments, the environmental data can also be humidity, air quality index, concentration of specific types of substances, etc. The environmental data can be obtained from an external server or detected by sensors installed in the external environment; this application embodiment does not impose any limitations on this.

[0055] As an optional form, the air conditioning historical data can be a curve showing the change of air parameters when the air conditioning device is running. For example, in this embodiment where the air parameter is temperature, the environmental data is the external ambient temperature, and the air conditioning device is an air conditioner, the corresponding air conditioning historical data would be a curve showing the change of room temperature over time when the air conditioner is cooling or heating. In other embodiments, for example, where the air parameter is the air quality index, the environmental data is the air quality index of the external environment, and the air conditioning device is an air purifier, the corresponding air conditioning historical data would be a curve showing the change of indoor air quality index over time when the air purifier is turned on.

[0056] As an optional approach, the historical air parameter recovery data is a curve showing the change in air parameters after the air conditioning device is turned off. For example, in this embodiment where the air parameter is temperature, the environmental data is the external ambient temperature, and the air conditioning device is an air conditioner, the historical air parameter recovery data would be historical data on the room's insulation capacity curve, i.e., the curve showing the change in room temperature over time when the air conditioner is turned off. In other embodiments, for example, where the air parameter is the air quality index, the environmental data is the air quality index of the external environment, and the air conditioning device is an air purifier, the historical air parameter recovery data would be the curve showing the change in indoor air quality index over time after the air purifier is turned off.

[0057] By recording and predicting the changes in air parameters in the target space when the air conditioning unit is turned on or off using a change curve, the changes in air parameters can be reflected more accurately. Consequently, the accuracy of time settings can be improved, taking into account both the user's comfort upon return and the energy consumption of the air conditioning unit.

[0058] Taking temperature as an example, because the rate of heat / cold dissipation in a room varies with different ambient temperatures, the ability of an air conditioner to regulate the room temperature also varies. Therefore, by linking and saving environmental data, historical air conditioning data, and historical air parameter recovery data, we can establish the correlation between the above data, perform certain preprocessing on the sample data, reduce the number of predictive features, and reduce the dimensionality of the sample data.

[0059] Furthermore, in the data saving step S1, the identifiers of the target space and the air conditioning device are also saved in association. Saving the target space, the corresponding air conditioning device, and historical change data in association allows for more targeted and accurate determination of regulation capacity information and change prediction information in subsequent steps. Moreover, historical data from different target spaces and different air conditioning devices can be cross-referenced, increasing the amount of usable data for model training and enhancing the diversity and effectiveness of its application in different scenarios.

[0060] <Data Acquisition Step S2>

[0061] Data acquisition step S2: Acquire the user's departure time period and the environmental data within the user's departure time period.

[0062] In the data acquisition step S2, as some specific examples, the user's absence time period can be obtained by receiving user input from the mobile terminal, receiving and translating user voice messages, or reading the user's schedule.

[0063] After obtaining the user's departure time period, query the environmental data within the user's departure time period.

[0064] For example, when a user leaves through the foyer, they might leave a voice message saying, "I'll be back at 5 PM." The smart home system can then use cloud-based natural language processing to translate this message and determine the user's absence period as "from the current time to 5 PM." After determining the user's absence period, the smart home system downloads ambient temperature data from an external server that publishes weather forecasts, covering the period from the current time to 5 PM, as the environmental data for the user's absence period.

[0065] Environmental data can include environmental data related to air parameters from multiple different time periods throughout the day. Using more granular environmental data allows forecasts to better match the continuous changes in daily environmental data, improving the accuracy of forecasts for regulatory capacity and change predictions.

[0066] Environmental data can be downloaded from external servers or obtained using sensors installed on the outdoor unit of the air conditioner. External servers can provide predicted environmental data, improving the accuracy of future environmental forecasts and consequently enhancing the accuracy of determining regulation capacity and predicting changes. Environmental data obtained from sensors installed on the outdoor unit of the air conditioner is more consistent with the actual local environment and, in some application scenarios, is more accurate than values ​​published by external servers such as weather forecasts.

[0067] <Data Analysis Step S3>

[0068] Since ambient temperature is a physical quantity that determines the rate of heat / cooling loss in a room, and also determines the ability of the air conditioner to regulate the room temperature, the effectiveness and reliability of the model can be improved by treating environmental data as an independent predictive feature in data analysis step S3.

