Control method of air conditioner, storage medium, and air conditioner

Abstract

The application provides a control method of an air conditioner, a storage medium and the air conditioner, and the control method comprises the following steps: obtaining physiological parameters of a target user, current environmental body sense parameters and power consumption parameters of the air conditioner; generating adjustment reference feature information according to the physiological parameters, the environmental body sense parameters and the power consumption parameters; determining target operation parameters of the air conditioner according to the adjustment reference feature information; and controlling the air conditioner to operate according to the target operation parameters. According to the control method, the target operation parameters are obtained by comprehensively analyzing the physiological parameters of the target user, the current environmental body sense parameters and the power consumption parameters of the air conditioner, so that the operation parameters of the air conditioner are adjusted to create a more comfortable environment that is more suitable for the user's needs, and the personalized adaptability, intelligence, environmental adaptability and energy efficiency of the air conditioner are comprehensively optimized, thereby bringing great development space to the future smart home field.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of air conditioners, and particularly relates to an air conditioner control method, a storage medium and an air conditioner. BACKGROUND

[0002] It is known that the function of an air conditioner is to adjust the air in a room, including cooling and heating adjustment of the air. The existing air conditioner can detect environmental parameters such as indoor temperature and humidity to adjust the compressor frequency, air speed and the like of the air conditioner according to the environmental parameters, but its adjustment is limited to fixed preset modes and set parameters, and cannot actively adapt to the individual needs of users.

[0003] With the continuous improvement of people's living standards, users have higher and higher requirements for air conditioners. Therefore, how to enable the air conditioner to be more fine, personalized and intelligent to meet the more diversified needs of users has become a technical problem to be solved in the field of air conditioners. SUMMARY

[0004] The embodiments of the application provide an air conditioner control method, a storage medium and an air conditioner, which can solve the problem of how to improve the intelligence and personalization of air conditioner operation.

[0005] To achieve the above object, the application provides the following technical scheme:

[0006] An air conditioner control method comprises the following steps:

[0007] Obtaining physiological parameters of a target user, current environmental sensory parameters and power consumption parameters of the air conditioner;

[0008] Generating adjustment reference feature information according to the physiological parameters, the environmental sensory parameters and the power consumption parameters;

[0009] Determining target operation parameters of the air conditioner according to the adjustment reference feature information;

[0010] Controlling the air conditioner to operate according to the target operation parameters.

[0011] In some embodiments, the generating adjustment reference feature information according to the physiological parameters, the environmental sensory parameters and the power consumption parameters comprises:

[0012] Determining emotion type information of the target user according to the physiological parameters;

[0013] Extracting features from the environmental sensory parameters to obtain environmental sensory feature information;

[0014] Extracting features from the power consumption parameters to obtain power consumption feature information;

[0015] The mood type information, the environmental somatosensory feature information and the power consumption feature information are fused according to preset weights to obtain adjustment reference feature information.

[0016] In some embodiments, the feature extraction on the environmental somatosensory parameters to obtain environmental somatosensory feature information comprises:

[0017] The environmental somatosensory parameters are feature extracted by a behavior prediction model to obtain environmental somatosensory feature information.

[0018] In some embodiments, before the environmental somatosensory parameters are respectively feature extracted by the behavior prediction model, the method further comprises:

[0019] In response to an input of a user interface, actual running parameters are obtained, and actual environmental parameters at the time of the input are acquired;

[0020] The behavior prediction model is trained based on the actual running parameters and the actual environmental parameters to obtain a new behavior prediction model.

[0021] In some embodiments, the determination of the target running parameters of the air conditioner according to the adjustment reference feature information comprises:

[0022] A target running mode is determined according to the adjustment reference feature information;

[0023] A preset running parameter corresponding to the target running mode is taken as a target running parameter.

[0024] In some embodiments, before the adjustment reference feature information is generated according to the physiological parameters, the environmental somatosensory parameters and the power consumption parameters, the method further comprises:

[0025] Behavior state information of the target user is acquired;

[0026] The generation of the adjustment reference feature information according to the environmental somatosensory parameters, the power consumption parameters and the physiological parameters comprises:

[0027] The adjustment reference feature information is generated according to the environmental somatosensory parameters, the power consumption parameters, the physiological parameters and the behavior state information.

