Methods and devices for improving the intelligence of air conditioners

Abstract

This invention discloses a method and apparatus for improving the intelligence of air conditioners. The method includes: after the air conditioner is powered on, it enters an automatic operation mode and determines the outdoor sliding average temperature for the day; based on the outdoor sliding average temperature for the day and the set automatic operation mode, it determines the target temperature for each time period; it generates a temperature control table based on the target temperature for each time period; and it controls the temperature of the air conditioner according to the temperature control table. Using this invention, the control of air conditioners can be made more intelligent and comfortable.

Description

Technical Field

[0001] This invention relates to the field of air conditioning control technology, and more specifically to a method and apparatus for improving the intelligence of air conditioning. Background Technology

[0002] Currently, research on thermal comfort worldwide has entered a new era, particularly in air conditioning control. This research aims to provide people with more comfortable working and living environments, improving work efficiency and maintaining good health. Consequently, the industry has proposed the concept of comfort air conditioning, which refers to air conditioning systems that determine and control the main state parameters of indoor air according to human comfort requirements. However, due to the numerous factors affecting human comfort, and the need to consider energy consumption, the level of intelligence and comfort in air conditioners on the market still needs improvement, limited by current air conditioning control technology. Summary of the Invention

[0003] This invention provides a method and apparatus for improving the intelligence of air conditioners, thereby enhancing the intelligence of air conditioner control while meeting user needs.

[0004] Therefore, the present invention provides the following technical solution:

[0005] A method for improving the intelligence of an air conditioner, the method comprising:

[0006] The air conditioner enters automatic operation mode after being powered on.

[0007] Determine the outdoor sliding average temperature for the day;

[0008] The target temperature for each time period is determined based on the outdoor sliding average temperature of the day and the set automatic operation mode logic.

[0009] A temperature control table is generated based on the target temperature for each time period;

[0010] The air conditioner is used to control the temperature according to the temperature control table.

[0011] Optionally, determining the outdoor sliding average temperature for the day includes:

[0012] The outdoor daily average temperature for a given number of historical days is weighted and calculated to obtain the outdoor moving average temperature for that day.

[0013] Optionally, the historical setting period is the previous 7 days.

[0014] Optionally, the automatic operation mode logic includes: comprehensive prediction of the current set temperature based on historical set temperatures, independent prediction of the current set temperature based on historical weekday set temperatures, independent prediction of the current set temperature based on historical rest day set temperatures, and independent prediction of the current set temperature based on specific days of the week in the past.

[0015] Optionally, determining the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic includes:

[0016] Set the variable parameters corresponding to each logic item in the automatic operation mode logic;

[0017] Determine the relevant variable parameters for the day, and generate a target temperature calculation model based on the sliding temperature according to the logical terms corresponding to the variable parameters.

[0018] The target temperature for each time period is calculated based on the target temperature calculation model based on the sliding temperature.

[0019] Optionally, determining the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic further includes:

[0020] The target temperature calculation model based on sliding temperature is modified based on the thermophysiological regulation characteristics of the human body.

[0021] The calculation of the target temperature for each time period based on the target temperature calculation model based on sliding temperature includes:

[0022] The target temperature for each time period is calculated based on the modified target temperature calculation model based on sliding temperature.

[0023] Optionally, the method further includes:

[0024] Obtain current environmental parameters and user parameters, wherein the environmental parameters include: ambient temperature and / or humidity;

[0025] Based on the current set temperature in automatic operation mode, the current environmental parameters, and user parameters, the air conditioner's operating mode and operating parameters are determined. The operating modes include: cooling / heating mode and / or sleep mode; the operating parameters include: humidity control parameters, fresh air control parameters, and underfloor heating control parameters.

[0026] The air conditioner is controlled according to the determined working mode and parameters.

[0027] Optionally, the air conditioner operating mode includes: the automatic operating mode, and also includes one or more other operating modes;

[0028] The method further includes:

[0029] Record user intervention information regarding air conditioner operating mode and parameters, as well as temperature parameters, under the other operating modes;

[0030] The automatic operation mode logic is updated based on the intervention information.