[0069] It should be noted that in data analysis step S3, the physical quantities upon which the regulation capacity information and change prediction information are based may include, but are not limited to, environmental data during the user's absence period. In some embodiments, for example, when determining the regulation capacity curve and change prediction information, factors such as whether doors and windows are open, the output power of the air conditioner, and the on or off status of other indoor appliances may also be considered to determine the regulation capacity information and change prediction information. This application does not limit whether other physical quantities are used as the basis in data analysis step S3.

[0070] refer to Figure 2 In this embodiment, in the data analysis step S3, the machine learning model is applied to the environmental data during the user's absence period to generate adjustment capability information and change prediction information.

[0071] The machine learning model is trained using environmental data, historical air conditioning data, and historical air parameter recovery data saved in data storage step S1 as sample data, prior to data analysis step S3. Training the model based on sample data recorded during normal operation and shutdown of the air conditioning unit improves the accuracy of its predictions. In data analysis step S3, the model is applied, using the trained model to more accurately obtain prediction data for the regulation capacity curve (i.e., regulation capacity information) and the heat preservation capacity curve (i.e., change prediction information).

[0072] The regulating capability curve has time on the horizontal axis and actual room temperature on the vertical axis. The curve shows the relationship between actual room temperature and time under specific set and ambient temperatures. An air conditioner's regulating capability depends not only on its output but also on ambient temperature, set temperature, room size, the presence of other heat or cold sources, room sealing performance, and the insulation performance of wall materials. By using machine learning, measurable and variable quantities (such as ambient temperature and set temperature) are used as predictive features, while invariant and difficult-to-measure quantities (such as room size, room sealing performance, and the insulation performance of wall materials) are embedded in the model. This reduces the number of physical quantities to be measured while still ensuring the accuracy of the prediction results.

[0073] The air conditioner output power on which the adjustment capability curve is calculated is a specified output. Optionally, the specified output is the maximum output of the air conditioning unit. Using the maximum output of the air conditioning unit as the specified output is an optional setting method that can reduce the number of times the air conditioning unit is turned on and off, thereby increasing its service life. In other optional technical solutions, other output values ​​can also be used as the specified output, such as the output value of the air conditioning unit when its energy efficiency is relatively high, or any other reasonable setting method.

[0074] The insulation capacity curve is a curve that gradually approaches and eventually reaches equilibrium with the external ambient temperature. The horizontal axis of the insulation capacity curve represents time, and the vertical axis represents the actual room temperature. The insulation capacity curve reflects the change in room temperature over time when the air conditioner is off, thus demonstrating the room's insulation capacity.

[0075] In some implementations, historical air conditioning data and historical air parameter recovery data can also be recorded in the form of regulation capacity curves and insulation capacity curves, respectively. The points on the curves can be recorded continuously or periodically and fitted into a curve. Of course, the "curve" does not limit the specific storage format of the data, but is merely an expression of the deterministic functional relationship between actual room temperature and time.

[0076] <Mode Setting Step S4>

[0077] refer to Figure 2 In this embodiment, the time t1 required for the air conditioner to change the room temperature from the environmental equilibrium value to the comfort range can be obtained from the adjustment capability curve. The change prediction information can then be used to analyze the time t2 required for the room temperature to change from the value at which the air conditioner was turned off to the environmental equilibrium value.

[0078] In this embodiment, the environmental balance value is the room temperature value when the indoor and outdoor temperatures are balanced under the current external ambient temperature conditions and the air conditioner is turned off. The comfort range is a comfortable temperature range, such as 18-26℃. In other embodiments, the environmental balance value can also be the humidity value when the indoor and outdoor humidity are balanced under the current external humidity conditions and the humidifier / dehumidifier is turned off; correspondingly, the comfort range is a comfortable humidity range. In other words, the units of each curve and physical quantity in the embodiments of the present invention can be adjusted according to the units of the physical quantities of the adjusted air parameters, and the embodiments of the present invention do not limit this.

[0079] In addition, it should be noted that in the embodiments of the present invention, physical quantities such as environmental balance values, environmental data, comfort ranges, t1, t2, etc. can be equal within a unit time period. For example, the same value is used within a time period such as one day or one hour, or they can be dynamically changed. For example, the values obtained by real-time acquisition or calculation are used for further operations or judgments. The embodiments of the present invention do not limit this.

[0080] In some embodiments, after determining t1 and t2, the specific setting of the leaving-home mode can be determined by comparing the relationship between t1 + t2 and t0, where t0 is the duration of the user's leaving period. If t0 ≥ t1 + t2, the air conditioning device is turned off when the user leaves, and the air conditioning device is turned on in advance for a duration of t1 before the user returns; if t0 < t1 + t2, the air conditioning device is turned off when the user leaves, and the air conditioning device is turned on in advance before the air parameters reach the environmental balance value.

