Control method and device of air conditioner, air conditioner, medium and product

Abstract

This disclosure relates to a control method, apparatus, air conditioner, medium, and product for an air conditioner. The method includes: in response to the air conditioner being in cooling mode or dehumidification mode, acquiring operating parameters and / or environmental parameters of the air conditioner; processing the operating parameters and / or environmental parameters of the air conditioner based on a humidity model, and outputting a humidity prediction value; and displaying the humidity prediction value on a target interface. Based on the method provided in this disclosure, the accuracy of humidity prediction for air conditioners can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of household air conditioning, and in particular to air conditioning control methods, devices, air conditioners, media and products. Background Technology

[0002] In the field of home air conditioning, air conditioners not only have the function of temperature regulation, but also need to take into account humidity control to improve user comfort.

[0003] Currently, the relative humidity of indoor air is mainly measured by humidity sensors, and the measured humidity is displayed on the terminal. Although relative humidity can be obtained, the cost is high, and if the humidity sensor is damaged, the humidity display will be inaccurate, affecting the user experience. Summary of the Invention

[0004] To overcome the problems existing in the related technologies, this disclosure provides a control method, device, air conditioner, medium and product for an air conditioner.

[0005] According to a first aspect of the present disclosure, an air conditioner control method is provided, comprising:

[0006] In response to the air conditioner being in cooling or dehumidification mode, collect the air conditioner's operating parameters and / or environmental parameters;

[0007] The humidity model is used to process the operating parameters and / or environmental parameters of the air conditioner and output the humidity prediction value.

[0008] Display the humidity forecast on the target interface.

[0009] The beneficial effects of this embodiment are as follows: it can directly predict the humidity of the air conditioner by processing data from multiple sources. Among the multiple data sources, the operating parameters and predicted air volume of the air conditioner can reflect the actual operating status of the air conditioner. At the same time, combined with environmental data, it can improve the accuracy of humidity prediction. It also effectively avoids the problem of inaccurate humidity display caused by the damage of the humidity sensor in models that only set up a humidity sensor to obtain humidity. In addition, displaying the humidity prediction value can improve the diversity and flexibility of user interaction.

[0010] In one embodiment of this disclosure, in response to the air conditioner being in cooling mode or dehumidification mode, collecting the air conditioner's operating parameters and / or environmental parameters further includes:

[0011] When the air conditioner has no humidity sensor or the humidity sensor is damaged, the system collects the air conditioner's operating parameters and / or environmental parameters in response to the air conditioner being in cooling mode or dehumidification mode.

[0012] The beneficial effects of this embodiment are: it can predict the humidity of the air conditioner directly by processing data from multiple sources without relying on a physical humidity sensor. At the same time, it effectively avoids the problem of inaccurate humidity display caused by the damage of the humidity sensor in models that only have a humidity sensor to obtain humidity. In addition, it improves the flexibility of air conditioner humidity prediction.

[0013] In one embodiment of this disclosure, the operating parameters of the air conditioner include one or more of the following: indoor fan speed, outdoor fan speed, indoor fan current, outdoor fan current, compressor operating frequency, expansion valve opening, exhaust temperature, inner pipe temperature and outer pipe temperature, indoor fan damper and outdoor fan input power;

[0014] Environmental parameters include one or more of the following: inner ring temperature, outer ring temperature, outer ring humidity, air pressure, outer air density, outer air specific heat at constant pressure, and inner air density.

[0015] The beneficial effect of this embodiment is that by using various operating parameters and environmental parameters of the air conditioner, the actual operating status of the air conditioner can be reflected in all aspects, thereby improving the accuracy of humidity prediction.

[0016] In one embodiment of this disclosure, the operating parameters and / or environmental parameters of the air conditioner are processed based on a humidity model to output a predicted humidity value, including:

[0017] The operating parameters and / or environmental parameters of the air conditioner are processed based on physical models, numerical models, fitting models or mapping models to output humidity prediction values.

[0018] The beneficial effects of this embodiment are: humidity can be obtained in multiple ways, which improves the flexibility and diversity of humidity prediction.

[0019] In one embodiment of this disclosure, the operating parameters of the air conditioner processed by the physical model include: outdoor fan speed, outdoor fan current, outdoor pipe temperature, inner pipe temperature, and outdoor fan input power; the environmental parameters processed by the physical model include: outer ring temperature, inner ring temperature, outer air density, outer air specific heat at constant pressure, and inner air density.

[0020] The beneficial effects of this embodiment are as follows: by processing various operating and environmental parameters of the air conditioner, the physical model can comprehensively reflect the actual operating conditions of the air conditioner, thereby improving the accuracy of humidity prediction.

[0021] In one embodiment of this disclosure, the operating parameters and / or environmental parameters of the air conditioner are processed based on a physical model to output a humidity prediction value, including:

[0022] The air outlet temperature of the air conditioner is corrected based on the air conditioner's operating parameters and environmental parameters to obtain the corrected outer air outlet temperature and the corrected inner air outlet temperature.

[0023] The heat exchange capacity of the outdoor unit is determined based on the corrected external air outlet temperature, the air conditioner's operating parameters, and environmental parameters.

[0024] The air conditioner's internal air outlet status data is determined based on the corrected internal air outlet temperature, where the air conditioner's internal air outlet status data includes the air outlet enthalpy value.

[0025] The return air enthalpy of the air conditioner is determined based on environmental parameters, the heat exchange of the outdoor unit, and the outlet air enthalpy.

[0026] The moisture content of the return air is determined based on the enthalpy of the return air and the temperature of the inner ring.

[0027] The first humidity data is obtained based on the return air moisture content;

[0028] Use the first humidity data as the humidity prediction value.

[0029] The beneficial effects of this embodiment are as follows: by processing the operating parameters and / or environmental parameters of the air conditioner based on the physical correspondence involved in the physical model, it can ensure that the obtained first humidity data conforms to the actual situation and improve the accuracy of the first humidity data.

[0030] In one embodiment of this disclosure, the air outlet temperature of the air conditioner is corrected based on the air conditioner's operating parameters and environmental parameters to obtain corrected outer air outlet temperature and corrected inner air outlet temperature, including:

[0031] Using a preset first physical relationship, the outer pipe temperature, outer ring temperature, and first fitting parameters are processed to obtain the corrected outer outlet air temperature. The first physical relationship is:

[0032]

[0033] in, The outside air outlet temperature, This refers to the temperature of the outer tube. The outer ring temperature, These are the first fitted parameters;

[0034] The inner pipe temperature, inner ring temperature, and second fitting parameters are processed using a preset second physical relationship to obtain the corrected inner outlet air temperature. The second physical relationship is as follows:

[0035]

[0036] in, The temperature of the air outlet on the inside. This refers to the temperature of the inner tube. The inner ring temperature, is the second fitting parameter.

[0037] The beneficial effect of this embodiment is that by fitting parameters to correct the inner and outer air outlet temperatures, the accuracy of subsequent humidity prediction can be improved.

[0038] In one embodiment of this disclosure, determining the heat exchange capacity of the outdoor unit based on the corrected external air outlet temperature, air conditioner operating parameters, and environmental parameters includes:

[0039] Determine the outdoor air volume;

[0040] Based on the preset energy conservation equation, the corrected external outlet air temperature, external fan input power, external air density, outdoor air volume, external ring temperature, and external air specific heat at constant pressure are processed to obtain the heat exchange capacity of the outdoor unit. The energy conservation equation is as follows:

[0041]

[0042] in, For heat exchange of the outdoor unit, The density of the air on the outside. This refers to the outdoor airflow. The specific heat at constant pressure of the outer air. The outside air outlet temperature, This refers to the outer ring temperature.

[0043] The beneficial effect of this embodiment is that by determining the outdoor air volume and combining it with the energy conservation equation, the heat exchange of the outdoor unit that conforms to the actual operation of the air conditioner can be obtained, which can improve the accuracy of subsequent humidity prediction.

[0044] In one embodiment of this disclosure, determining the air conditioner's inner outlet air status data based on the corrected inner outlet air temperature includes:

[0045] The corrected inner outlet air temperature is processed based on the preset third physical relation to obtain the corresponding saturated water vapor pressure inside the air conditioner. The third physical relation characterizes the correspondence between the inner outlet air temperature and the saturated water vapor pressure.

[0046] The product of the saturated water vapor pressure and the preset humidity fitting parameters is determined as the water vapor partial pressure inside the air conditioner.

