Air conditioner control method and air conditioner system

Abstract

The invention discloses an air conditioner control method and an air conditioner system. The air conditioner control method comprises the steps that air conditioner data and user data are collected, and a relation model capable of outputting comfortable temperature ranges of corresponding users under different scenes is trained and updated regularly; when the air conditioner runs, current air conditioner data and current user data are collected in each adjusting period; when a single user uses the air conditioner, a single user mode is started, current air conditioner data and current user data are input into the relation model, and the comfortable temperature range of the user is obtained; the target temperature of the air conditioner during heating is controlled to be within a certain range away from the minimum value of the comfortable temperature range and is larger than the temperature value of the minimum value; and / or the target temperature of the air conditioner during refrigeration is controlled to be within a certain range away from the maximum value of the comfortable temperature range and is smaller than the temperature value of the maximum value. According to the invention, the comfort requirement can be met, and the energy consumption can be saved.

Description

Technical Field

[0001] The present invention relates to the technical field of air-conditioning systems, and in particular to a control method for an air-conditioning system with intelligent response. Background Art

[0002] As environmental awareness becomes increasingly prominent, green energy conservation has become a common development trend in the global home appliance market. How to use as little energy as possible to create a more comfortable environment for users has become the common direction of all air-conditioning equipment manufacturers. For example, the use of variable frequency compressors enables air conditioners to operate more efficiently, reduce energy waste, and improve energy efficiency; the speed of the compressor can also be automatically adjusted according to changes in indoor temperature, thereby achieving precise temperature control. Further, photovoltaic systems can be introduced for energy supply, and green energy can be used to reduce the dependence of equipment on traditional energy.

[0003] The above existing methods of reducing air conditioning energy consumption are all adjusted from the software and hardware conditions of the system itself. A more intelligent control method can also be used for the user side, but the existing user-side control method is usually to meet the user's comfort.

[0004] For example, in the prior art, the user's air-conditioning usage data, as well as the air-conditioning operation data and the air-conditioning environmental data are collected to train the corresponding intelligent control model. Through the intelligent control module, a comfortable target temperature value can be automatically output for the user based on the corresponding air-conditioning environmental data and the user's corresponding activity status. The air-conditioning system then uses the target temperature value as the target temperature of the air-conditioning to provide comfort for the user.

[0005] The above control method has the following problems.

[0006] Usually the model outputs an exact comfort target temperature. If the air-conditioning operation is not adjusted according to the exact comfort target temperature, the training significance of the model is relatively weak. However, once it is adjusted according to the exact comfort target temperature, the air-conditioning control will lack room for energy saving.

[0007] Furthermore, in the process of training the model, it is usually more convenient to consider the user comfort issue, while it is more difficult to consider the energy saving of air conditioning. The reason is that the training of the model depends on the user's adjustment data. Most users use air conditioning mainly based on their own comfort considerations and it is difficult to consider energy saving issues.

[0008] Finally, the existing air conditioning control methods and models are mostly for a single user. When multiple users are within the range of the same air conditioner, how to satisfy both comfort and reduce corresponding energy consumption is also a relatively blank area in the existing technology.

[0009] Therefore, how to provide an air conditioning control method that can both meet user comfort needs and reduce energy consumption is a technical problem to be solved. Summary of the invention

[0010] In order to solve the technical problem in the prior art that when an air conditioner adjusts a target temperature controlled on a user side, energy-saving adjustment cannot be performed, the present invention proposes a control method and an air conditioner system.

[0011] The air conditioner control method of the present invention comprises:

[0012] Collect air conditioning data and user data, and regularly train and update the relationship model that can output the corresponding user's comfortable temperature range in different scenarios;

[0013] When the air conditioner is running, the current air conditioner data and current user data are collected in each adjustment cycle;

[0014] When a single user uses the air conditioner, the single user mode is entered, and the current air conditioner data and the current user data are input into the relationship model to obtain the user's comfortable temperature range;

[0015] When controlling heating, the target temperature of the air conditioner is a temperature value within a certain range from a minimum value of the comfortable temperature range and greater than the minimum value; and / or

[0016] When controlling cooling, the target temperature of the air conditioner is a temperature value within a certain range from a maximum value of the comfortable temperature range and less than the maximum value.