[0081] In this embodiment, after determining t1 and t2, the specific setting of the leaving-home mode can be determined by comparing the magnitude relationship among t0, t1 + t2, and t'. Where t0 is the duration of the user's leaving period, and t' is a specified duration threshold. The specified duration threshold t' can be, for example, a duration threshold set based on the fact that the air conditioning device is not suitable for high-frequency opening and closing, or a duration threshold set considering that the air parameters inside the target space are not suitable for large disturbances.

[0082] If t0 ≤ t', the air conditioning device is not turned off when the user leaves. That is, as long as the duration of the user's leaving is not sufficient to change the temperature from the environmental balance value to the comfort range, the air conditioning device is not turned off. Through the above setting, it can be ensured that the room temperature can return to the comfort range when the user returns, which is a setting method focusing on the user experience. In other embodiments, t' can also be a duration threshold set based on the fact that the air conditioning device is not suitable for high-frequency opening and closing, or a duration threshold set considering that the air parameters inside the target space are not suitable for large disturbances. When t0 ≤ t', not turning off the air conditioning device can extend the service life of the air conditioning device or reduce the fluctuation range of the air parameters of the target air, etc.

[0083] If \(t_0\geq t_1 + t_2\) and \(t_0\geq t_1 + t'\), the air conditioner is turned off when the user leaves, and the air conditioner is turned on \(t_1\) time in advance before the user returns. \(t_1 + t_2\) can more accurately reflect the length of a time period from turning off the air conditioner for a period of time to turning on the air conditioner again to make the air parameters return to the comfortable range. When the duration \(t_0\) of the user's leaving period is longer than \(t_1 + t_2\) and \(t_2\geq t'\), it is judged that even if the air parameters change to the environmental equilibrium value, the remaining time is still greater than or equal to \(t_1\), which is sufficient to make the temperature return from the environmental equilibrium value to the comfortable range. Therefore, it is only necessary to turn on the air conditioner \(t_1\) time in advance. If \(t_2\lt t'\), that is, the air conditioner still does not meet the specified threshold time \(t'\) after being turned off for \(t_2\) time. In order to ensure the duration \(t_1\) of the air conditioner being turned on, the condition \(t_0\geq t_1 + t'\) needs to be satisfied at this time. If the above conditions are not met, that is, \(t_0\geq t_1 + t_2\) and \(t_0\lt t_1 + t'\), the air conditioner is not turned off.

[0084] If \(t'\lt t_0\lt t_1 + t_2\), it means that if the air parameters are allowed to change to the environmental equilibrium value, the remaining time is less than \(t_1\), that is, the air conditioning device cannot change the air parameters from the environmental equilibrium value to the comfortable range even if it adopts the maximum output or the output with the best energy efficiency ratio, etc., which will sacrifice the comfort in the target space when the user returns. Therefore, it is necessary to confirm the relationship between the time \(t_2(n)\) (i.e., the time when the air conditioner is turned off) and \(t'\) when the air conditioner is turned on again when the temperature reaches \(T\) x at ( \(T\) x is between \(T\) 环 and \(T\) 舒 ) after the user leaves and assuming the air conditioner is turned off, so as to determine whether the air conditioner needs to be turned off. Where \(T\) 环 is the environmental equilibrium value, \(T\) 舒 is the threshold value of the comfortable range. Assume the calculation method of the time \(t_2(n)\) when the air conditioner needs to be turned off is as follows.

[0085] Figure 3 Taking winter heating as an example, it is a schematic diagram of the calculation method of each physical quantity when \(t_0\lt t_1 + t_2\) deduced from the temperature change curve when \(t_0 = t_1 + t_2\). Refer to Figure 3 , \(T\) x For example, it can be obtained by the following method: Assume \(T\) <( x = \(T_{(env)}+nT_0\), where \(T_{(env)}\) is the environmental equilibrium value. \(n\) is an integer that takes values of 0, 1, 2... in sequence. \(T_0\) is a preset step value, which can be a positive number or a negative number. For example, different step values can be selected according to the refrigeration or heating working conditions. In this embodiment, \(T_0 = 1K\) (or \(1^{\circ}C\)) to calculate the corresponding \(t_1(n)+t_2(n)\) values for different \(n\) values in sequence, and determine \(T\) x corresponding to the \(t_1(n)+t_2(n)\) value closest to \(t_0\) with the value of \(T_{(env)}+nT_0\) xSince t0 < t1 + t2, if the temperature drops to the ambient equilibrium value T(amb), the remaining time is not enough to increase it to the comfortable range. Therefore, assuming that the target temperatures to which the room temperature drops after the air conditioner is turned off are T(amb) + 1K, T(amb) + 2K, T(amb) + 3K, etc., calculate the values of t1(n) + t2(n) corresponding to each target temperature, compare the obtained values of t1(n) + t2(n) with t0, and find the one among the t1(n) + t2(n) that is closest to the duration t0 of the user's departure period. Assign T with the corresponding T(amb) + nT0 x The above is only an exemplary description of the T x assignment method. In other embodiments of the present invention, T x can also be determined by other reasonable methods, and the embodiments of the present invention do not limit this