[0047] The water vapor partial pressure inside the air conditioner is processed based on the preset fourth physical relation to obtain the corresponding outlet air humidity. The fourth physical relation characterizes the correspondence between water vapor partial pressure and outlet air humidity.

[0048] The corrected inner outlet air temperature and outlet air humidity are processed based on the preset fifth physical relation to obtain the outlet air enthalpy value. The fifth physical relation characterizes the correspondence between the inner outlet air temperature, outlet air humidity and outlet air enthalpy value.

[0049] The beneficial effect of this embodiment is that, based on the physical correspondence between the parameters in the third, fourth and fifth physical relations, the outlet enthalpy value that conforms to the actual operation of the air conditioner can be obtained, which can improve the accuracy of subsequent humidity prediction.

[0050] In one embodiment of this disclosure, determining the return air enthalpy of the air conditioner based on environmental parameters, the heat exchange capacity of the outdoor unit, and the outlet air enthalpy includes:

[0051] Determine the indoor air volume;

[0052] The mass flow rate of the inner air is determined based on the indoor side air volume and the inner air density.

[0053] Determine the product of the mass flow rate of the inner air and the heat exchange of the outdoor unit, and sum the product with the outlet air enthalpy to obtain the return air enthalpy.

[0054] The beneficial effects of this embodiment are as follows: based on the physical correspondence between the heat exchange of the outdoor unit, the mass flow rate of the inner air, the outlet enthalpy and the return air enthalpy, a return air enthalpy that conforms to the actual operation of the air conditioner can be obtained, which can improve the accuracy of subsequent humidity prediction.

[0055] In one embodiment of this disclosure, determining the moisture content of the return air based on the return air enthalpy and the inner ring temperature includes:

[0056] The return air enthalpy and inner ring temperature are processed based on the preset sixth physical relation to obtain the return air moisture content. The sixth physical relation characterizes the correspondence between the return air enthalpy, inner ring temperature and return air moisture content.

[0057] The beneficial effects of this embodiment are: based on the physical correspondence between the return air enthalpy and the inner ring temperature, the return air humidity content that conforms to the actual operation of the air conditioner can be obtained, which can improve the accuracy of subsequent humidity prediction.

[0058] In one embodiment of this disclosure, first humidity data is obtained based on the return air moisture content, including:

[0059] The return air humidity is processed based on the preset seventh physical relation to obtain the corresponding water vapor partial pressure. The seventh physical relation characterizes the correspondence between the return air humidity and the water vapor partial pressure.

[0060] The saturated vapor pressure at the inner ring temperature is determined based on the preset eighth physical relation.

[0061] The ratio of water vapor partial pressure to saturated water vapor pressure is determined as the first humidity data.

[0062] The beneficial effects of this embodiment are as follows: Based on the seventh and eighth physical relations, the first humidity data that conforms to the actual operation of the air conditioner can be obtained based on the physical correspondence between the return air humidity, inner ring temperature, water vapor partial pressure, saturated water vapor pressure and humidity data, which can improve the accuracy of subsequent humidity prediction.

[0063] In one embodiment of this disclosure, the operating parameters of the air conditioner processed by the numerical model include: indoor fan speed, indoor fan current, compressor operating frequency, exhaust temperature, outer pipe temperature and inner pipe temperature; the environmental parameters processed by the numerical model include: outer ring temperature and inner ring temperature.

[0064] The beneficial effects of this embodiment are as follows: by processing various operating and environmental parameters of the air conditioner, the numerical model can comprehensively reflect the actual operating conditions of the air conditioner, thereby improving the accuracy of humidity prediction.

[0065] In one embodiment of this disclosure, the operating parameters and / or environmental parameters of the air conditioner are processed based on a numerical model to output a humidity prediction value, including:

[0066] The indoor fan speed and indoor fan current are processed to obtain the indoor air volume;

[0067] The outer ring temperature, inner pipe temperature, inner ring temperature, indoor air volume, compressor operating frequency, exhaust temperature and outer pipe temperature are processed to obtain the corresponding latent heat.

[0068] The temperature of the inner tube, the temperature of the inner ring, the latent heat, and the air volume on the indoor side are processed to obtain the corresponding dry bulb temperature of the indoor unit outlet air.

[0069] The temperature of the inner tube, the temperature of the inner ring, and the dry bulb temperature of the indoor unit outlet are processed to obtain the corresponding wet bulb temperature of the inner outlet.

[0070] The dry bulb temperature of the indoor unit's outlet air and the wet bulb temperature of the inner outlet air are processed to obtain the corresponding outlet air humidity content;

[0071] The corresponding return air humidity is obtained based on the outlet air humidity.

[0072] The return air humidity and inner ring temperature are processed to obtain a second humidity data;

[0073] Use the second humidity data as the humidity prediction value.

[0074] The beneficial effect of this embodiment is that by performing calculations on the operating parameters and / or environmental parameters of the air conditioner based on a numerical model, the accuracy of the obtained second humidity data value can be guaranteed.

[0075] In one embodiment of this disclosure, the operating parameters and / or environmental parameters of the air conditioner are processed based on a fitting model to output a humidity prediction value, including:

[0076] Determine the predicted air volume value corresponding to the air conditioner. Based on the fitting model, perform fitting processing on the predicted air volume value, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or environmental parameters to obtain the third humidity data. The first humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the physical model. The second humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the numerical model.

[0077] Alternatively, the fourth humidity data can be obtained by fitting the outer ambient temperature, outer ambient humidity, and air pressure based on the fitting model;

[0078] Alternatively, the operating parameters of the air conditioner can be fitted using a fitting model to obtain the fifth humidity data.

[0079] Use the third, fourth, or fifth humidity data as the humidity prediction value.

[0080] The beneficial effect of this embodiment is that by fitting the operating parameters and / or environmental parameters of the air conditioner in different ways based on the fitting model, the accuracy of humidity prediction can be improved.

[0081] In one embodiment of this disclosure, a third humidity data is obtained by fitting the predicted air volume, first humidity data, second humidity data, air conditioner operating parameters, and / or environmental parameters based on a fitting model, including:

[0082] The predicted air volume, the first humidity data, the second humidity data, the operating parameters of the air conditioner, and / or the environmental parameters are normalized.

[0083] The normalized predicted air volume, the first humidity data, the second humidity data, the air conditioner's operating parameters and / or environmental parameters are input into the humidity prediction model. The humidity prediction model is a neural network model based on the Transformer architecture, used to predict humidity values.

[0084] The input data is processed using a multi-head attention mechanism of the humidity prediction model to obtain the processing results corresponding to each attention head.

[0085] The processing results corresponding to each attention point are concatenated to obtain the corresponding concatenation result;

[0086] The splicing results are processed using a preset normalization formula to obtain the third humidity data.

[0087] The beneficial effects of this embodiment are as follows: by normalizing the input data, the standardization and stability of the input data can be improved, thereby improving the prediction efficiency and accuracy of the humidity prediction model. Normalizing the splicing results can improve the standardization of the splicing results, further improving the accuracy of humidity prediction.

[0088] In one embodiment of this disclosure, before processing the input data using the multi-head attention mechanism of the humidity prediction model, the method further includes:

[0089] The gating score corresponding to each attention head is determined by a sparse gating mechanism;

[0090] Based on the gating score corresponding to each attention head, the attention heads to be activated are determined;

[0091] Activate the attention target to be activated.

[0092] The beneficial effects of this embodiment are as follows: by determining the attention heads to be activated based on the gating scores of each attention head, it can be ensured that the activated attention heads can accurately analyze the input data and ensure the accuracy of humidity prediction.

[0093] In one embodiment of this disclosure, a multi-head attention mechanism of a humidity prediction model is used to process the input data to obtain the processing results corresponding to each attention head, including:

[0094] For each activated attention head, the query vector, key vector, and value vector corresponding to the attention head are determined by the input data. The query vector, key vector, and value vector are then normalized to obtain the processing result corresponding to the attention head.

[0095] For each attention head that is not activated, set the processing result corresponding to that attention head to zero.

[0096] The beneficial effects of this embodiment are: by activating the attention head to retain the correlation of key features and setting the processing results of inactive ones to zero, it ensures that the input data is fully extracted while avoiding interference from inactive attention heads on the splicing results.