[0031] A device for enhancing the intelligence of an air conditioner, the device comprising:

[0032] The operating mode selection module is used to enter the automatic operation mode after the air conditioner is powered on;

[0033] The sliding temperature determination module is used to determine the outdoor sliding average temperature for the day.

[0034] The target temperature determination module is used to determine the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic.

[0035] The temperature control table generation module is used to generate temperature control tables based on the target temperature for each time period.

[0036] The control module is used to control the temperature of the air conditioner according to the temperature control table.

[0037] Optionally, the target temperature determination module includes:

[0038] The parameter setting unit is used to set the variable parameters corresponding to each logic item in the automatic operation mode logic;

[0039] The model generation unit is used to determine the relevant variable parameters for the day and generate a target temperature calculation model based on the sliding temperature according to the logical terms corresponding to the variable parameters.

[0040] The calculation unit calculates the target temperature for each time period according to the target temperature calculation model based on the sliding temperature.

[0041] Optionally, the target temperature determination module further includes:

[0042] The correction unit is used to correct the target temperature calculation model based on the sliding temperature based on the human body's thermophysiological regulation characteristics.

[0043] The calculation unit calculates the target temperature for each time period based on the modified target temperature calculation model based on sliding temperature.

[0044] Optionally, the device further includes:

[0045] The parameter acquisition module is used to acquire environmental parameters and user parameters;

[0046] The working mode and parameter determination module is used to determine the air conditioner's working mode and working parameters based on the outdoor sliding average temperature of the day, the environmental parameters, and the user parameters. The working mode includes: cooling and heating mode, and / or sleep mode; the working parameters include: humidity control parameters, fresh air control parameters, and floor heating control parameters.

[0047] The control module is also used to control the air conditioner according to the determined working mode and working parameters.

[0048] Optionally, the air conditioner operating mode includes: the automatic operating mode, and also includes one or more other operating modes;

[0049] The device further includes:

[0050] The information recording module is used to record user intervention information regarding the air conditioner's operating mode, operating parameters, and temperature parameters under the other operating modes.

[0051] The logic update module is used to update the automatic operation mode logic based on the intervention information.

[0052] The method and apparatus for improving the intelligence of air conditioners provided in this invention enter an automatic operation mode after the air conditioner is powered on, and determine the outdoor sliding average temperature for the day; determine the target temperature for each time period based on the outdoor sliding average temperature for the day and the set automatic operation mode; generate a temperature control table based on the target temperature for each time period; and control the air conditioner temperature according to the temperature control table. Thus, automatic temperature control of the air conditioner can be achieved without manual intervention. Because the outdoor sliding average temperature for the day is considered when determining the target temperature for each time period, the target temperature of the air conditioner can change with the outdoor temperature at different times, making the air conditioner control more intelligent and comfortable.

[0053] Furthermore, the system automatically controls the air conditioner's operating mode and parameters by comprehensively considering the current set temperature, current outdoor environmental parameters (temperature, humidity, etc.), and user parameters in the automatic operation mode. The operating modes include cooling / heating mode and / or sleep mode; the operating parameters include humidity control parameters and fresh air control parameters. This allows the control of the air conditioner's operating mode and parameters to change according to variations in influencing factors at different times, effectively improving the user experience.

[0054] Furthermore, when multiple air conditioning operating modes coexist, the system can also record user intervention information regarding the air conditioning's operating mode, operating parameters, and temperature parameters in other operating modes. Based on this information, the automatic operating mode logic is updated, making the automatic operating mode logic more compatible with the user's individual needs. Thus, after running for a period of time, the automatic operating mode alone can fully meet the user's needs without human intervention, or with a very low probability of needing human intervention, greatly improving the intelligence of the air conditioner and achieving fully intelligent operation. Attached Figure Description

[0055] Figure 1 This is a flowchart of a method for improving the intelligence of an air conditioner according to an embodiment of the present invention;

[0056] Figure 2 This is a schematic diagram of a device for improving the intelligence of air conditioners according to an embodiment of the present invention;

[0057] Figure 3 This is another structural schematic diagram of the device for improving the intelligence of air conditioners according to an embodiment of the present invention. Detailed Implementation

[0058] To enable those skilled in the art to better understand the embodiments of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and implementation methods.