[0086] Determine T according to the above method x and n and t2(n) corresponding to T x Next, compare t2(n) with t'. If t2(n) > t', turn off the air conditioner during the user's absence. If t2(n) ≤ t', do not turn off the air conditioner during the user's absence

[0087] Finally, after determining the parameter settings of the departure mode during the user's departure period, send the mode setting instruction to the corresponding air conditioner for execution to end the process

[0088] Through the above method, the control method of the air conditioning device provided in this embodiment can automatically and efficiently set the working mode of the air conditioning device during the user's departure period after receiving or analyzing the user's departure period, taking into account the scenarios of the user's short-term absence and long-term absence. Do not turn off during short-term absence, and turn off the air conditioning device in advance during longer or long-term absence, and turn on the air conditioning device in advance at a more accurate moment, which will neither waste energy due to premature turning on nor make it difficult for the air parameters to return to the comfortable range due to late turning on, effectively taking into account and solving the problems of user experience and energy consumption

[0089] <Application Scenario 1 - Single Person Travel>

[0090] Figure 4An application scenario of the control method for the air conditioning device according to this embodiment is illustrated. Taking a single-person apartment as an example, a smart home system 100 is installed in the apartment. The smart home system 100 includes a control center, one or more air conditioning devices 1, and a microphone 3. The control center is installed in the living room; multiple air conditioning devices 1 are installed in different rooms, and the following description uses one of these air conditioning devices 1 as an example. The microphone 3 is installed in the foyer, allowing the user to interact with the smart home system 100 by speaking to the microphone 3 when leaving the foyer.

[0091] In addition, users can interact with the smart home system 100 through text conversations, graphical user interfaces, or any other suitable means. Figure 5 and Figure 6 The diagram illustrates some implementations of how text conversations interact with the smart home system 100. Of course, text conversations and voice interaction can be interchanged, as long as a corresponding voice recognition module is configured. In this embodiment of the invention, for ease of illustration, the specific conversation method is described in the form of text conversations.

[0092] refer to Figure 5 When a user leaves home on a weekday morning, the smart home system 100 initiates a conversation as the user passes through the foyer, asking for their return time. The user can inform the smart home system 100 of their return time. The smart home system 100 determines that the user will be away for an extended period (t0 > t1 + t2), and immediately turns off the air conditioner when the user leaves, and anticipates the user's return by t1 hours in advance. Figure 5 Turn on the air conditioner half an hour in advance to change the room temperature to a comfortable range.

[0093] refer to Figure 6 When a user needs to go out for a walk on a weekend evening, the smart home system 100 will proactively initiate a conversation when the user passes through the foyer to ask for their return time. The user can inform the smart home system 100 of their return time. The smart home system 100 will determine that the user is going out for a short time, i.e., t0≤t'. During the time the user is away, the air conditioner will continue to operate normally or in energy-saving mode to maintain the indoor environment within a comfortable range.

[0094] <Application Scenario 2 - Management of Multiple-User Families Away From Home>

[0095] Figure 7 This illustrates another application scenario of the control method of the air conditioning device 1 according to this embodiment.

[0096] refer to Figure 7In this application scenario, there are multiple users within a household. We will use a family of three as an example. The travel times and return times of these multiple users may differ.

[0097] Figure 8 The timing relationship between multiple users leaving and returning is illustrated using a sequence diagram. Figure 8 Solid arrows indicate the time periods when a user was at home, while dashed arrows indicate the time periods when a user was away. (Reference) Figure 8 The male homeowner, M, leaves earliest in the morning and returns earliest in the afternoon, while the female homeowner, F, leaves latest in the morning and returns latest in the afternoon. Child C leaves between the departure times of homeowner M and homeowner F, returning after homeowner M but before homeowner F. In this scenario, the user's departure time can be determined solely by the time between the departure time of the latest departing person and the return time of the earliest returning person. Based on this departure time, adjustment capacity information and change prediction information can be determined. That is, in this embodiment, the time between homeowner F's departure time and homeowner M's return time is counted as the user's departure time.