[0097] In one embodiment of this disclosure, the splicing result is processed using a preset normalization formula to obtain third humidity data, including:

[0098] For each activated attention head, the gating weight corresponding to the attention head is determined by the preset gating weight relationship and the gating score corresponding to the attention head;

[0099] For each inactive attention head, reset the gating weight corresponding to the attention head to zero;

[0100] Based on the gating weights corresponding to each attention point, the splicing results are processed by a preset normalization formula to obtain the third humidity data.

[0101] The beneficial effect of this embodiment is that by resetting the gating weight of the inactive attention head to zero, the interference of the inactive attention head on humidity prediction can be avoided, thereby improving the accuracy of humidity prediction.

[0102] In one embodiment of this disclosure, the operating parameters and / or environmental parameters of the air conditioner are processed based on a mapping model to output a humidity prediction value, including:

[0103] Establish a mapping relationship between the operating parameters and / or environmental parameters of the air conditioner and humidity, and form a mapping table or mapping curve;

[0104] Collect the operating parameters of the air conditioner and environmental parameters, input them into a mapping table or mapping curve for table lookup or interpolation processing, and output the corresponding humidity prediction value.

[0105] The beneficial effect of this embodiment is that it can determine the corresponding humidity prediction value based on the direct mapping relationship between operating parameters and / or environmental parameters and humidity, thereby improving the accuracy of humidity prediction.

[0106] In one embodiment of this disclosure, displaying the humidity prediction value on the target interface includes:

[0107] The humidity prediction value of the air conditioner is dynamically displayed on the air conditioner's display screen.

[0108] Alternatively, the humidity prediction value of the air conditioner can be dynamically displayed through preset software on the user terminal.

[0109] The beneficial effect of this embodiment is that by dynamically displaying real-time data of air conditioner humidity in different ways, the diversity and flexibility of user interaction can be improved.

[0110] In one embodiment of this disclosure, the humidity model is stored in the local memory of the air conditioner or in a cloud server.

[0111] The beneficial effects of this embodiment are: humidity can be predicted based on a humidity model through the collaboration of a local processor or a cloud server, thereby improving the diversity and convenience of humidity prediction.

[0112] In one embodiment of this disclosure, it further includes:

[0113] Check if the air conditioner's humidity display function is enabled;

[0114] If it is determined that the humidity display function of the air conditioner is not turned on, the target interface controlling the air conditioner will not display the humidity prediction value.

[0115] The beneficial effect of this embodiment is that when the air conditioner does not have a display function, the control target interface does not display the humidity prediction value, so as to save the power of the air conditioner.

[0116] According to a second aspect of the present disclosure, an air conditioner control device is provided. The air conditioner control device is used to process the air conditioner control method as described in any of the first aspects above, including:

[0117] The response module is used to collect the operating parameters of the air conditioner and / or environmental parameters in response to whether the air conditioner is in cooling mode or dehumidification mode.

[0118] The processing module is used to process the operating parameters and / or environmental parameters of the air conditioner based on the humidity model and output the humidity prediction value.

[0119] The processing module is also used to display the humidity prediction value on the target interface.

[0120] According to a third aspect of the present disclosure, an air conditioner is provided, comprising: a memory and a display screen;

[0121] The memory stores the instructions that the computer executes;

[0122] The computer executes the instructions stored in the memory to implement the air conditioner control method as described in any of the first aspects above;

[0123] The display screen is used to dynamically show the humidity prediction value of the air conditioner.

[0124] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, which stores computer-executable instructions that, when executed, are used to implement the air conditioning control method as described in any of the first aspects above.

[0125] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed, implements an air conditioning control method as described in any of the first aspects above.

[0126] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: The air conditioning control method, device, air conditioner, medium and product provided by this disclosure can predict the humidity of the air conditioner in real time by collecting the operating parameters and environmental data of the air conditioner during the operation of the air conditioner. The operating parameters and environmental data of the air conditioner can reflect the actual operating status of the fan, which can improve the accuracy of humidity prediction. At the same time, displaying the humidity prediction value can improve the diversity and flexibility of interaction with the user.

[0127] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0128] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0129] Figure 1 This is an example of a scenario covered by this disclosure;

[0130] Figure 2 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 1 ;

[0131] Figure 3 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 2 ;

[0132] Figure 4 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 3 ;

[0133] Figure 5 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 4 ;

[0134] Figure 6 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 5 ;

[0135] Figure 7 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 6 ;

[0136] Figure 8 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 7 ;

[0137] Figure 9 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 8 ;

[0138] Figure 10 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 9 ;

[0139] Figure 11 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 ;

[0140] Figure 12 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10one;

[0141] Figure 13 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 two;

[0142] Figure 14 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 three;

[0143] Figure 15 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Four;

[0144] Figure 16 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 five;

[0145] Figure 17 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 six;

[0146] Figure 18 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 seven;

[0147] Figure 19 This is a structural diagram of an air conditioner control device according to some embodiments of the present disclosure;

[0148] Figure 20 This is a schematic diagram of the structure of the air conditioner disclosed herein. Detailed Implementation

[0149] Some embodiments of this disclosure will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. Various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but can be changed as will become apparent upon understanding this disclosure, except for operations that must be performed in a particular order. Furthermore, for clarity and brevity, descriptions of features known in the art may be omitted.

[0150] First, the application scenarios of this disclosure will be explained. This disclosure pertains to the field of household air conditioning. In this field, air conditioners not only regulate temperature but also control humidity to improve user comfort. For example, in dehumidification mode, users expect the air conditioner to monitor and adjust indoor humidity in real time to avoid stuffiness caused by excessive humidity or dryness caused by excessively low humidity. However, traditional air conditioners typically rely on physical humidity sensors to collect data, but these sensors are costly, susceptible to environmental interference (such as dust, temperature and humidity fluctuations), and require regular calibration or replacement, increasing the user's maintenance burden. Furthermore, some low-end air conditioners lack humidity sensors due to cost constraints, resulting in inaccurate humidity control. If the air conditioner cannot dynamically provide humidity information during use, it not only affects the dehumidification effect but may also cause equipment malfunction due to abnormal humidity (such as the risk of condensation).

[0151] Figure 1 This is an example schematic diagram illustrating a scenario covered by this disclosure. To address the aforementioned problems, this disclosure provides a control method, apparatus, air conditioner, medium, and product for an air conditioner. Figure 1 As shown, this disclosure obtains a predicted humidity value by collecting the operating parameters and / or environmental data of the air conditioner and processing them using a humidity model. This predicted humidity value can then be displayed. The air conditioner control method provided by this disclosure does not rely on a physical humidity sensor. It can directly predict the humidity of the air conditioner by processing multiple data sources. Among these data sources, the predicted operating parameters and airflow of the air conditioner reflect its actual operating status. Combined with environmental data, the accuracy of humidity prediction is improved. This effectively avoids the problem of inaccurate humidity display caused by sensor malfunction, which is common in models that only use a humidity sensor. Furthermore, displaying the predicted humidity value enhances the diversity and flexibility of user interaction.

[0152] The present disclosure will now be described with reference to specific embodiments. The embodiments described in the following examples do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0153] Figure 2 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 1 ,like Figure 2 As shown, it includes the following steps.

[0154] S201. In response to the air conditioner being in cooling mode or dehumidification mode, collect the air conditioner's operating parameters and / or environmental parameters.

[0155] Based on scenario examples, the operating parameters and environmental parameters of the air conditioner can be determined according to requirements. For example, the operating parameters of the air conditioner include one or more of the following: indoor fan speed, outdoor fan speed, indoor fan current, outdoor fan current, compressor operating frequency, expansion valve opening, exhaust temperature, indoor pipe temperature and outdoor pipe temperature, indoor fan damper and outdoor fan input power; the environmental parameters include one or more of the following: inner ring temperature, outer ring temperature, outer ring humidity, air pressure, outer air density, outer air specific heat at constant pressure, and inner air density.