[0028] In some embodiments, before the adjustment reference feature information is generated according to the physiological parameters, the environmental somatosensory parameters and the power consumption parameters, the method further comprises:

[0029] A current time parameter is acquired;

[0030] The generation of the adjustment reference feature information according to the environmental somatosensory parameters, the power consumption parameters and the physiological parameters comprises:

[0031] Generate adjustment reference feature information according to the environmental body feeling parameter, the power consumption parameter, the physiological parameter and the time parameter.

[0032] In some embodiments, after controlling the air conditioner to run according to the target running parameter, further comprising:

[0033] Collect indoor temperature data after running for a preset time according to the target running parameter;

[0034] Fit a temperature change curve according to the indoor temperature data and the preset time;

[0035] According to the temperature change curve, predict the expected indoor temperature at the target time;

[0036] Adjust the target running parameter according to the expected indoor temperature.

[0037] A storage medium of an air conditioner, having a computer program stored thereon, the computer program being executed to perform the control method of the air conditioner.

[0038] An air conditioner for performing the control method of the air conditioner.

[0039] The control method of the air conditioner, the storage medium and the air conditioner provided by the embodiments of the present application obtain the target running parameter by comprehensively analyzing the physiological parameter of the target user, the current environmental body feeling parameter and the power consumption parameter of the air conditioner, adjust the running parameter of the air conditioner to create a more comfortable environment that meets the user's demand, and realize comprehensive optimization of the individual adaptability, intelligence, environmental adaptability and energy efficiency of the air conditioner, thus bringing huge development space for the future smart home field. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0041] In order to more completely understand the present application and its beneficial effects, the following will be described with reference to the drawings. In the following description, the same reference numerals represent the same parts.

[0042] Figure 1 The flow chart of the control method of the air conditioner provided by the embodiments of the present application.

[0043] Figure 2 Another flow chart of the control method of the air conditioner provided by the embodiments of the present application.

[0044] Figure 3 The training method of the behavior prediction model provided by the embodiment of the present application.

[0045] Figure 4 The structural schematic diagram of the air conditioner provided by the embodiment of the present application.

[0046] Figure 5 The structural schematic diagram of the emotion recognition system provided by the embodiment of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0048] The embodiment of the present application provides a control method of an air conditioner. For example, refer to Figure 1 , Figure 1 The flowchart of the control method of the air conditioner provided by the embodiment of the present application. The control method of the air conditioner includes the following steps S101-S104:

[0049] Step S101: obtaining physiological parameters of a target user, current environmental somatosensory parameters and power consumption parameters of the air conditioner;

[0050] For example, the air conditioner communicates with the wearable device on the target user to obtain the physiological parameters of the target user. The physiological parameters include, for example, the heart rate, blood oxygen, body temperature, blood pressure, respiratory rate and other parameters of the target user. The wearable device detects multiple physiological parameters of the target user through, for example, the built-in heart rate sensor, skin electric sensor and emotion sensor and other biological sensors, and converts the physiological parameters into digital signals and transmits them to the air conditioner. The wearable device is, for example, a smart watch / bracelet, smart glasses, smart clothing, smart earphones, smart ring and other devices. In some other embodiments, the air conditioner can also obtain the physiological parameters of the user through the mounted camera device, heat recognition device and the like.

[0051] It should be noted that the environmental somatosensory parameters can include the temperature, humidity, gas concentration, light intensity, noise level and other parameters of the indoor and outdoor environment where the air conditioner is located. The air conditioner detects the environmental somatosensory parameters through, for example, the mounted humidity sensor, temperature sensor, gas concentration sensor, noise sensor, light sensor and other devices.

[0052] Step S102: generating adjustment reference feature information according to the physiological parameters, environmental somatosensory parameters and power consumption parameters;

[0053] The adjustment reference feature information is a kind of fusion feature information, which can comprehensively reflect the characteristics of physiological parameters, environmental parameters and power consumption parameters in three dimensions. In an embodiment, the physiological parameters, environmental parameters and power consumption parameters can be input into a feature fusion network to obtain the adjustment reference feature information. It can be understood that by fusing the three kinds of data to obtain one data, it is beneficial to reduce the complexity of subsequent data processing.