[0059] To address the issue of insufficient intelligence in existing air conditioner controls, this invention provides a method and apparatus for improving air conditioner intelligence. After the air conditioner is powered on, it enters automatic operation mode and determines the daily outdoor sliding average temperature. Based on the daily outdoor sliding average temperature and the set automatic operation mode, it determines the target temperature for each time period. A temperature control table is generated based on the target temperatures for each time period. The air conditioner's temperature is then controlled according to the temperature control table. This achieves automatic temperature control of the air conditioner without manual intervention. Because the daily outdoor sliding average temperature is considered when determining the target temperatures for each time period, the target temperature of the air conditioner can change with the outdoor temperature at different times, making the air conditioner control more intelligent and comfortable.

[0060] like Figure 1 The diagram shown is a flowchart of a method for improving the intelligence of an air conditioner according to an embodiment of the present invention, which includes the following steps:

[0061] Step 101: After the air conditioner is powered on, it enters automatic operation mode.

[0062] Step 102: Determine the outdoor sliding average temperature for the day.

[0063] The term "sliding temperature" is relative to "fixed temperature," meaning that the temperature changes at different times.

[0064] In this embodiment of the invention, the outdoor daily average temperature over a set number of historical days (e.g., 7 days) can be weighted to obtain the outdoor moving average temperature for that day.

[0065] For example, in a non-limiting embodiment, the outdoor sliding average temperature of the day can be calculated by weighting the outdoor daily average temperatures of the previous seven days, specifically using the following calculation formula:

[0066] Tma n =(Tout n-1 +0.8Tout n-2 +0.6Tout n-3 +0.5Toutn-4 +0.4Tout n-5 +0.3Tout n-6 +0.2

[0067] Tout n-7 ) / 3.8;

[0068] Among them, Tma n Tout represents the outdoor sliding average temperature on day n, and Tout represents the daily average temperature.

[0069] It should be noted that the weighting coefficients for the above items can be determined through extensive statistical testing.

[0070] Step 103: Determine the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic.

[0071] For example, in a non-limiting embodiment, the automatic operation mode logic may be configured to include the following four items:

[0072] T auto (24,1)——The combined prediction of the current set temperature based on the historical set temperature;

[0073] T autowork (24,1)——Independent prediction of the current set temperature based on historical weekday set temperatures;

[0074] T autorest (24,1)——Independent prediction of the current set temperature based on the historical rest day set temperature;

[0075] T week (24,7)——Independent predictions of the current set temperature for each specific day of the week in history.

[0076] Where 24 represents 24 hours in a day, and 1 and 7 represent the interval granularity. 1 means an interval of 1 hour, for example, 8:30 pm belongs to T(21), and 7 means an interval of 7 days.

[0077] It should be noted that, in practical applications, the interval granularity can be set as needed, and this embodiment of the invention does not limit it.

[0078] The indoor temperature (i.e., target temperature) setting needs to be based on the outdoor sliding average temperature (Tma) at the time the air conditioner is powered on. int The calculation involves using a sliding temperature to determine a target temperature reference table, which roughly corresponds to winter, transitional season, and summer from top to bottom.

[0079] Specifically, four tables can be generated based on the sliding temperature: auto, work, rest, and week. Then, the target temperature can be calculated by weighting these tables at the corresponding time.

[0080] For example, the target temperature T for each time period of the day. auto =ones(24,1) is calculated as follows:

[0081] If Tma int If ≤13, then:

[0082] T auto =24T auto ;

[0083] T auto (1:7) = 19.6;

[0084] T auto (22:24) = 19.6;

[0085] If 13 <Tma int If <20, then:

[0086] T auto =(0.57Tma int +16.4)*T auto ;

[0087] T auto (1:7) = 23.5;

[0088] T auto (22:24) = 23.5;

[0089] If Tma int If ≥20, then:

[0090] T auto =28T auto ;

[0091] T auto (1:7) = 27.4;

[0092] T auto (22:24) = 27.4;

[0093] T autowork =T auto

[0094] T autorest =T auto

[0095] T week (24,7)=[T auto ,T auto ,T auto ,Tauto ,T auto ,T auto ,T auto ]

[0096] The specific process for determining the target temperature for each time period based on the set automatic operation mode logic is as follows: set the variable parameters corresponding to each logic item in the automatic operation mode logic; determine the relevant variable parameters for the day, and generate a target temperature calculation model based on sliding temperature according to the logic items corresponding to the variable parameters; calculate the target temperature for each time period according to the target temperature calculation model based on sliding temperature.