[0156] The parameters are as follows: Inner pipe temperature refers to the pipe temperature of the indoor heat exchanger in the air conditioner; outer pipe temperature refers to the pipe temperature of the outdoor heat exchanger; exhaust temperature refers to the compressor exhaust port temperature; inner ring temperature refers to the indoor ambient temperature; and outer ring temperature refers to the outdoor ambient temperature. These parameters can be directly obtained through temperature sensors. The outer ring humidity can be obtained through a humidity sensor. The indoor and outdoor fan currents can be obtained through current sensors, and the air pressure can be obtained through an atmospheric pressure sensor. The indoor and outdoor fan speeds can be obtained through Hall effect sensors. The indoor fan damper is set by the user. The compressor operating frequency and expansion valve opening can be set by the processor in the air conditioner. The outdoor fan input power can be calculated by first collecting the outdoor fan voltage and current. The outer air density can be calculated by first collecting the outdoor ambient temperature, outdoor air pressure, and outdoor humidity. Similarly, the inner air density can be calculated by first collecting the indoor ambient temperature, indoor air pressure, and indoor humidity. The specific heat of the outer air at constant pressure changes very little with temperature and humidity, and can be obtained directly by looking up a table or by using a fixed preset value.

[0157] Based on the method provided in this example, the actual operating status of the air conditioner can be comprehensively reflected through various operating parameters and environmental parameters, thereby improving the accuracy of humidity prediction.

[0158] In addition, S201 further includes: when the air conditioner has no humidity sensor or the humidity sensor is damaged, in response to the air conditioner being in cooling mode or dehumidification mode, collecting the operating parameters of the air conditioner and / or environmental parameters.

[0159] In the case of a scenario example, if the air conditioner has a humidity sensor and the humidity sensor is working properly, the humidity can be detected directly through the humidity sensor. When the humidity sensor is not working or the air conditioner does not have a humidity sensor, the method provided in this disclosure does not rely on a physical humidity sensor. It can directly predict the humidity by collecting the operating parameters of the air conditioner and / or environmental parameters. At the same time, it effectively avoids the problem of inaccurate humidity display caused by the damage of the humidity sensor in models that only have a humidity sensor to obtain humidity. In addition, it improves the flexibility of air conditioner humidity prediction.

[0160] S202. Process the operating parameters and / or environmental parameters of the air conditioner based on the humidity model, and output the humidity prediction value.

[0161] Based on the scenario examples, the humidity model can be implemented in multiple ways. For example, optionally, S202 includes: processing the air conditioner's operating parameters and / or environmental parameters based on a physical model, numerical model, fitting model, or mapping model to output predicted humidity values.

[0162] The operating parameters and / or environmental parameters of the air conditioner can be processed using physical models, numerical models, fitting models, or mapping models to obtain the corresponding humidity prediction values ​​under different models. Based on the method provided in this example, humidity can be obtained in multiple ways, improving the flexibility and diversity of humidity prediction.

[0163] S203. Display the humidity prediction value on the target interface.

[0164] With the help of scenario examples, during the operation of the air conditioner, the predicted humidity value of the air conditioner is dynamically displayed in real time on the target interface, allowing users to understand the humidity status of the air conditioner in a timely manner.

[0165] Optional, Figure 3 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 2 ,like Figure 3 As shown, S203 includes:

[0166] S301. The predicted humidity value of the air conditioner is dynamically displayed on the air conditioner's display screen.

[0167] Based on the scenario example, the target interface can be the air conditioner's display screen, and the humidity prediction value can be displayed through the air conditioner's built-in display screen.

[0168] S302, or dynamically display the humidity prediction value of the air conditioner through preset software on the user terminal.

[0169] Based on the scenario example, humidity can also be displayed wirelessly or via Bluetooth, sending the predicted humidity value of the air conditioner to the user terminal that has established communication with the air conditioner. The real-time humidity data is then displayed through pre-installed software on the terminal. Based on the method provided in this example, dynamically displaying real-time humidity data in different ways can improve the diversity and flexibility of user interaction.

[0170] Based on the method provided in this example, the humidity of the air conditioner can be predicted directly by processing data from multiple sources without relying on a physical humidity sensor. Among the multiple data sources, the air conditioner's operating parameters and predicted airflow can reflect the actual operating status of the air conditioner. At the same time, combined with environmental data, the accuracy of humidity prediction can be improved. This also effectively avoids the problem of inaccurate humidity display caused by the failure of humidity sensors in models that only use humidity sensors to obtain humidity. In addition, displaying the humidity prediction value can improve the diversity and flexibility of user interaction.

[0171] Optionally, the operating parameters of the air conditioner processed by the physical model include: outdoor fan speed, outdoor fan current, outdoor pipe temperature, indoor pipe temperature, and outdoor fan input power; the environmental parameters processed by the physical model include: outer ring temperature, inner ring temperature, outer air density, outer air specific heat at constant pressure, and inner air density.

[0172] For example, a physical model is a mathematical or conceptual model established based on physical laws, conservation principles, and mechanistic relationships to describe real physical processes or natural phenomena. Therefore, the physical model in this example analyzes and processes external fan speed, external fan current, external pipe temperature, internal pipe temperature, external fan input power, outer ring temperature, inner ring temperature, outer air density, outer air specific heat at constant pressure, and inner air density according to physical laws to obtain the corresponding humidity prediction value. Thus, by processing various operating and environmental parameters of the air conditioner, the physical model can comprehensively reflect the actual operating conditions of the air conditioner, thereby improving the accuracy of humidity prediction.

[0173] Figure 4 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 3 ,like Figure 4 As shown, the operating parameters and / or environmental parameters of the air conditioner are processed based on a physical model to output predicted humidity values, including:

[0174] S401. Based on the operating parameters and environmental parameters of the air conditioner, the air outlet temperature of the air conditioner is corrected to obtain the corrected outer air outlet temperature and the corrected inner air outlet temperature.

[0175] In the context of specific scenarios, the outer air outlet temperature refers to the temperature of the air vented outdoors, such as the exhaust temperature of the outdoor unit of an air conditioner. The inner air outlet temperature refers to the temperature of the air vented indoors, and can be used to determine the cooling / heating effect.

[0176] Figure 5 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 4 ,like Figure 5 As shown, the processing procedure of S401 is as follows:

[0177] S501. Using a preset first physical relationship, the outer pipe temperature, outer ring temperature, and first fitting parameters are processed to obtain the corrected outer outlet air temperature. The first physical relationship is:

[0178]

[0179] in, The outside air outlet temperature, This refers to the temperature of the outer tube. The outer ring temperature, These are the first fitted parameters.

[0180] In the scenario example, the outer ring temperature refers to the outdoor ambient temperature, and the outer pipe temperature refers to the temperature of the outdoor heat exchanger coil, which can be obtained by collecting the temperature of the copper pipes inside the outdoor unit. A correction term proportional to the difference between the outer ring temperature and the outer pipe temperature is superimposed on the outer pipe temperature to obtain the corrected outer outlet air temperature. The first fitting parameter determines the correction magnitude; this parameter can be a preset value determined based on actual conditions or obtained by fitting historical operating data.

[0181] S502. Using a preset second physical relationship, the inner pipe temperature, inner ring temperature, and second fitting parameters are processed to obtain the corrected inner outlet air temperature. The second physical relationship is as follows:

[0182]

[0183] in, The temperature of the air outlet on the inside. This refers to the temperature of the inner tube. The inner ring temperature, is the second fitting parameter.

[0184] In the scenario example, the inner ring temperature refers to the indoor ambient temperature, and the inner pipe temperature refers to the temperature of the indoor heat exchanger coil, which can be obtained by collecting the temperature of the copper pipes inside the air conditioner indoor unit. A correction term proportional to the difference between the inner ring temperature and the inner pipe temperature is superimposed on the inner pipe temperature to obtain the corrected inner outlet air temperature. The second fitting parameter determines the correction magnitude; this second fitting parameter can be a preset value determined based on actual conditions or obtained by fitting historical operating data.

[0185] Based on the method provided in this example, the inner and outer air outlet temperatures can be corrected by fitting parameters to improve the accuracy of subsequent humidity predictions.

[0186] S402. Determine the heat exchange capacity of the outdoor unit based on the corrected external air outlet temperature, air conditioner operating parameters, and environmental parameters.

[0187] By combining scenario examples, the heat exchange capacity of the outdoor unit can be directly calculated by combining the corrected external air outlet temperature, operating parameters, and environmental data.

[0188] Accordingly, Figure 6 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 5 ,like Figure 6 As shown, S402 includes:

[0189] S601. Determine the outdoor air volume.

[0190] Using a scenario example, by collecting the outdoor fan current and speed, and applying the calculation logic of the airflow sensor corresponding to the outdoor airflow, the corresponding outdoor airflow is determined. The calculation logic of the airflow sensor corresponding to the outdoor airflow is as follows:

[0191]

[0192] in, This refers to the outdoor airflow. This refers to the external fan speed. For the external fan current, speed correction factor, current correction factor, Correction factor and V 修正 This is the default value.