[0017] Furthermore, when multiple users use the air conditioner, if multiple users have a comfortable temperature range, it is determined whether each user is located in the same sweeping fan area within the sweeping range. If so, the user with a higher frequency of adjusting the target temperature is selected according to the user data, and the single user mode is entered based on the user's comfortable temperature range.

[0018] Further, if each user is located in a different wind sweeping fan zone within the wind sweeping range, the comfortable temperature ranges of two users in two adjacent sectors are compared. If the comfortable temperature ranges of the two users overlap, the target temperature of the air conditioner during heating control is set to a temperature value within a certain range from a minimum value of the overlapping range and greater than the minimum value; and / or

[0019] When controlling cooling, the target temperature of the air conditioner is set to a temperature value within a certain range from the maximum value of the overlapping range and smaller than the maximum value.

[0020] Furthermore, if the comfortable temperature ranges of two users in two adjacent sectors do not overlap, the average of the maximum value of the lower comfortable temperature range and the minimum value of the higher comfortable temperature range is taken as the target temperature;

[0021] And when heating, the windshield in the lower comfortable temperature range is lowered, and the windshield in the higher comfortable temperature range is raised; and / or when cooling, the windshield in the lower comfortable temperature range is raised, and the windshield in the higher comfortable temperature range is lowered.

[0022] Furthermore, when multiple users use the air conditioner, if only one user has a comfortable temperature range, the single-user mode is entered to control the target temperature of the air conditioner.

[0023] Furthermore, if the user adjusts the target temperature of the air conditioner and / or the windshield of the corresponding fan zone in each adjustment cycle, the user's adjustment shall prevail, and corresponding air conditioning data and user data are collected based on the user's adjustment.

[0024] Furthermore, during the collection process, user data of the corresponding user and air-conditioning data of the user when using the air-conditioner are collected with each user as a unit to train and update the relationship model.

[0025] Furthermore, during the initial collection, the target temperature set by the user is used as a reference, the preset adjustment value is reduced and increased in sequence, and the user data is recorded to obtain the minimum and maximum values ​​of the user's comfortable temperature range under the corresponding air-conditioning data.

[0026] Furthermore, the air conditioning data includes: air conditioning operation data and air conditioning environment data; the user data includes: user activity status data and user adjustment data for the air conditioning.

[0027] The air conditioning system proposed in the present invention comprises a controller, and the controller is controlled according to the air conditioning control method of the above technical solution.

[0028] The present invention constructs a relationship model between user behavior, working conditions and the target temperature of air-conditioning operation through user data and air-conditioning data, and the relationship model can obtain the comfortable temperature range of each user, and select the target temperature that can reduce the energy consumption of the air-conditioning within the user's comfortable temperature range as the final target temperature, which can not only meet the user's comfort needs, but also reduce the energy consumption of the air-conditioning. Furthermore, the present invention can also realize the specific control strategy for multiple users, and reduce the energy consumption of the air-conditioning as much as possible while meeting the comfort needs of multiple users, thus filling the gap in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present invention is described in detail below with reference to the embodiments and accompanying drawings, wherein:

[0030] Figure 1 Schematic diagram of a control structure according to an embodiment of the present invention.

[0031] Figure 2 is a flow chart of an embodiment of the present invention.

[0032] Figure 3 is a flow chart of another embodiment of the present invention.

[0033] Figure 4 is a flow chart of other embodiments of the present invention.

[0034] Figure 5 FIG. 1 is a simplified block diagram of an air conditioner according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0036] Thus, a feature indicated in this specification will be used to illustrate one of the features of an embodiment of the present invention, rather than implying that each embodiment of the present invention must have the described feature. In addition, it should be noted that this specification describes many features. Although some features can be combined together to illustrate possible system designs, these features can also be used in other combinations that are not explicitly described. Thus, unless otherwise stated, the described combinations are not intended to be limiting.