[0097] For example, after the air conditioner enters automatic operation mode, it calls the pre-stored automatic operation variable parameters based on the current Beijing time and the type of day (weekday or weekend). In automatic operation mode, the temperature setting for n time periods (intervals of 1 hour) is calculated according to the following formula (the set temperature for the new time period is calculated every hour on the hour):

[0098] First, determine what day of the week it is, whether it's a weekday or a weekend. For example, the variables related to a workday include: T auto T week T autowork The variables related to rest days include: T auto T week T autorest Based on the logical terms corresponding to the variable parameters, a target temperature calculation model based on the sliding temperature is generated, namely:

[0099] If today = workday, then the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i);

[0100] Otherwise, the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i).

[0101] Where a, b, and c are the weighting coefficients of each logical term, for example, they can be set as: a = 0.4, b = 0.4, c = 0.2.

[0102] Furthermore, in a non-limiting embodiment, the target temperature calculation model based on sliding temperature can be modified based on the thermophysiological regulation characteristics of the human body. Specifically, a modification term based on the thermophysiological regulation characteristics of the human body can be added to the aforementioned target temperature calculation model based on sliding temperature. This modification term can be represented by d[Tmatoday-Tmayesterday], where Tmatoday represents the outdoor sliding average temperature of the current day, and Tmayesterday represents the outdoor sliding average temperature of the previous day. The modified target temperature calculation models based on sliding temperature are then:

[0103] T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i)+d[Tmatoday-Tmayesterday];

[0104] T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i)+d[Tmatoday-Tmayesterday];

[0105] Where d is the weighting coefficient of the correction term, which is related to the city where the specific project is located. For example, it is 0.19 for Qinhuangdao and 0.17 for Beijing.

[0106] This correction requires the use of the moving average temperature for calculation, so the system should at least store today's and yesterday's outdoor moving average temperatures.

[0107] Step 104: Generate a temperature control table based on the target temperature for each time period.

[0108] It should be noted that the target temperature refers to the preceding T. set It is dynamic, especially after considering human thermophysiological corrections. However, since the outdoor sliding average temperature of today and yesterday is fixed, and if the aforementioned auto remains unchanged, the 24-hour T... set It can be confirmed.

[0109] Step 105: Control the temperature of the air conditioner according to the temperature control table.

[0110] In other words, the air conditioner's set temperature is automatically adjusted according to the temperature control table.

[0111] The method for improving the intelligence of air conditioners provided in this invention involves the air conditioner entering automatic operation mode after being powered on, determining the outdoor sliding average temperature for the day, determining the target temperature for each time period based on the outdoor sliding average temperature and the set automatic operation mode, generating a temperature control table based on the target temperature for each time period, and controlling the air conditioner temperature according to the temperature control table. This achieves automatic temperature control of the air conditioner without manual intervention. The outdoor sliding average temperature is a weighted value of the previous few days, so its value is constant for 24 hours. Therefore, the change in target temperature at different times of the day is mainly determined by the set values ​​of various tables such as auto and work at different times, thus allowing the target temperature of the air conditioner to change dynamically at different times, making the air conditioner control more intelligent and comfortable.

[0112] Furthermore, in another embodiment of the method of the present invention, the air conditioner's operating mode and operating parameters can be automatically controlled by comprehensively considering the current set temperature of the automatic operation mode, the current outdoor environmental parameters (temperature, humidity, etc.), and user parameters. The operating modes include: cooling / heating mode and / or sleep mode; the operating parameters include: humidity control parameters and underfloor heating control parameters.