[0054] In some embodiments, before generating the adjustment reference feature information according to the physiological parameters, environmental parameters and power consumption parameters, the behavior state information of the target user is also obtained, and then the adjustment reference feature information is generated according to the environmental parameters, power consumption parameters, physiological parameters and behavior state information. The behavior state includes the state of the target user in sleep, leisure, exercise or diet, etc. The air conditioner is equipped with a camera, and the state image of the user is obtained through the camera, and the behavior state information of the user is determined by analyzing the state image.

[0055] In other embodiments, before generating the adjustment reference feature information according to the physiological parameters, environmental parameters and power consumption parameters, the current time parameter is also obtained, and then the adjustment reference feature information is generated according to the environmental parameters, power consumption parameters, physiological parameters and time parameters.

[0056] Step S103: determining the target operating parameters of the air conditioner according to the adjustment reference feature information;

[0057] It should be noted that the target operating parameters can include the compressor operating frequency of the air conditioner, the indoor and outdoor fan speed, the air guide angle, the air outlet mode and other parameters. For the air conditioner equipped with devices such as humidifiers, the target operating parameters can also include the humidification frequency and other parameters.

[0058] Step S104: controlling the air conditioner to operate according to the target operating parameters.

[0059] In actual application, the air conditioner adjusts the actual operating parameters in real time according to the physiological parameters of the target user, the current environmental parameters and the power consumption parameters of the air conditioner during operation.

[0060] The control method of the air conditioner provided by the embodiments of the present application can realize the comprehensive optimization of the individual adaptability, intelligence, environmental adaptability and energy efficiency of the air conditioner, thereby greatly improving the user comfort and reducing the energy consumption, and also bringing great development space for the future smart home field. The control method of the present scheme can realize the dynamic adjustment of the air conditioner parameters, and when the emotional needs, environmental changes or energy efficiency change, it can quickly respond and dynamically adjust the air conditioner parameters to meet the user comfort needs and energy saving goals.

[0061] Further, please refer to Figure 2 , Figure 2 Another flowchart of the control method of the air conditioner provided by the embodiments of the present application is provided. The control method of the air conditioner can include the following steps S201-S212:

[0062] Step S201: obtaining the physiological parameters of the target user, the current environmental body feeling parameters and the power consumption parameters of the air conditioner;

[0063] Step S202: determining the emotional type information of the target user according to the physiological parameters;

[0064] The air conditioner analyzes and processes the physiological parameters by the pre-stored emotional recognition algorithm to determine the emotional type information of the target user. In other embodiments, the air conditioner extracts features from the physiological parameters to obtain physiological feature information, and then determines the emotional type information of the target user according to the corresponding relationship between the physiological feature information and the pre-set emotional type. The emotional type includes, for example, angry, happy, anxious, tired and sad, fear, calm and the like. In actual application, the air conditioner is provided with, for example, a human-computer interaction interface, which provides functions such as preference setting, emotional state feedback and special demand input, and the user can conveniently interact with the air conditioner system. These input information will be recorded and used as a reference for system optimization. Secondly, the system will monitor and collect user behavior data and its feedback to the system adjustment in real time, including user satisfaction evaluation, individualized needs, preferences in specific scenarios and other information. The air conditioner continuously optimizes the emotional recognition algorithm according to the user feedback to be able to more accurately adapt to the changing needs of the user and continuously provide individualized and intelligent air conditioner adjustment services.

[0065] In an embodiment, the use scenario of the air conditioner is in a private space, for example, installed in a general home environment, and there can be 2-3 people or 3-5 people in the room at the same time. If the mood change of each person causes the working mode of the air conditioner to be adjusted, it can cause the air conditioner control to be chaotic. In order to avoid the above situation, the air conditioner determines the user closest to the air conditioner as the target user, for example, through the positioning information of each user in the room or other ways. In another possible implementation, the target user can be set by a person with management authority to have priority order for multiple users respectively. For example, the elderly, children, sick people or pregnant women in the family can be set as users with high priority, and other personnel can be set as users with low priority. The air conditioner prioritizes the user with high priority as the target user, thereby prioritizing the comfort of the target user; if the user with high priority is not in the room, the user with lower priority is sequentially set as the target user.

[0066] Step S203: feature extraction is performed on the environmental body feeling parameters to obtain environmental body feeling feature information.