[0193] S602. Based on the preset energy conservation equation, the corrected external outlet air temperature, external fan input power, external air density, outdoor air volume, external ring temperature, and external air constant pressure specific heat are processed to obtain the heat exchange capacity of the outdoor unit. The energy conservation equation is as follows:

[0194]

[0195] in, For heat exchange of the outdoor unit, The density of the air on the outside. This refers to the outdoor airflow. The specific heat at constant pressure of the outer air. The outside air outlet temperature, The outer ring temperature, This is the input power for the external fan.

[0196] Based on the scenario example and according to the law of conservation of energy, the heat exchange of the outdoor unit ≈ the sensible cooling capacity of the indoor unit + the latent cooling capacity of the indoor unit + the compressor work. The sensible cooling capacity refers to the heat change caused by the cooling of the indoor air, the latent cooling capacity refers to the heat corresponding to the water condensed from the dehumidified air, and the compression work refers to the portion of the electrical energy input to the air conditioning system that is converted into heat energy. Based on this energy conservation equation, the heat exchange of the outdoor unit can be calculated using the collected outside air density, outside air specific heat at constant pressure, and outer ring temperature, as well as the previously determined outdoor airflow and outside outlet air temperature. The outside air density and outside air specific heat at constant pressure can be preset values ​​and can be determined according to actual conditions. For example, the outside air density can be directly taken as 1.18~1.20kg / m³, and the outside air specific heat at constant pressure can be directly taken as 1.005kJ / (kg·℃).

[0197] Based on the method provided in this example, the outdoor air volume can be directly determined by an air volume sensor, and combined with the energy conservation equation, the heat exchange of the outdoor unit that conforms to the actual operation of the air conditioner can be obtained, which can improve the accuracy of subsequent humidity prediction.

[0198] S403. Determine the air conditioner's internal air outlet status data based on the corrected internal air outlet temperature, wherein the air conditioner's internal air outlet status data includes the air outlet enthalpy value.

[0199] In the context of a scenario, the enthalpy of the air outlet refers to the enthalpy of the air delivered after being processed by the evaporator. The enthalpy of the air refers to the total energy per unit mass of dry air.

[0200] Optional, Figure 7 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 6 ,like Figure 7 As shown, S403 includes:

[0201] S701. The corrected inner air outlet temperature is processed based on the preset third physical relationship to obtain the saturated water vapor pressure corresponding to the inner side of the air conditioner. The third physical relationship characterizes the correspondence between the inner air outlet temperature and the saturated water vapor pressure.

[0202] Based on the scenario example, the third physical relation is as follows:

[0203]

[0204] in, This is the corrected inner air outlet temperature. This refers to the saturated vapor pressure corresponding to the corrected inner outlet air temperature.

[0205] S702. The product of the saturated water vapor pressure and the preset humidity fitting parameters is determined as the water vapor partial pressure inside the air conditioner.

[0206] Based on the scenario example, the preset humidity fitting parameter represents the relative humidity of the air outlet on the inside. For example, the humidity fitting parameter can be defined as "c", where 0≤c≤1. The specific value of the humidity fitting parameter can be obtained through actual measurement or experimental fitting.

[0207] S703. The water vapor partial pressure inside the air conditioner is processed based on the preset fourth physical relation to obtain the corresponding outlet air humidity. The fourth physical relation characterizes the correspondence between water vapor partial pressure and outlet air humidity.

[0208] Based on the scenario example, the fourth physical relation is as follows:

[0209]

[0210] in, The moisture content of the exhaust air. The partial pressure of water vapor is obtained from step S702. The pressure is atmospheric pressure, usually standard atmospheric pressure (approximately 101.325 kPa).

[0211] S704. Based on the preset fifth physical relation, the corrected inner outlet air temperature and outlet air moisture content are processed to obtain the outlet air enthalpy value. The fifth physical relation characterizes the correspondence between the inner outlet air temperature, outlet air moisture content and outlet air enthalpy value.

[0212] With a scenario example, the fifth physical relation is as follows:

[0213]

[0214] in, This refers to the enthalpy value of the exhaust air.

[0215] Based on the method provided in this example, the air outlet enthalpy value that conforms to the actual operation of the air conditioner can be obtained based on the physical correspondence between the parameters in the third, fourth and fifth physical relations, which can improve the accuracy of subsequent humidity prediction.

[0216] S404. Based on environmental parameters, the heat exchange capacity of the outdoor unit, and the outlet air enthalpy, determine the return air enthalpy of the air conditioner.

[0217] In the context of a scenario, the enthalpy of return air refers to the enthalpy of the air before the indoor return air enters the evaporator.

[0218] Optional, Figure 8 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 7,like Figure 8 As shown, S404 includes:

[0219] S801. Determine the indoor air volume.

[0220] Using a scenario example, by collecting the indoor fan current and speed, and processing the data according to the calculation logic of the indoor air volume sensor, the corresponding outdoor air volume is determined. The calculation logic of the indoor air volume corresponding to the air volume sensor is as follows:

[0221]

[0222] in, This refers to the indoor air volume. This refers to the internal fan speed. For the internal fan current, speed correction factor, current correction factor, Correction factor and V 修正 This is the default value.

[0223] S802. Determine the mass flow rate of the inner air based on the indoor side air volume and the inner air density.

[0224] Based on the scenario example, the inner air density can be a preset value, which can be determined according to the actual situation. For example, an inner air density of 1.18–1.20 kg / m³ is sufficient. The mass flow rate of the inner air can be calculated using the following formula:

[0225]

[0226] in, The density of the air inside. This refers to the indoor air volume.

[0227] S803. Determine the product of the mass flow rate of the inner air and the heat exchange of the outdoor unit, and sum the product with the outlet enthalpy to obtain the return air enthalpy.

[0228] Based on the scenario example, the return air enthalpy can be obtained using the following formula:

[0229]

[0230] in, This is the enthalpy value of the return air.

[0231] Based on the method provided in this example, the return air enthalpy value that conforms to the actual operation of the air conditioner can be obtained based on the physical correspondence between the heat exchange of the outdoor unit, the mass flow rate of the inner air, the outlet enthalpy value, and the return air enthalpy value, which can improve the accuracy of subsequent humidity prediction.

[0232] S405. Determine the moisture content of the return air based on the enthalpy of the return air and the inner ring temperature.

[0233] In the context of a scenario, the moisture content of return air is the mass of water vapor carried per unit mass of dry air.

[0234] Optionally, the return air enthalpy and inner ring temperature can be processed based on a preset sixth physical relation to obtain the return air moisture content. The sixth physical relation characterizes the correspondence between the return air enthalpy, inner ring temperature and return air moisture content.

[0235] With a scenario example, the sixth physical relation is as follows:

[0236]

[0237] in, This refers to the moisture content of the return air.

[0238] Based on the sixth physical relationship provided in this example, the return air humidity content that conforms to the actual operation of the air conditioner can be obtained based on the physical correspondence between the return air enthalpy and the inner ring temperature, which can improve the accuracy of subsequent humidity prediction.

[0239] S406. Based on the moisture content of the return air, the first humidity data is obtained.

[0240] Based on the scenario example, the first humidity data can be the ratio of water vapor partial pressure to saturated water vapor pressure at the same temperature, which can reflect the humidity level of the air.

[0241] Optional, Figure 9 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 8 ,like Figure 9 As shown, S406 includes:

[0242] S901. The return air moisture content is processed based on the preset seventh physical relation to obtain the corresponding water vapor partial pressure, wherein the seventh physical relation characterizes the correspondence between the return air moisture content and the water vapor partial pressure.

[0243] With a scenario example, the seventh physical relation is as follows:

[0244]

[0245] in, This is the partial pressure of water vapor, representing the actual pressure of water vapor in the air; The pressure is atmospheric pressure, usually standard atmospheric pressure (approximately 101.325 kPa). This refers to the moisture content of the return air.

[0246] S902. Determine the saturated water vapor pressure at the inner ring temperature based on the preset eighth physical relation.

[0247] With a scenario example, the eighth physical relation is as follows:

[0248]

[0249] in, To the inner ring temperature The maximum water vapor pressure that can be contained is the saturated water vapor pressure at the inner ring temperature.

[0250] S903. The ratio of water vapor partial pressure to saturated water vapor pressure is determined as the first humidity data.