[0113] For example, the control logic for cooling and heating modes is set as follows: pattern = function(T, T set The date is determined based on the current ambient temperature T, the set temperature, and the date, as follows:

[0114] If date ∈ (11.15-3.15), then pattern = heating;

[0115] If date ∈ (5.15-9.15), then pattern = cooling;

[0116] In T set -4 <T<T set In the case of +4, if pattern = cooling, then pattern = cooling; if pattern = heating, then pattern = heating.

[0117] In T set When +4 <= T, pattern = cooling;

[0118] In T set When -4>=T, pattern=heating.

[0119] It should be noted that the above control of air conditioner operating modes and parameters is only an example. In actual applications, it is not limited to the above control logic and can be set according to the actual application environment.

[0120] It should be noted that users can manually adjust the above-mentioned working modes and parameters, and are given the highest priority.

[0121] Accordingly, in another non-limiting embodiment of the method of the present invention, user intervention information regarding the air conditioner's operating mode and parameters, as well as temperature parameters, can also be recorded under the other operating modes. Based on the user's intervention information, the aforementioned automatic operating mode logic is updated.

[0122] It is evident that, even with multiple air conditioning operating modes coexisting, the system can record user intervention information regarding the air conditioning's operating mode, parameters, and temperature parameters in other operating modes. Based on this information, the automatic operating mode logic can be updated, making it more aligned with individual user needs. Consequently, after a period of operation, the automatic operating mode can fully meet the user's requirements without human intervention, or with a very low probability of needing human intervention. This significantly enhances the intelligence of the air conditioner and enables fully intelligent operation.

[0123] Accordingly, embodiments of the present invention also provide a device for improving the intelligence of air conditioners, such as... Figure 2 The diagram shown is a structural schematic of the device.

[0124] The device 200 that enhances the intelligence of the air conditioner includes the following modules:

[0125] The operation mode selection module 201 is used to enter the automatic operation mode after the air conditioner is powered on;

[0126] The sliding temperature determination module 202 is used to determine the outdoor sliding average temperature for the day.

[0127] The target temperature determination module 203 is used to determine the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic.

[0128] Temperature control table generation module 204 is used to generate temperature control tables based on the target temperature for each time period.

[0129] The control module 205 is used to control the temperature of the air conditioner according to the temperature control table.

[0130] Specifically, the target temperature determination module 203 may include the following units:

[0131] The parameter setting unit is used to set the variable parameters corresponding to each logic item in the automatic operation mode logic;

[0132] The model generation unit is used to determine the relevant variable parameters for the day and generate a target temperature calculation model based on the sliding temperature according to the logical terms corresponding to the variable parameters.

[0133] The calculation unit calculates the target temperature for each time period according to the target temperature calculation model based on the sliding temperature.

[0134] Furthermore, the target temperature determination module may further include a correction unit, used to correct the target temperature calculation model based on sliding temperature according to the human body's thermophysiological regulation characteristics. Correspondingly, the calculation unit calculates the target temperature for each time period based on the corrected target temperature calculation model based on sliding temperature.

[0135] The device for enhancing the intelligence of air conditioners provided in this invention enters automatic operation mode after the air conditioner is powered on, determines the outdoor sliding average temperature for the day, determines the target temperature for each time period based on the outdoor sliding average temperature and the set automatic operation mode, generates a temperature control table based on the target temperature for each time period, and controls the air conditioner temperature according to the temperature control table. Thus, automatic temperature control of the air conditioner can be achieved without manual intervention. Because the outdoor sliding average temperature for the day is considered when determining the target temperature for each time period, the target temperature of the air conditioner can change with the outdoor temperature at different times, making the air conditioner control more intelligent and comfortable.

[0136] like Figure 3 The diagram shown is another structural schematic of the device for improving the intelligence of air conditioners according to an embodiment of the present invention.