[0037] like Figure 1 , Figure 2 As shown, in a basic embodiment, the air conditioner control method of the present invention includes the following steps.

[0038] The present invention needs to collect air conditioning data and user data, and regularly train and update the relationship model that can output the comfortable temperature range of the corresponding user in different scenarios.

[0039] When the air conditioner is running, the current air conditioner data and current user data are collected in each adjustment cycle;

[0040] If a single user is using the air conditioner at this time, the single-user mode is entered, and the current air-conditioning data and the current user data are input into the relationship model to obtain the user's comfortable temperature range. When controlling heating, the target temperature of the air conditioner is a temperature value that is within a certain range from the minimum value of the comfortable temperature range and is greater than the minimum value; and / or when controlling cooling, the target temperature of the air conditioner is a temperature value that is within a certain range from the maximum value of the comfortable temperature range and is less than the maximum value.

[0041] For example, when cooling, the comfortable temperature range of user A is (21, 28) when the ambient temperature is 34 degrees Celsius. In the current scenario, the target temperature of the air conditioner is adjusted to 27 degrees, which can not only meet the user's comfort needs, but also reduce the energy consumption of the air conditioner.

[0042] Since the relational model of the present invention outputs not the exact comfortable temperature of the user in different scenarios, but a comfortable temperature range, when controlling the target temperature of the air conditioner, the target temperature that is more conducive to energy saving can be selected according to the operating mode of the air conditioner to adjust the air conditioner, thereby creating a stable and comfortable use environment with the least possible power consumption.

[0043] like Figure 3 As shown, in another embodiment, when multiple users use the air conditioner at the same time, if multiple users have a comfortable temperature range, that is, the data of the corresponding users are collected during the relationship model training stage, the air conditioning system will determine whether these users are in the same sweep fan area. If they are in the same sweep fan area, the user with a higher frequency of adjusting the target temperature will be preferentially selected according to the user data, and the temperature will be switched to the single user mode for temperature adjustment based on the user's comfortable temperature range.

[0044] This embodiment describes a usage scenario for multiple users. In fact, this is also a relatively common scenario. If the air-conditioning system recognizes multiple users, but for users who lack historical data, if the corresponding current user data and current air-conditioning data are collected and input into the relationship model, the user's comfortable temperature range will not be obtained. At this time, the control is based on the user with historical data. This embodiment describes the collection of current user data and current air-conditioning data of multiple users who are currently using the air conditioner. For the same indoor unit, the current air-conditioning data of multiple users are the same, and only the user data may be different. The current user data and current air-conditioning data of multiple users are input into the relationship model, and multiple comfortable temperature ranges can be obtained, which means that multiple users have comfortable temperature ranges. If these users with comfortable temperature ranges are located in the same fan sweeping area, the user who adjusts the target temperature most frequently has absolute decision-making power over the air conditioner. Therefore, the single-user mode is entered based on the user.

[0045] For example, both user A and user B have comfortable temperature ranges, and user A and user B are in the same fan sweeping zone. If user A adjusts the target temperature more frequently than user B, the target temperature of the air conditioning system is adjusted based on the comfortable temperature range of user A. For example, when user A and user B are in the same fan sweeping zone in the past month, the user who adjusts the target temperature more frequently between user A and user B can be used as the standard. Those skilled in the art can also adjust the duration of the user adjustment frequency in the recent period as needed, for example, adjusting it to the past week to see who adjusts the frequency more frequently between user A and user B.

[0046] Assume that user A is used as the standard and the single-user mode is entered. At this time, user B feels uncomfortable and adjusts the target temperature. Then the adjustment time and the adjusted target temperature of user B are stored as the user data of user B, and the air conditioning data corresponding to the user data is stored. After that, the relationship model can be trained according to the latest air conditioning data and user data of user B to obtain the most suitable comfortable temperature range for the current user B. Assume that although the target temperature is adjusted based on the comfortable temperature range of user A, user B does not adjust the target temperature at this time, the user data and air conditioning data of user B at this time can also be recorded to provide more data basis for the further accuracy of the machine self-learning of the comfortable temperature range of user B.