[0098] The refresh time point for the user's absence period can be the moment when the smart home system 100 initiates a session to inquire about the return time of the user who is away from home. After the user's absence period changes, the mode settings can be recalculated to determine the time to turn on the air conditioning device 1 in advance.

[0099] Furthermore, unlike the scenario of a single person traveling alone, for multi-person households, whether to immediately turn off the air conditioning unit 1 when a user leaves also needs to consider whether there are other users indoors. That is, when a user leaves, if there are other family members indoors, only the return time of the departing user is recorded. And when the last family member leaves, the user's departure time period is determined, and the data analysis step S3 and mode setting step S4 are then executed. This method avoids turning off the air conditioning unit simply because some users are away, thus catering to the comfort needs of all users in the target space. Other steps are essentially the same as for a single person traveling alone, and will not be elaborated upon here.

[0100] <Application Scenario 3 - Multiple Air Conditioning Units of Different Types>

[0101] Figure 9This illustration demonstrates the application of the control method for the air conditioning device 1 in another scenario. Specifically, in this embodiment, three different types of air conditioning devices 1 are installed in a room, including an air conditioner 1a for temperature regulation, a humidifier 1c for humidity regulation, and an air purifier 1b for air quality regulation. The air conditioner 1a, humidifier 1c, and air purifier 1b are all communicatively connected to the control center of the smart home appliance system. Furthermore, the control center is also communicatively connected to a microphone 3 installed in the lobby.

[0102] In this embodiment, since various types of air conditioning devices 1 are installed in the room, and the adjustment capabilities of different types of air conditioning devices 1 are not the same, in other words, the rates and capabilities at which different types of air conditioning devices 1 adjust different air parameters in the room to a comfortable range are different. Therefore, corresponding adjustment capability curves and change prediction curves can be created for different air conditioning devices 1, thereby allowing different types of air conditioning devices 1 to be turned on at different times in advance.

[0103] Furthermore, users can set whether different types of air conditioning devices 1 should be turned on in advance. For example, if a user has a high tolerance for certain air parameters that are not in the comfortable range, the user can choose not to turn on automatically or in advance, and instead turn on manually.

[0104] Figure 10 This is a timing diagram showing the on / off states of different air conditioning devices 1 in this application scenario. (Reference) Figure 10 In this embodiment, air conditioning devices 1 that are not suitable for repeated opening and closing (humidifier 1c is taken as an example in this embodiment) can be kept on all the time. For air conditioning devices 1 with a slower air parameter adjustment speed (air conditioner 1a is taken as an example in this embodiment), they can be turned on a longer time in advance; while for air conditioning devices 1 with a faster air parameter adjustment speed (air purifier 1b is taken as an example in this embodiment), they can be turned on later than air conditioner 1a, as long as the indoor air can be purified to meet the standards in time.

[0105] In other embodiments, an air conditioning unit 1 can adjust multiple different air parameters. For example, some air conditioners 1a can adjust both temperature and humidity simultaneously. In these embodiments, the duration t1 for early activation can be calculated based on the lower adjustment rate.

[0106] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method for an air conditioning device, used to control at least one air parameter of a target space, characterized in that, The control method includes the following steps: A data saving step of associatively saving environmental data, air conditioning historical data, and air parameter recovery historical data. Herein, the environmental data is the air parameters of the external environment of the target space, the air conditioning historical data is the change historical data of the air parameters when the air conditioning device operates, and the air parameter recovery historical data is the change historical data of the air parameters after the air conditioning device is turned off; A data acquisition step of acquiring the user's leaving time period and the environmental data during the user's leaving time period; A data analysis step of determining the adjustment ability information of the air conditioning device for the air parameters in the target space and the change prediction information of the air parameters in the target space when the air conditioning device is turned off, according to the environmental data during the user's leaving time period; A mode setting step of setting the time for turning on the air conditioning device in advance, according to the adjustment ability information and the change prediction information; 2. The control method of the air conditioning device according to claim 1, wherein: In the mode setting step, first judge whether it is necessary to turn off the air conditioning device during the user's leaving time period. If so, set the time for turning on the air conditioning device in advance according to the adjustment ability information and the change prediction information.