[0137] and Figure 2 Unlike the illustrated embodiment, in this embodiment, the device 300 for enhancing the intelligence of the air conditioner further includes:

[0138] The parameter acquisition module 301 is used to acquire environmental parameters and user parameters;

[0139] The working mode and parameter determination module 302 is used to determine the air conditioner's working mode and working parameters based on the outdoor sliding average temperature of the day, the environmental parameters, and the user parameters. The working mode includes: cooling and heating mode, and / or sleep mode; the working parameters include: humidity control parameters, fresh air control parameters, and floor heating control parameters.

[0140] Accordingly, the control module 205 is also used to control the air conditioner according to the determined working mode and working parameters.

[0141] In another non-limiting embodiment, the air conditioner operation mode includes the above-mentioned automatic operation mode, and may also include one or more other operation modes, such as manual operation mode, intelligent control operation mode, etc.

[0142] In this case, the device for enhancing the intelligence of the air conditioner may further include: an information recording module and a logic update module. Wherein:

[0143] The information recording module is used to record user intervention information regarding the air conditioner's operating mode, operating parameters, and temperature parameters under the other operating modes.

[0144] The logic update module is used to update the automatic operation mode logic based on the intervention information.

[0145] By updating the automatic operation mode logic using recorded human intervention information, the automatic operation mode logic can be better matched to the individual needs of users. After running for a period of time, the automatic operation mode alone can fully meet the user's needs without human intervention, or with a very low probability of needing human intervention, greatly improving the intelligence of the air conditioner and achieving fully intelligent operation.

[0146] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0147] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. Furthermore, the system embodiments described above are merely illustrative. The modules and units described as separate components may or may not be physically separate; that is, they may be located on a single network unit or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0148] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means.

[0149] An integrated unit implemented as a software functional unit can be stored in a computer-readable storage medium. This software functional unit, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in the various embodiments of this application.

[0150] In various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0151] The embodiments of the present invention have been described in detail above. Specific implementation methods have been used to illustrate the present invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and apparatus of the present invention, and are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention, and the content of this specification should not be construed as a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for improving the intelligence of an air conditioner, characterized in that, The method includes: The air conditioner enters automatic operation mode after being powered on. Determine the outdoor sliding average temperature for the day; The target temperature for each time period is determined based on the outdoor sliding average temperature of the day and the set automatic operation mode logic. A temperature control table is generated based on the target temperature for each time period; The air conditioner temperature is controlled according to the temperature control table. The step of determining the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic includes: Set the variable parameters corresponding to each logic item in the automatic operation mode logic; Determine the relevant variable parameters for the day, and generate a target temperature calculation model based on the sliding temperature according to the logical terms corresponding to the variable parameters. Calculate the target temperature for each time period based on the target temperature calculation model based on the sliding temperature: If today = workday, then the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i); Otherwise, the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i); Where a, b, and c are the weighting coefficients of each logical term, and T auto T is a comprehensive prediction of the current set temperature based on historical set temperatures. autowork T is an independent prediction of the current set temperature based on historical workday set temperatures. autorest Independent prediction of the current set temperature based on historical rest day temperature, T week For each specific day of the week in history, the independent predicted value for the current set temperature is given, where n is the time period and i is the interval granularity. The target temperature calculation model based on sliding temperature is modified based on the thermophysiological regulation characteristics of the human body. The target temperature for each time period is calculated based on the modified target temperature calculation model based on sliding temperature. The two target temperature calculation models based on sliding temperature are revised as follows: T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i)+d[Tmatoday- [Tmayesterday] T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i)+d[Tmatoday- [Tmayesterday] Where d is the weighting coefficient of the correction term, which is related to the city where the specific project is located. d[Tmatoday-Tmayesterday] is a correction term based on the human body's thermophysiological regulation characteristics. Tmatoday represents the outdoor sliding average temperature of the day, and Tmayesterday represents the outdoor sliding average temperature of the previous day.

2. The method according to claim 1, characterized in that, The determination of the outdoor sliding average temperature for the day includes: The outdoor daily average temperature for a given number of historical days is weighted and calculated to obtain the outdoor moving average temperature for that day.