[0047] This method of identifying multi-user scenarios and making adjustments based on the situation or collecting data in a timely manner to update the relationship model not only realizes the intelligent optimization of temperature regulation, but also improves the user experience, effectively avoids temperature conflicts in multi-user scenarios, and provides higher adaptability and flexibility for the intelligence of the air-conditioning system.

[0048] like Figure 4 As shown, in one embodiment, when multiple users use the air conditioner at the same time, if multiple users have comfortable temperature ranges, that is, data of corresponding users are collected during the relationship model training stage, the air conditioning system determines that these users are located in different air sweeping fan zones within the air sweeping range. The air conditioning system compares the comfortable temperature ranges of two users in two adjacent sectors. If the comfortable temperature ranges of the two users overlap, the target temperature of the air conditioner when controlling heating is set to a temperature value within a certain range from the minimum value of the overlapping range and greater than the minimum value; and / or the target temperature of the air conditioner when controlling cooling is set to a temperature value within a certain range from the maximum value of the overlapping range and less than the maximum value.

[0049] This situation is a practice of reducing mutual influence between different users in two adjacent sweeping fan zones. Taking cooling as an example, when the comfort temperature range of user A is (20, 27) and the comfort temperature range of user B is (25, 28), there is an overlapping range between user A and user B. At this time, 26 degrees Celsius or 26.5 degrees Celsius is selected as the target temperature of the air-conditioning system. In this way, although user A and user B are located in different sectors, in fact, user A and user B both use the same target temperature, which not only meets the comfort needs of user A and user B, but also saves energy compared to the lowest target temperature of user A. Since both sectors use the same target temperature, the two sectors can actually be regarded as merged into one sector in terms of control, which simplifies the control process.

[0050] Based on this embodiment, there is a more complicated situation. For example, there are users A and C in the first sector, and there are users B and D in the second sector, and users A to D all have comfortable temperature ranges. In this case, the control method is to first judge multiple users in the same sector based on each sector (for example, two, but in fact, three or more), that is, to judge which user in the first sector has the highest frequency of adjustment in the recent period of time, and then take this user as the standard. Assuming that the first sector is the user A who has the highest frequency of adjusting the target temperature in the recent period of time, the first sector is based on user A. The same judgment is made for the second sector. Assuming that the second sector is the user B who has the highest frequency of adjustment in the recent period of time, the second sector is based on user B. Then, since the first sector and the second sector are adjacent, it is judged whether the comfortable temperature ranges of users A and B overlap. If there is an overlapping range, according to the difference between the cooling condition and the heating condition, the most energy-saving and simultaneously satisfying target temperature of users A and B in the overlapping range is selected. In this way, the needs of all users are met while simplifying control and reducing system energy consumption.

[0051] Assume that after the target temperature is adjusted, one of users A to D feels uncomfortable and adjusts the target temperature. The user data of the user is updated, and the adjustment time and the adjusted target temperature of the user are stored as the user data of the user, and the air-conditioning data corresponding to the user data is stored. After that, the relationship model can be trained according to the user's latest air-conditioning data and user data to obtain the most suitable comfortable temperature range for the current user.

[0052] In one embodiment, if the comfort temperature ranges of two users in the first sector and the second sector do not overlap, the average of the maximum value of the lower comfort temperature range and the minimum value of the higher comfort temperature range is taken as the target temperature, and the windshield of the lower comfort temperature range is lowered and the windshield of the higher comfort temperature range is raised during heating; and / or the windshield of the lower comfort temperature range is raised and the windshield of the higher comfort temperature range is lowered during cooling.

[0053] For the same indoor unit, when the comfort temperature ranges of multiple users are quite different and they are not in the same sector, adjustments can be made according to the situation. For the target temperature, the average of the maximum value in the smaller range and the minimum value in the larger range can be taken to meet the needs of different users in the two sectors as much as possible. Since the selected target temperature is not within the comfort temperature range of the users in the two sectors, the windshield can be adjusted to meet the comfort requirements of the users as much as possible.