[0251] Using a scenario example, the relative humidity is obtained by comparing the partial pressure of water vapor with the saturated vapor pressure, and this is determined as the primary humidity data. The primary humidity data is typically presented as a percentage, ranging from 0 to 1.

[0252] Based on the seventh and eighth physical relationships provided in this example, the first humidity data that conforms to the actual operation of the air conditioner can be obtained based on the physical correspondence between return air moisture content, inner ring temperature, water vapor partial pressure, saturated water vapor pressure and humidity data, which can improve the accuracy of subsequent humidity prediction.

[0253] S407. Use the first humidity data as the humidity prediction value.

[0254] Based on the scenario example, the first humidity data is the result of the physical model predicting the humidity of the air conditioner based on the operating parameters and / or environmental parameters of the air conditioner, and can be used as a humidity prediction value.

[0255] This example processes the air conditioner's operating parameters and environmental data based on the physical correspondences involved in the physical model, ensuring that the obtained initial humidity data matches the actual situation and improving the accuracy of humidity prediction.

[0256] Optionally, the operating parameters of the air conditioner processed by the numerical model include: indoor fan speed, indoor fan current, compressor operating frequency, exhaust temperature, external pipe temperature and internal pipe temperature; the environmental parameters processed by the numerical model include: external ring temperature and internal ring temperature.

[0257] A numerical model refers to a computational model that discretizes and approximates physical models or complex mathematical equations. By processing parameters such as internal fan speed, internal fan current, compressor operating frequency, exhaust temperature, external pipe temperature, internal pipe temperature, outer ring temperature, and inner ring temperature, a numerical model can obtain corresponding humidity prediction values. By processing various operating and environmental parameters of the air conditioner, the numerical model can comprehensively reflect the actual operating conditions of the air conditioner, thereby improving the accuracy of humidity prediction.

[0258] Optional, Figure 10 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 9 ,like Figure 10 As shown, based on a numerical model, the operating parameters and / or environmental parameters of the air conditioner are processed to output predicted humidity values, including:

[0259] Figure 10 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 9 ,like Figure 10 As shown, S204 includes:

[0260] S1001. Process the indoor fan speed and indoor fan current to obtain the indoor air volume.

[0261] In the example scenario, the fan speed and current used to calculate the indoor airflow are the internal fan speed and current. As mentioned above, the internal fan current and speed can be calculated to determine the corresponding outdoor airflow. The calculation logic for the outdoor airflow is as follows:

[0262]

[0263] in, This refers to the indoor air volume. This refers to the internal fan speed. For the internal fan current, speed correction factor, current correction factor, Correction factor and V 修正 This is the default value.

[0264] S1002 processes the outer ring temperature, inner pipe temperature, inner ring temperature, indoor air volume, compressor operating frequency, exhaust temperature, and outer pipe temperature to obtain the corresponding latent heat.

[0265] Based on the scenario example, the calculation logic for latent heat is as follows:

[0266]

[0267] in, Latent heat The outer ring temperature, This refers to the temperature of the inner tube. The inner ring temperature, This refers to the indoor air volume. For compressor operating frequency, The exhaust temperature, For external pipe temperature, outer loop correction factor, inner pipe correction factor, inner loop correction factor, air volume correction factor, frequency correction factor, exhaust correction factor, and external pipe correction factor. Correction factor Upper limit, frequency correction factor and The upper limit correction factor is a preset value, which can be determined according to the actual situation.

[0268] S1003. Process the inner pipe temperature, inner ring temperature, latent heat and indoor air volume to obtain the corresponding indoor unit outlet dry bulb temperature.

[0269] Based on the scenario example, the calculation logic for the dry bulb temperature of the indoor unit's outlet air is as follows:

[0270]

[0271] in, For the indoor unit's outlet dry bulb temperature, latent heat correction factor, air volume correction factor, and The correction factor is a preset value, which can be determined according to the actual situation.

[0272] S1004. Process the inner tube temperature, inner ring temperature and indoor unit outlet dry bulb temperature to obtain the corresponding inner outlet wet bulb temperature.

[0273] Based on the scenario example, the calculation logic for the wet-bulb temperature of the inner outlet air is as follows:

[0274]

[0275] in, The inner outlet wet-bulb temperature, the outlet dry-bulb correction factor, and The correction factor is a preset value, which can be determined according to the actual situation.

[0276] S1005. Process the dry bulb temperature of the indoor unit's outlet air and the wet bulb temperature of the inner outlet air to obtain the corresponding outlet air humidity content.

[0277] Based on the scenario example, the calculation logic for the humidity content of the outlet air is as follows:

[0278]

[0279] in, This refers to the humidity content of the exhaust air.

[0280] S1006. Obtain the corresponding return air humidity based on the outlet air humidity.

[0281] Using a scenario example, the humidity content of the outlet air is converted according to the following formula to obtain the corresponding humidity content of the return air.

[0282]

[0283] in, This refers to the moisture content of the return air.

[0284] S1007. Process the return air humidity and inner ring temperature to obtain the second humidity data.

[0285] Based on the scenario example, the calculation logic for processing the return air humidity and inner ring temperature is as follows:

[0286]

[0287] Here, RH represents relative humidity, which is the second humidity data.

[0288] S1008. Use the second humidity data as the humidity prediction value.

[0289] Based on the scenario example, the second humidity data is the result of the numerical model predicting the humidity of the air conditioner based on the operating parameters and / or environmental parameters of the air conditioner, and can be used as a humidity prediction value.

[0290] Numerical models are used for numerical calculations. Based on numerical models, the accuracy of the obtained second humidity data can be guaranteed, thereby improving the accuracy of humidity prediction.

[0291] Optional, Figure 11 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 ,like Figure 11 As shown, the operating parameters and / or environmental parameters of the air conditioner are processed based on the fitted model to output predicted humidity values, including:

[0292] S1101. Determine the predicted air volume value corresponding to the air conditioner. Based on the fitting model, perform fitting processing on the predicted air volume value, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or environmental parameters to obtain the third humidity data. The first humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the physical model. The second humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the numerical model.

[0293] In the context of a scenario, a fitting model refers to a data-driven model that approximates a set of observed data using a functional form. It doesn't emphasize the underlying mechanisms and typically doesn't concern itself with physical meaning, only aiming to minimize error. First, the airflow of the air conditioner is predicted. Then, based on the predicted airflow, combined with first humidity data, second humidity data, the air conditioner's operating parameters, and / or environmental parameters, humidity is predicted.

[0294] Optional, Figure 12 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 First, such as Figure 12 As shown, the process for determining the predicted air volume is as follows:

[0295] S1201. Collect the fan speed and fan current of the air conditioner fan.

[0296] In the example scenario, fan speed refers to the rotational speed of the air conditioner fan motor, measured in revolutions per minute (rpm), which can be collected in real time by a sensor built into the air conditioner. Fan current refers to the operating current of the air conditioner fan motor, measured in amperes (amperes), which can be directly collected by a current sensor built into the air conditioner.

[0297] S1202. The fan speed and fan current are processed through a preset air volume numerical model to obtain the corresponding air volume value. The air volume numerical model represents the physical relationship between fan speed, fan current and air volume.

[0298] In a scenario example, fan speed directly affects airflow output, and there is a linear relationship between fan current and airflow. Therefore, based on the collected fan speed and current, real-time airflow prediction can be achieved. Optionally, the airflow value can be determined through an airflow numerical model, primarily based on the physical relationship between fan speed, fan current, and airflow. The collected fan speed and current are calculated to obtain the corresponding airflow value. The physical relationship between fan speed, fan current, and airflow can be a linear formula or an exponential formula.

[0299] For example, the numerical model for air volume is:

[0300]

[0301] in, For air volume, This refers to the fan speed. For the fan current, b are the fitting parameters.

[0302] Using a scenario example, the collected fan speed and fan current are used as inputs to the air volume numerical model. The fan speed and fan current are calculated using the formulas in the air volume numerical model to obtain the corresponding air volume value. In the formulas involved in the air volume numerical model, the values ​​of fitting parameters a and b can be obtained by fitting experimental data.

[0303] S1203. Input the fan speed, fan current and air volume values ​​as input data into the preset air volume prediction model.

[0304] Based on scenario examples, the fan speed, fan current, and air volume values ​​are normalized to obtain input data, which is then input into the air volume prediction model.