[0067] In some embodiments, the processor of the air conditioner extracts features from the environmental body feeling parameters through a behavior prediction model to obtain environmental body feeling feature information. The behavior prediction model is obtained by training a preset training algorithm based on past user operation behaviors on the air conditioner and changes in environmental body feeling parameters at the time of operation, for example.

[0068] For example, referring to Figure 3 , Figure 3 The training method of the behavior prediction model provided in the embodiments of the present application. Before the environmental body feeling parameters are extracted by the behavior prediction model, the air conditioner is further used to perform steps S301-S302:

[0069] Step S301: in response to the input of the user interface, obtaining the actual running parameters and acquiring the actual environmental parameters at the time of input;

[0070] It should be noted that the input of the user interface indicates that the user has implemented an operation behavior on the air conditioner through a remote control device or a touch device on the indoor unit of the air conditioner to adjust the running state of the air conditioner, for example, adjusting the running mode, temperature setting, air outlet speed, timing length and other parameters of the air conditioner. The actual running parameters are the running parameters of the air conditioner after the user input. The actual environmental parameters can include temperature parameters, humidity parameters, gas concentration parameters, light intensity parameters, noise level parameters and the like in the room where the air conditioner is located.

[0071] It can be understood that the step aims to make the air conditioner learn the use habits of the target user by collecting actual operation parameters corresponding to actual environment parameters, so as to establish and train a behavior prediction model of the target user, and then in the subsequent working process, the air conditioner can intelligently adjust the operation parameters based on the behavior prediction model and according to the actual environment parameters at that time to predict the demand of the target user.

[0072] Step S302: training the behavior prediction model based on the actual operation parameters and the actual environment parameters to obtain a new behavior prediction model.

[0073] In some embodiments, the air conditioner obtains the environmental sensory parameters, for example, in real time or every fixed time, to compare and analyze the actual environment parameters at the time of user input with the measured environmental sensory parameters to obtain the environmental sensory change characteristic information before the user input. The air conditioner also compares and analyzes the actual operation parameters with the operation parameters before the input to obtain the operation parameter change characteristic information corresponding to the environmental sensory change characteristic information, and then trains the behavior prediction model according to the corresponding relationship between the environmental sensory change characteristic information and the operation parameter change characteristic information.

[0074] In other embodiments, the air conditioner also obtains the time parameter at the time of input in response to the input of the user interface, and trains the behavior prediction model based on the actual operation parameters, the actual environment parameters and the time parameter to obtain a new behavior prediction model. For example, the user adjusts the temperature setting of the air conditioner multiple times in a target time period, for example, adjusts the temperature of the air conditioner to be higher multiple times in the time period of 22:00-23:00, and the air conditioner trains the behavior prediction model by learning the habit of the user, and then realizes the personalized adjustment of the operation parameters.

[0075] In practical application, the user can also make feedback according to the experience brought by the operation of the air conditioner, and the air conditioner continuously optimizes the behavior prediction model according to the feedback of the user to provide more suitable air conditioner experience for the user.

[0076] The control method of the air conditioner provided by the embodiments of the present application can continuously learn the user behavior, analyze and learn the user behavior according to the prediction algorithm, predict the user demand and automatically adjust the operation parameters of the air conditioner, thereby creating a personalized and intelligent comfortable environment for the user, gradually reducing the operation times of the user, enabling the user to feel the liberation of both hands brought by comfortable and intelligent control, and improving the evaluation and stickiness of the user.

[0077] Step S204: feature extraction is performed on the power consumption parameters to obtain power consumption characteristic information;

[0078] Step S205: the mood type information, the environmental sensory characteristic information and the power consumption characteristic information are fused according to a preset weight to obtain adjustment reference characteristic information.

[0079] In the preset weight, the weight of the emotion type information is greater than the weight of the environmental sensory feature information and the power consumption feature information.

[0080] For example, the emotion type information, the environmental sensory feature information and the power consumption feature information are input into a feature fusion network, and the emotion type information, the environmental sensory feature information and the power consumption feature information are respectively processed by feature alignment to obtain the final adjustment reference feature information.

[0081] In some embodiments, the air conditioner further extracts the environmental sensory parameters to obtain seasonal information, and fuses the emotion type information, the environmental sensory feature information, the power consumption feature information and the seasonal information according to preset weights to obtain the adjustment reference feature information.