[0054] In a more complex embodiment, assuming that the air conditioner has more than two sweep fan zones, there will be a sweep fan zone adjacent to the other two sweep fan zones, for example, the second sweep fan zone is adjacent to both the first sweep fan zone and the third sweep fan zone. Then, the comfortable temperature range of the users in the first sweep fan zone and the users in the second sweep fan zone can be compared first. If there is an overlapping range between the two, the target temperature is adjusted based on the overlapping range. At this time, the target temperatures of the users in the first sweep fan zone and the second sweep fan zone are unified, so in fact, the first sweep fan zone and the second sweep fan zone can be regarded as the same sector. Then, the overlapping range of the two sweep fan zones is compared with the comfortable temperature range of the users in the third sweep fan zone to see if there is an overlapping range. If so, their overlapping range is further found. Based on the final overlapping range, the three sweep fan zones can be merged and controlled. Assuming that the third sweep fan zone has no overlapping range with the first two merged sweep fan zones, the average value of the maximum value of the lower range and the minimum value of the higher range between the two is used as the target temperature.

[0055] Assuming that there is no overlapping area between the first sweep fan area and the second sweep fan area, check whether there is an overlapping area between the second sweep fan area and the third sweep fan area. If there is an overlapping area between the second sweep fan area and the third sweep fan area, first merge the second sweep fan area and the third sweep fan area, and then compare them with the comfortable temperature range of users in the first sweep fan area to see if there is an overlapping range. If so, process it as if there is an overlapping range. If not, take the corresponding average value based on the overlapping range of the second and third sweep fan areas and the comfortable temperature range of users in the first sweep fan area (the method of taking the average value is described in detail in other cases).

[0056] For the same outdoor ambient temperature and the same user activity status, the situation where the comfortable temperature ranges of users located in three or more sweeping fan zones have no overlap is relatively rare and is therefore not within the scope of discussion of the present invention.

[0057] In one embodiment, when multiple users use the air conditioner, if and only one user has a comfortable temperature range, the single-user mode is entered to control the target temperature of the air conditioner. For example, when there are guests at home, or new employees in the company, since they are new to the company and lack historical data, the user with a comfortable temperature range is used as the standard at this time, and the single-user mode is entered to adjust the target temperature. If the guest feels that the target temperature is uncomfortable and adjusts the target temperature of the air conditioner, the guest's adjustment time, the adjusted target temperature, the corresponding air conditioning data at this time, etc. can be stored as the guest's data to facilitate the training of the relationship model. If the guest does not adjust the target temperature at this time, the user data and air conditioning data of the current guest can also be recorded to accumulate the historical data corresponding to the guest, so as to facilitate the training of the relationship model.

[0058] In the above embodiment, if the user adjusts the target temperature of the air conditioner and / or the windshield of the corresponding fan zone in each adjustment cycle, the user's adjustment shall prevail, and corresponding air conditioning data and user data are collected based on the user's adjustment.

[0059] In the above embodiment, when collecting data, each user is used as a unit, and the user data of the corresponding user and the air conditioning data of the user when using the air conditioner are collected to train and update the relationship model. For homes and offices, the users are usually relatively fixed, so the air conditioner can be equipped with some identification devices to identify each user, so as to collect user data. This provides more data basis for the intelligent control of the air conditioner.

[0060] The collection of training data required for the relational model of the present invention is carried out in two stages.

[0061] The first stage is the initial collection stage. There is no training data at this stage. Users do not necessarily adjust the target temperature of the air conditioner frequently. Usually, after selecting a target temperature, they may keep it on all day. Therefore, even for a single user, the collected data is very small.

[0062] At this stage, the present invention will use the target temperature set by the user as a benchmark, reduce the preset adjustment value in sequence and increase the preset adjustment value in sequence, and record the user data to obtain the minimum and maximum values ​​of the user's comfortable temperature range under the corresponding air-conditioning data.