[0305] S1204. The input data is processed by the air volume prediction model to predict the air volume of the air conditioner and obtain the predicted air volume value of the air conditioner.

[0306] With specific scenario examples, the airflow prediction model can be a virtual sensor combining a physical model and a deep learning model, or it can be a model using the Transformer architecture. The airflow prediction model employs a multi-head attention mechanism to process the input data and predict the airflow, outputting the corresponding predicted airflow value.

[0307] Figure 13 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Second, such as Figure 13 As shown, based on the fitting model, the predicted air volume, the first humidity data, the second humidity data, the air conditioner's operating parameters, and / or environmental parameters are fitted to obtain the third humidity data, including:

[0308] S1301, Normalize the predicted air volume, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or the environmental parameters.

[0309] Based on scenario examples, the normalization process of input data maps the input data to a preset range (0-1), ensuring the stability of the input data. This improves the standardization and stability of the input data, thereby enhancing the prediction efficiency and accuracy of the humidity prediction model.

[0310] Optionally, during the training of the humidity prediction model, random noise or outliers can be added to the first and second humidity data to obtain training data. The model can then be trained using this training data. Random perturbations can be added to the first and second humidity data using a Gaussian distribution to introduce Gaussian noise and simulate sensor error scenarios. Outliers can be isolated samples introduced into the first and second humidity data to simulate sudden load changes. The training data is then normalized to avoid fluctuations in the model output due to noise or outliers, thereby improving the robustness of the humidity prediction model. Injecting random noise and outliers allows the model to learn abnormal patterns in advance, reducing prediction errors during actual operation.

[0311] S1302. Input the normalized predicted air volume, the first humidity data, the second humidity data, the air conditioner's operating parameters and / or environmental parameters as input data into the humidity prediction model. The humidity prediction model is a neural network model based on the Transformer architecture, used to predict humidity values.

[0312] With the help of scenario examples, the humidity prediction model can be a virtual sensor that combines a physical model and a deep learning model, or it can be a model that adopts the Transformer architecture. The humidity prediction model is used to process the input data to predict the humidity of the air conditioner.

[0313] S1303. The input data is processed using a multi-head attention mechanism of the humidity prediction model to obtain the processing results corresponding to each attention head.

[0314] With a scenario example, the multi-head attention mechanism refers to capturing the multidimensional correlations between features of the input data by computing multiple attention heads in parallel, in order to obtain the processing results corresponding to each attention head. The processing results corresponding to each attention head can be denoted as headi (i=1-n), where n is the number of attention heads. For example, a humidity prediction model includes 8 attention heads. The 8 attention heads determine the different feature correlations between fan speed, fan current, and humidity values ​​obtained from the physical model, and then the processing results corresponding to the 8 attention heads are head1-head8 respectively.

[0315] Optional, Figure 14 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Third, such as Figure 14 As shown, before S1303, it also includes:

[0316] S1401. Determine the gating score corresponding to each attention point through a sparse gating mechanism.

[0317] With specific scenario examples, a corresponding gating mechanism can be configured for each attention head. The sparse gating mechanism refers to selectively activating some attention heads by determining the gating score for each attention head, thereby reducing computational resource consumption. For example, the gating score for each attention head can be determined using the following formula:

[0318]

[0319] in, This refers to the gating score corresponding to the attention head; This refers to the input data ( A linear transformation is performed to obtain the basic gating score; ε refers to Gaussian noise, which is used to increase the randomness of gating and improve the sparsity and generalization ability of the humidity prediction model; Softplus is the activation function, with the formula Softplus(z)=ln(1+ez), which maps the input data to non-negative values ​​and serves as the noise intensity coefficient, allowing the noise level to be dynamically adjusted with the input. Noise intensity.

[0320] S1402. Based on the gating scores corresponding to each attention head, determine the attention heads to be activated.

[0321] Based on scenario examples, the gating scores corresponding to each attention head are arranged from largest to smallest. The Top-K strategy is used to determine the K attention heads with the highest gating scores as the attention heads to be activated. If the Top-K strategy indicates that two attention heads need to be activated, then the attention heads with the highest gating scores (the first two) are determined as the attention heads to be activated.

[0322] S1403. Activate the attention head to be activated.

[0323] Based on a scenario example, a sparse gating mechanism is used to activate the two attention heads identified above. Only the two activated attention heads are used to extract features from the input data. Based on the method provided in this example, the attention heads to be activated are determined according to their gating scores, ensuring that the activated attention heads accurately analyze the input data and guaranteeing the accuracy of humidity prediction.

[0324] Optional, Figure 15 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Fourth, such as Figure 15 As shown, S1303 includes:

[0325] S1501. For each activated attention head, determine the query vector, key vector, and value vector corresponding to the attention head through input data, and normalize the query vector, key vector, and value vector to obtain the processing result corresponding to the attention head.

[0326] Based on a scenario example, we can define the query vector corresponding to the attention head as Q, the key vector as K, and the value vector as V. In the Transformer architecture, the query vector Q corresponds to the weight matrix W. Q The weight matrix W corresponding to the key vector K k The sum vector V corresponds to the weight matrix W. V Weight matrix W Q The weights of the query vector Q corresponding to each attention head are included in the weight matrix W. Q The first weight of the query vector Q corresponding to each activated attention head is determined in the matrix. Similarly, the weight matrix W... k The weights of the key vector K corresponding to each attention head are included in the weight matrix W. k The second weights of the key vectors K corresponding to each activated attention head are determined in the matrix W. V The weights of the value vector V corresponding to each attention head are included in the weight matrix W. V The third weight of the value vector V corresponding to each activated attention head is determined. The query vector Q, key vector K, and value vector V can be determined by the following formula:

[0327]

[0328] in, This refers to the query vector corresponding to the i-th attention head. This refers to the key vector corresponding to the i-th attention head. X refers to the value vector corresponding to the i-th attention head, and X refers to the input data.

[0329] For each activated attention head, the query vector, key vector, and value vector corresponding to that attention head can be normalized using the following attention head processing formula:

[0330]

[0331] in, This refers to the processing result corresponding to the i-th attention head; softmax is a normalization function that maps the score to attention weights between 0 and 1, so that the sum of all weights is 1; It refers to The transpose of the matrix; This refers to the multi-head attention subspace dimension. For example, the humidity prediction model in this embodiment includes 8 attention heads. =8.

[0332] Therefore, for each activated attention head, the corresponding processing result can be obtained by referring to the attention head processing formula mentioned above.

[0333] S1502. For each attention head that is not activated, set the processing result corresponding to the attention head to zero.

[0334] Based on the scenario example, for attention heads that are not activated, they do not need to participate in feature extraction of the input data, and the corresponding processing result can be directly determined as zero.

[0335] Based on the method provided in this example, the key feature correlation is preserved by activating the attention head, and the processing results of the inactive ones are set to zero. This ensures that the input data is fully extracted while avoiding the interference of the inactive attention head on the splicing result.

[0336] S1304. The processing results corresponding to each attention point are spliced ​​together to obtain the corresponding splicing result.

[0337] Based on the scenario example, the concatenated result, which is the final output of multi-head attention, can be determined using the following formula:

[0338]

[0339] in, The final output of multi-head attention; This refers to the concatenation operation, which concatenates the processing results of n attention heads into a large matrix according to their dimensions, where n is the number of attention heads; The output linear transformation matrix is ​​used to map the spliced ​​result to the target dimension, ensuring compatibility with the input dimension of the humidity prediction model. The target dimension refers to the dimension of the multi-head attention subspace, which is the number of attention heads, such as 8 in the example above.

[0340] S1305. The splicing results are processed using a preset normalization formula to obtain the third humidity data.

[0341] Based on the scenario example and the final output of the multi-head attention obtained above, humidity is predicted to obtain third humidity data.

[0342] Based on the method provided in this example, by resetting the gating weight of inactive attention heads to zero, the interference of inactive attention heads on humidity prediction can be avoided, and the normalization of the stitching results can be improved, thereby improving the accuracy of humidity prediction.

[0343] Optional, Figure 16 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Fifth, such as Figure 16 As shown, S1203 includes:

[0344] S1601. For each activated attention head, determine the gating weight corresponding to the attention head by using the preset gating weight relationship and the gating score corresponding to the attention head.