3. The method according to claim 2, characterized in that, The historical setting period is the previous 7 days.

4. The method according to claim 1, characterized in that, The automatic operation mode logic includes: comprehensive prediction of the current set temperature based on historical set temperatures, independent prediction of the current set temperature based on historical weekday set temperatures, independent prediction of the current set temperature based on historical rest day set temperatures, and independent prediction of the current set temperature based on specific days of the week based on historical set temperatures.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Obtain current environmental parameters and user parameters, wherein the environmental parameters include: ambient temperature and / or humidity; Based on the current set temperature in automatic operation mode, the current environmental parameters, and user parameters, the air conditioner's operating mode and operating parameters are determined. The operating modes include: cooling / heating mode and / or sleep mode; the operating parameters include: humidity control parameters, fresh air control parameters, and underfloor heating control parameters. The air conditioner is controlled according to the determined working mode and parameters.

6. The method according to claim 5, characterized in that, The air conditioner operating modes include: the automatic operating mode, and also include one or more other operating modes; The method further includes: Record user intervention information regarding air conditioner operating mode and parameters, as well as temperature parameters, under the other operating modes; The automatic operation mode logic is updated based on the intervention information.

7. A device for enhancing the intelligence of an air conditioner, characterized in that, The device includes: The operating mode selection module is used to enter the automatic operation mode after the air conditioner is powered on; The sliding temperature determination module is used to determine the outdoor sliding average temperature for the day. The target temperature determination module is used to determine the target temperature for each time period based on the outdoor sliding average temperature of the day and the set automatic operation mode logic. The temperature control table generation module is used to generate temperature control tables based on the target temperature for each time period. The control module is used to control the temperature of the air conditioner according to the temperature control table; The target temperature determination module includes: The parameter setting unit is used to set the variable parameters corresponding to each logic item in the automatic operation mode logic; The model generation unit is used to determine the relevant variable parameters for the day, and generate a target temperature calculation model based on the sliding temperature according to the logical terms corresponding to the variable parameters. If today = workday, then the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i); Otherwise, the target temperature calculation model based on the sliding temperature is: T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i); Where a, b, and c are the weighting coefficients of each logical term, and T auto T is a comprehensive prediction of the current set temperature based on historical set temperatures. autowork T is an independent prediction of the current set temperature based on historical workday set temperatures. autorest Independent prediction of the current set temperature based on historical rest day temperature, T week For each specific day of the week in history, the independent predicted value for the current set temperature is given, where n is the time period and i is the interval granularity. The calculation unit calculates the target temperature for each time period according to the target temperature calculation model based on the sliding temperature. The correction unit is used to correct the target temperature calculation model based on sliding temperature based on the thermophysiological regulation characteristics of the human body; the calculation unit calculates the target temperature for each time period according to the corrected target temperature calculation model based on sliding temperature, and the two target temperature calculation models based on sliding temperature are corrected as follows: T set =a*T auto (n)+b*T autowork (n)+c*T week (n,i)+d[Tmatoday- [Tmayesterday] T set =a*T auto (n)+b*T autorest (n)+c*T week (n,i)+d[Tmatoday- [Tmayesterday] Where d is the weighting coefficient of the correction term, which is related to the city where the specific project is located. d[Tmatoday-Tmayesterday] is a correction term based on the human body's thermophysiological regulation characteristics. Tmatoday represents the outdoor sliding average temperature of the day, and Tmayesterday represents the outdoor sliding average temperature of the previous day.

8. The apparatus according to claim 7, characterized in that, The device further includes: The parameter acquisition module is used to acquire environmental parameters and user parameters; The working mode and parameter determination module is used to determine the air conditioner's working mode and working parameters based on the outdoor sliding average temperature of the day, the environmental parameters, and the user parameters. The working mode includes: cooling and heating mode, and / or sleep mode; the working parameters include: humidity control parameters, fresh air control parameters, and floor heating control parameters. The control module is also used to control the air conditioner according to the determined working mode and working parameters.

9. The apparatus according to claim 8, characterized in that, The air conditioner operating modes include: the automatic operating mode, and also include one or more other operating modes; The device further includes: The information recording module is used to record user intervention information regarding the air conditioner's operating mode, operating parameters, and temperature parameters under the other operating modes. The logic update module is used to update the automatic operation mode logic based on the intervention information.

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