[0063] For example, in cooling mode, if the target temperature set by the user is 26 degrees Celsius, the air conditioning system can first adjust the target temperature to 25, 24, and 23 degrees Celsius in sequence to see the user's reaction. Suppose the user adjusts the target temperature or windshield when the target temperature is adjusted to 24 degrees Celsius, then it can be known that 24 degrees Celsius is the minimum value of the user's comfortable temperature range of the current ambient temperature. Similarly, the target temperature can be adjusted to 27, 28, and 29 degrees in sequence based on 26 degrees Celsius. When it is adjusted to 29 degrees, the user adjusts the target temperature, and it can be known that the maximum value of the user's comfortable temperature range is 28 degrees Celsius. The user's comfortable temperature range can be obtained through tentative adjustments of the air conditioning system.

[0064] The second stage is the collection stage during the use process after the relational model is officially used. In this collection stage, since the air-conditioning system will adjust the target temperature based on the number of users and the different sectors in which the users are located, the users will feel uncomfortable and will actively adjust the target temperature. This can also further collect user data and corresponding air-conditioning data.

[0065] For a scenario with multiple users, if the target temperature is adjusted based on a certain user, but the user does not feel uncomfortable and does not adjust the target temperature, this data can also be recorded to supplement the corresponding data for training the user's comfortable temperature range.

[0066] In the above embodiments of the present invention, the air conditioning data includes: the operation data of the air conditioning and the environmental data of the air conditioning. The operation data of the air conditioning may include the target temperature of the air conditioning, the air outlet temperature of the air conditioning, the target humidity of the air conditioning, the windshield of each fan zone of the air conditioning, etc. The environmental data of the air conditioning may include the outdoor environment temperature, the outdoor environment humidity, the operation season, the operation time period (e.g., morning, noon, evening), etc.

[0067] In the above embodiments, the user data includes: user activity status data and user adjustment data for the air conditioner. The user activity status data can be specifically determined based on the user's heart rate, etc., or based on a camera, etc. The user activity status data can be divided into daily activities, exercise, sleep, etc. The user adjustment data for the air conditioner can include the adjusted target temperature, the adjusted windshield, etc.

[0068] The present invention also protects a corresponding air-conditioning system, which includes a controller, and the controller is controlled according to the air-conditioning control method of the above-mentioned technical solution, so that the air-conditioning system can meet the comfort of each user using the air-conditioning as much as possible, and reduce the energy consumption of the air-conditioning as much as possible on the basis of meeting the user's comfort.

[0069] In order to cooperate with the implementation of the above control method, the air conditioning system can be equipped with temperature sensors, humidity sensors, brightness sensors, etc. to monitor indoor and outdoor environmental parameters and operating data such as outlet temperature and windshield in real time. The air conditioning system can also be equipped with some cameras, human displacement sensors, visual sensors, human sensors and other devices to collect user data. By learning user data, the relationship model can know the user's activity status and the user's adjustment of the air conditioner, etc. Taking the user's sleep as an example, if the adjustment of the target temperature causes the user to kick the quilt, the body surface temperature rises, etc., these user data of the user can be recorded, so that during the user's sleep stage, more accurate training data can be obtained to update the relationship model. The sensors exemplified here are not used to limit the scope of protection of the present invention. Those skilled in the art can also replace them with other sensors according to the needs of collecting data. Figure 5 A brief block diagram of an air-conditioning system is shown. In the block diagram, the air-conditioning system includes environmental sensors (such as indoor and outdoor ambient temperature sensors, indoor and outdoor ambient humidity sensors, etc.), a controller, a human activity sensor (such as a camera, etc.), and a signal transmission module (such as a 5G communication module, etc.).

[0070] The indoor unit of the air-conditioning system of the present invention has different sweep fan zones, and the wind shields in different sweep fan zones can be adjusted. Usually, the ceiling unit has different sweep fan zones, usually four sweep fan zones, and there are also ceiling units with eight sweep fan zones. Different wind shields can be adjusted for each sweep fan zone. Some household wall-mounted units do not have different sweep fan zones, and some technical solutions of the present invention cannot be applied (such as different sweep sectors need to be adjusted to different wind shields). However, some wall-mounted units have a larger sweep range and the wind shields in different sweep fan zones within the sweep range can apply all the technical solutions of the present invention.