[0082] Step S206: determining a target operation mode according to the adjustment reference feature information;

[0083] Step S207: taking preset operation parameters corresponding to the target operation mode as target operation parameters;

[0084] For example, the air conditioner determines a target emotion mode, a target behavior mode and a target energy consumption mode according to the adjustment reference feature information, and determines the target operation mode according to a preset corresponding relationship between combinations of the multiple emotion modes, the behavior modes and the energy consumption modes and the multiple operation modes. The multiple operation modes are one-to-one corresponding to multiple operation parameters, so that the corresponding target operation parameters are determined according to the target operation mode.

[0085] Step S208: controlling the air conditioner to operate according to the target operation parameters;

[0086] The control method of the air conditioner provided by the embodiments of the present application can realize comprehensive optimization of the individualized adaptability, intelligence, environmental adaptability and energy efficiency of the air conditioner, thereby greatly improving the user comfort and reducing the energy consumption, and also bringing great development space for the future smart home field. Moreover, the behavior prediction model is established by learning the use habits of the user to the air conditioner, the environmental sensory feature information is obtained by extracting the environmental sensory parameters according to the behavior prediction model, and the target operation parameters are analyzed, thereby further improving the individualized adaptability of the air conditioner.

[0087] In some embodiments, after the air conditioner operates according to the target operation parameters, in order to reduce the energy consumption of the air conditioner as much as possible, the air conditioner further performs the following steps:

[0088] Step S209: collecting indoor temperature data after the air conditioner operates for a preset time according to the target operation parameters;

[0089] The indoor area refers to the room where the air conditioner is located.

[0090] Step S210: Fit a temperature change curve based on indoor temperature data and a preset time.

[0091] Step S211: Based on the temperature change curve, predict the expected indoor temperature at the target time;

[0092] Step S212: Adjust the target operating parameters according to the expected indoor temperature.

[0093] Adjusting target operating parameters may include, for example, adjusting the operating frequency of the air conditioner to achieve energy saving or other purposes. For instance, the air conditioner acquires the actual indoor temperature at a target time. If the actual indoor temperature is lower than the expected indoor temperature data, a first frequency offset value is determined based on the expected indoor temperature data and the actual indoor temperature, and the operating frequency of the air conditioner is reduced by the first frequency offset value. If the actual indoor temperature is higher than the expected indoor temperature data, a second frequency offset value is determined based on the expected indoor temperature data and the actual indoor temperature, and the operating frequency of the air conditioner is increased by the first frequency offset value.

[0094] This application embodiment also provides an air conditioner storage medium, on which a computer program is stored, and the computer program executes the above-described air conditioner control method when it runs.

[0095] This application also provides an air conditioner, for example, please refer to [link to example]. Figure 4 , Figure 4 This is a schematic diagram of the structure of an air conditioner provided in an embodiment of this application. The air conditioner 100 includes an emotion recognition module 110, an environmental perception module 120, a power consumption monitoring module 130, and a main processor 140.

[0096] The emotion recognition module 110 is used to acquire the physiological parameters of the target user and determine the target user's emotion type information based on the physiological parameters. For example, see [link to example]. Figure 5 , Figure 5 This is a schematic diagram of the structure of an emotion recognition system provided in an embodiment of this application. The emotion recognition system 10 includes an air conditioner 100 and a wearable device 200. The emotion recognition module 110 of the air conditioner 100 is communicatively connected to the wearable device 200, so that the wearable device 200 transmits the collected physiological parameters of the target user to the emotion recognition module 110.

[0097] The environmental sensing module 120 includes, for example, various sensors and an environmental parameter processor. The various sensors are used to collect different environmental data, and the environmental parameter processor integrates and processes the data collected by the multiple sensors to obtain environmental perception parameters.

[0098] The power consumption monitoring module 130 is configured to detect a power consumption parameter of the air conditioner 100, which can include a power consumption parameter of the air conditioner body and power consumption parameters of various load modules in the air conditioner.