3. The control method for the air conditioning device as described in claim 2, characterized in that, It further includes: A model training step of using the environmental data, air conditioning historical data, and air parameter recovery historical data associatively saved in the data saving step as sample data for model training to train the model; In the data analysis step, apply the model to the environmental data during the user's leaving time period to determine the adjustment ability information and the change prediction information.

4. The control method of the air conditioning device according to claim 3, wherein: The adjustment ability information includes the change curve of the air parameters when the air conditioning device operates at a specified output; The change prediction information includes the change curve of the air parameters when the air conditioning device is turned off; 5. The control method for the air conditioning device as described in claim 4, characterized in that, The specified output is the maximum output of the air conditioning device; 6. The control method for the air conditioning device as described in claim 3, characterized in that, The adjustment ability information includes the time t1 required for the air parameters to change from the environmental balance value to within the comfortable range, and the change prediction information includes the time t2 required for the air parameters to change from the value at the time of turning off the air conditioning device to the environmental balance value after the air conditioning device is turned off; The environmental balance value is the air parameter value when the indoor and outdoor environments are balanced when the air conditioning device is turned off, corresponding to this environmental parameter; 7. The control method for the air conditioning device as described in claim 6, characterized in that, The duration of the user's leaving time period is t0; If t0≥t1 + t2, turn off the air conditioning device when the user leaves, and turn on the air conditioning device t1 time in advance before the user returns; If t0<t1 + t2, turn off the air conditioning device when the user leaves, and turn on the air conditioning device in advance before the air parameters reach the environmental balance value.

8. The control method for the air conditioning device as described in claim 6, characterized in that, The duration of the user's departure period is t0, and t' is a specified duration threshold. If t0 ≥ t1 + t2 and t0 ≥ t1 + t', then the air conditioning device is turned off when the user leaves, and turned on t1 hours in advance before the user returns.

9. The control method for the air conditioning device as described in claim 6, characterized in that, The duration of the user's leaving period is t0, and t’ is the specified duration threshold. If t’ < t0 < t1 + t2, then T is determined x and t2(n): Assume T x = T(ring) + nT0, where T(ring) is the environmental equilibrium value, n is an integer taking values ​​of 0, 1, 2..., and T0 is a preset step size value. T is calculated sequentially for different n values. x The corresponding t1(n)+t2(n) values ​​are used to determine T, which is the T(ring)+nT0 value corresponding to the t1(n)+t2(n) value closest to t0. x ; If t2(n) > t', then the air conditioner will be turned off while the user is away, and the air parameters will be adjusted to T. x In such cases, turn on the air conditioning device in advance; If t2(n)≤t', then the air conditioner will not be turned off while the user is away.

10. The control method for the air conditioning device as described in claim 6, characterized in that, The duration of the user's absence period is t0, and t' is a specified duration threshold. If t0 ≤ t', the air conditioning device will not be turned off when the user leaves.

11. The control method for the air conditioning device as described in claim 1, characterized in that, The target space corresponds to multiple users, and the user departure time period is the time period during which all multiple users leave the target space.

12. The control method for the air conditioning device as described in claim 1, characterized in that, In the data saving step, the identifier of the target space and the identifier of the air conditioning device are also saved together.

13. The control method for the air conditioning device as described in claim 1, characterized in that, The environmental data is obtained by downloading from an external server and / or by detecting it using sensors installed at the outdoor unit of the air conditioning device.

14. The control method for the air conditioning device as described in claim 1, characterized in that, The environmental data includes environmental data associated with the air parameters at multiple different time periods throughout the day.

15. The control method for the air conditioning device as described in claim 1, characterized in that, The air parameters are temperature, humidity, air quality index, or the concentration of a specific type of substance.

16. An air conditioning device for controlling at least one air parameter of a target space, characterized in that, include: The memory is associated with and stores environmental data, air conditioning history data, and air parameter recovery history data. The environmental data refers to the air parameters of the external environment of the target space. The air conditioning history data refers to the historical data of changes in the air parameters when the air conditioning device is running. The air parameter recovery history data refers to the historical data of changes in the air parameters after the air conditioning device is turned off. The communication unit acquires the user's departure time period and environmental data within the user's departure time period; The processor determines, based on the environmental data during the user's absence period, the air conditioning device's ability to regulate the air parameters in the target space, and the predicted changes in the air parameters in the target space when the air conditioning device is turned off; The control unit sets the time to turn on the air conditioning device in advance based on the adjustment capability information and the change prediction information.

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