[0071] The relational model in the above technical solution can be set in the air-conditioning system or located on the server. Therefore, in addition to obtaining air-conditioning data and user data, the air-conditioner also needs to have the ability to communicate with the server.

[0072] The relationship model of the present invention can be a neural network model, or a decision tree or other similar machine self-learning model.

[0073] Based on the above technical scheme of the present invention, the present invention can realize comfort adjustment for specific users while reducing the energy consumption of the air-conditioning system as much as possible. Technical personnel in this field can further combine the energy-saving adjustment of the air-conditioning system itself on the basis of the present invention to achieve better energy-saving effects.

[0074] The above description is only a preferred embodiment of the present invention and is 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 in the protection scope of the present invention.

Claims

1. A method for controlling an air conditioner, characterized in that: include: Collect air conditioning data and user data, and regularly train and update the relationship model that can output the corresponding user's comfortable temperature range in different scenarios; When the air conditioner is running, the current air conditioner data and current user data are collected in each adjustment cycle; When a single user uses the air conditioner, the single user mode is entered, and the current air conditioner data and the current user data are input into the relationship model to obtain the user's comfortable temperature range; When controlling heating, the target temperature of the air conditioner is a temperature value within a certain range from a minimum value of the comfortable temperature range and greater than the minimum value; and / or When controlling cooling, the target temperature of the air conditioner is a temperature value within a certain range from a maximum value of the comfortable temperature range and less than the maximum value.

2. The air conditioner control method according to claim 1, characterized in that: When multiple users use the air conditioner, if multiple users have a comfortable temperature range, it is determined whether each user is located in the same sweep fan area within the sweep range. If so, the user with a higher frequency of adjusting the target temperature is selected based on the user data, and the single user mode is entered based on the user's comfortable temperature range.

3. The air conditioner control method according to claim 2, characterized in that: If each user is located in a different sweep fan zone within the sweep air range, the comfortable temperature ranges of two users in two adjacent sectors are compared. If the comfortable temperature ranges of the two users overlap, the target temperature of the air conditioner during heating control is set to a temperature value within a certain range from the minimum value of the overlapping range and greater than the minimum value; and / or When controlling cooling, the target temperature of the air conditioner is set to a temperature value within a certain range from the maximum value of the overlapping range and smaller than the maximum value.

4. The air conditioner control method according to claim 3, characterized in that: If the comfortable temperature ranges of two users in two adjacent sectors do not overlap, the average of the maximum value of the lower comfortable temperature range and the minimum value of the higher comfortable temperature range is taken as the target temperature; And when heating, the windshield in the lower comfortable temperature range is lowered, and the windshield in the higher comfortable temperature range is raised; and / or when cooling, the windshield in the lower comfortable temperature range is raised, and the windshield in the higher comfortable temperature range is lowered.

5. The air conditioner control method according to claim 1, characterized in that: When multiple users use the air conditioner, if only one user has a comfortable temperature range, the single-user mode is entered to control the target temperature of the air conditioner.

6. The air conditioner control method according to any one of claims 1 to 5, characterized in that: If the user adjusts the target temperature of the air conditioner and / or the windshield of the corresponding fan zone in each adjustment cycle, the user's adjustment shall prevail, and corresponding air conditioning data and user data are collected based on the user's adjustment.

7. The air conditioner control method according to claim 1, characterized in that: During the collection, the user data of the corresponding user and the air-conditioning data of the user when using the air-conditioner are collected with each user as a unit to train and update the relationship model.

8. The air conditioner control method according to claim 7, characterized in that: During the initial collection, the target temperature set by the user is used as the benchmark, the preset adjustment value is reduced and increased in sequence, and the user data is recorded to obtain the minimum and maximum values ​​of the user's comfortable temperature range under the corresponding air-conditioning data.

9. The air conditioner control method according to claim 7, characterized in that: The air conditioning data includes: air conditioning operation data and air conditioning environment data; the user data includes: user activity status data and user adjustment data for the air conditioning.

10. An air conditioning system, comprising a controller, characterized in that: The controller performs control according to the air conditioner control method according to any one of claims 1 to 9.

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