[0099] The total processor 140 is connected with the emotion recognition module 110, the environment perception module 120 and the power consumption monitoring module 130, and is configured to acquire the physiological parameter of the target user, the current environment body feeling parameter and the power consumption parameter of the air conditioner; generate adjustment reference feature information according to the physiological parameter, the environment body feeling parameter and the power consumption parameter; determine the target operation parameter of the air conditioner according to the adjustment reference feature information; and control the air conditioner to operate according to the target operation parameter.

[0100] The air conditioner provided by the embodiments of the present application can obtain the target operation parameter by comprehensively analyzing the physiological parameter of the target user, the current environment body feeling parameter and the power consumption parameter of the air conditioner, and can realize comprehensive optimization of individual adaptability, intelligence, environment adaptability and energy efficiency of the air conditioner, thereby greatly improving user comfort and reducing energy consumption, and also bringing huge development space for the future smart home field.

[0101] The control method of the air conditioner, the storage medium and the air conditioner provided by the embodiments of the present application are described in detail above, and the principles and implementation manners of the present application are described by applying specific examples; the above embodiment descriptions are only used to help understand the method of the present application and its core idea; meanwhile, for those skilled in the art, the specific implementation manners and application ranges will be changed according to the idea of the present application, and in summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A control method of an air conditioner, characterized by, The method comprises: acquiring physiological parameters of a target user, current environmental parameters, and power consumption parameters of the air conditioner; generating adjustment reference feature information according to the physiological parameters, the environmental parameters, and the power consumption parameters, including: performing feature extraction on the environmental parameters to obtain environmental feature information; determining target operating parameters of the air conditioner according to the adjustment reference feature information; controlling the air conditioner to operate according to the target operating parameters; wherein the feature extraction on the environmental parameters to obtain environmental feature information comprises: obtaining actual operating parameters in response to input of a user interface, and acquiring actual environmental parameters at the time of the input; training a behavior prediction model based on the actual operating parameters and the actual environmental parameters to obtain a new behavior prediction model; performing feature extraction on the environmental parameters by using the new behavior prediction model to obtain environmental feature information.

2. The control method of the air conditioner according to claim 1, characterized by, The generation of the adjustment reference feature information according to the physiological parameters, the environmental parameters, and the power consumption parameters comprises: determining emotional type information of the target user according to the physiological parameters; performing feature extraction on the environmental parameters to obtain environmental feature information; performing feature extraction on the power consumption parameters to obtain power consumption feature information; fusing the emotional type information, the environmental feature information, and the power consumption feature information according to a preset weight to obtain the adjustment reference feature information.

3. The control method of the air conditioner according to claim 1 or 2, characterized by, The determination of the target operating parameters of the air conditioner according to the adjustment reference feature information comprises: determining a target operating mode according to the adjustment reference feature information; taking preset operating parameters corresponding to the target operating mode as the target operating parameters.

4. The control method of the air conditioner according to claim 1 or 2, characterized by, Before the generation of the adjustment reference feature information according to the physiological parameters, the environmental parameters, and the power consumption parameters, the method further comprises: acquiring behavior state information of the target user; The generation of the adjustment reference feature information according to the environmental parameters, the power consumption parameters, and the physiological parameters comprises: generating the adjustment reference feature information according to the environmental parameters, the power consumption parameters, the physiological parameters, and the behavior state information.

5. The control method of the air conditioner according to claim 1 or 2, characterized by, Before the generation of the adjustment reference feature information according to the physiological parameters, the environmental parameters, and the power consumption parameters, the method further comprises: acquiring a current time parameter; The generation of the adjustment reference feature information according to the environmental parameters, the power consumption parameters, and the physiological parameters comprises: generating the adjustment reference feature information according to the environmental parameters, the power consumption parameters, the physiological parameters, and the time parameter.

6. The control method of the air conditioner according to claim 1 or 2, characterized by, After the control of the air conditioner to operate according to the target operating parameters, the method further comprises: collecting indoor temperature data after a preset time of operation according to the target operating parameters; fitting a temperature change curve according to the indoor temperature data and the preset time; predicting an expected indoor temperature at a target time according to the temperature change curve; adjusting the target operating parameters according to the expected indoor temperature.

7. A storage medium of an air conditioner, characterized by, A computer program is stored on the computer program, and the computer program runs to execute the control method of the air conditioner according to any one of claims 1-6.

8. An air conditioner characterized by comprising: A control method for performing the air conditioner as claimed in any one of claims 1-6.

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