[0345] With a scenario example, the gating weight relationship is as follows:

[0346]

[0347] in, This refers to the input data ( The gating weights for the i-th attention head; This refers to the gating score of the i-th attention head; exp is an exponential function used to calculate the exponential score of the activated attention head and to amplify the score difference, so that the attention head to be activated with a higher gating score gets a higher weight; This refers to summing the exponential scores of all attention heads to be activated and using them for normalization, so that the sum of the weights of all attention heads to be activated is 1.

[0348] Using the gating weight relationship described above, each attention head to be activated is assigned a corresponding weight.

[0349] S1602. For each attention head that is not activated, reset the gating weight corresponding to the attention head to zero.

[0350] Similarly, by using the above gating weight relationship, the weights of the remaining attention heads are reset to zero, based on the scenario example.

[0351] S1603. Based on the gating weights corresponding to each attention point, the splicing results are processed by a preset normalization formula to obtain the third humidity data.

[0352] With a scenario example, the normalization formula is as follows:

[0353]

[0354] in, This refers to the virtual humidity data output, which is the humidity prediction value. H refers to the input data of the normalization formula of this layer, and H refers to the final output of the multi-head attention obtained above. This refers to normalization processing; Let be the gating weight for the i-th attention head; This refers to the forward computation result of the i-th attention head pair exiting the input; This refers to the weighted summation of the forward computation results of the K attention heads activated by the Top-K strategy.

[0355] Based on the method provided in this example, by resetting the gating weight of inactive attention heads to zero, the interference of inactive attention heads on humidity prediction can be avoided, and the normalization of the stitching results can be improved, thereby improving the accuracy of humidity prediction.

[0356] S1102, or, based on the fitting model, the outer ring temperature, outer ring humidity and air pressure are fitted to obtain the fourth humidity data.

[0357] Using a scenario example, real-time outdoor environmental data can be collected first, recording a set every 5 minutes, covering the outer ring temperature, outer ring humidity, air pressure, and the actual humidity of the air conditioner. Missing values ​​and outliers (such as temperature out-of-range data or sudden changes in air pressure) are removed. Then, 80% of the data is used as a training set and 20% as a test set to train and test the fitted model. The trained fitted model can quickly output a fitted humidity value based on the outer ring temperature, outer ring humidity, and air pressure, and this output fitted humidity value is used as the fourth temperature data point.

[0358] S1103, or, based on the fitting model, the operating parameters of the air conditioner are fitted to obtain the fifth humidity data.

[0359] Using a scenario example, the core operating parameters of the air conditioner and its actual humidity are first collected, with one set recorded every 3 minutes. These core operating parameters include indoor fan speed, indoor fan current, outdoor fan speed, outdoor fan current, compressor operating frequency, expansion valve opening, exhaust temperature, indoor and outdoor pipe temperatures, indoor fan damper, and outdoor fan input power. At least 1000 sets of data are collected, and abnormal data such as excessively high or low temperatures, sudden changes in air pressure, and missing parameters are removed. After preprocessing such as deduplication and completion, 80% is used as the training set and 20% as the test set. A linear regression model is selected for fitting. Based on the training and test sets, the linear regression model is trained to quickly output fitted humidity values ​​according to the air conditioner's operating parameters. The obtained fitted humidity values ​​are then used as the fifth set of temperature data.

[0360] S1104. Use the third, fourth, or fifth humidity data as the humidity prediction value.

[0361] Based on the scenario examples, the third, fourth, or fifth humidity data obtained through the above three methods can all be used as humidity prediction values ​​for air conditioners.

[0362] Based on the method provided in this example, the operating parameters and / or environmental parameters of the air conditioner can be fitted in different ways according to the fitting model, which can improve the accuracy of humidity prediction.

[0363] Optional, Figure 17 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 Sixth, such as Figure 17 As shown, the operating parameters and / or environmental parameters of the air conditioner are processed based on a mapping model to output predicted humidity values, including:

[0364] S1701. Establish the mapping relationship between the operating parameters and / or environmental parameters of the air conditioner and humidity, and form a mapping table or mapping curve.

[0365] In the context of scenario examples, a mapping model refers to a model that includes the correspondence between input and output data. It does not require explicit functions or physical mechanisms and emphasizes the transformation relationship of "input → output." Operating parameters used to establish the mapping relationship can include compressor operating frequency, indoor fan damper, and indoor pipe temperature; environmental parameters can include inner ring temperature. Multiple sets of valid data on compressor operating frequency, indoor fan damper, indoor pipe temperature, inner ring temperature, and humidity are collected. Based on the collected valid data, a mapping relationship between the air conditioner's operating parameters and / or environmental parameters and humidity is established. This data can be used to create a mapping table or mapping curve to record the mapping relationship between compressor operating frequency, indoor fan damper, indoor pipe temperature, inner ring temperature, and humidity.

[0366] S1702. Collect the operating parameters and environmental parameters of the air conditioner, input the mapping table or mapping curve for table lookup or interpolation processing, and output the corresponding humidity prediction value.

[0367] Based on a scenario example, actual data corresponding to the compressor operating frequency, indoor fan damper, indoor pipe temperature, and / or inner ring temperature during air conditioner operation are collected. This data is input into a mapping model, and the actual data are matched with a mapping table or curve. Humidity values ​​that have a mapping relationship with the actual data corresponding to the compressor operating frequency, indoor fan damper, indoor pipe temperature, and / or inner ring temperature are determined by directly querying the mapping table. Alternatively, the humidity value can be obtained by fitting the actual data corresponding to the compressor operating frequency, indoor fan damper, indoor pipe temperature, and / or inner ring temperature to a mapping curve, and this obtained humidity value is determined as the predicted humidity value. If there is a deviation between the actual data corresponding to the compressor operating frequency, indoor fan damper, indoor pipe temperature, and / or inner ring temperature and the mapping table or curve, a linear interpolation algorithm can be used to calculate the fitted humidity value based on adjacent operating parameters and environmental parameters to obtain the corresponding predicted humidity value.

[0368] Based on the method provided in this example, the corresponding humidity prediction value can be determined based on the direct mapping relationship between the target operating parameters and / or target environmental parameters of the air conditioner and humidity, which can improve the accuracy of humidity prediction.

[0369] Optionally, the humidity model can be stored in the air conditioner's local storage or in a cloud server.

[0370] In summary, humidity models include physical models, numerical models, fitting models, and mapping models. Each type of humidity model can be used to predict humidity. These models can be stored locally on the air conditioner, allowing the local processor to predict humidity. Alternatively, they can be stored on a cloud server, enabling collaborative processing and humidity prediction. Based on the method provided in this example, humidity can be predicted using either a local processor or a cloud server, thus improving the diversity and convenience of humidity prediction.

[0371] Optional, Figure 18 This is a flowchart illustrating an air conditioning control method according to some embodiments of the present disclosure. Figure 10 7. For example Figure 18 As shown, it also includes:

[0372] S1801. Determine whether the humidity display function of the air conditioner is turned on.

[0373] Using scenario examples, the system collects background operation data from the air conditioner and determines whether the humidity display function of the air conditioner is enabled.

[0374] S1802. If it is determined that the humidity display function of the air conditioner is not turned on, the target interface controlling the air conditioner will not display the humidity prediction value.

[0375] Based on the scenario example, when the air conditioner's humidity display function is not enabled, on the one hand, there is no need to display the humidity prediction value on the air conditioner's screen; on the other hand, there is no need to send the humidity prediction value to the user terminal that communicates with the air conditioner for display. Based on the method provided in this example, when the air conditioner does not have a display function, the target interface does not display the humidity prediction value, which can save the air conditioner's energy.

[0376] Optional features include: switching the air conditioner's operating mode based on humidity forecasts.

[0377] By referring to the predicted humidity value, the trend of humidity change can be determined, and then the air conditioner's operating mode can be switched based on the humidity prediction. For example, if the predicted humidity value is consistently higher than a preset threshold, it indicates that the humidity in the air is high, and the system can automatically switch to dehumidification mode. Therefore, based on the method provided in this example, the air conditioner's operating mode can be switched in advance based on the humidity prediction value, ensuring that the air conditioner's operating mode is more in line with the actual operating conditions and improving the air conditioner's intelligence.

[0378] Figure 19 This is a structural diagram of an air conditioner control device according to some embodiments of the present disclosure. The air conditioner control device is used to process the aforementioned air conditioner control method, such as... Figure 19 As shown, it includes:

[0379] The response module 191 is used to collect the operating parameters of the air conditioner and / or environmental parameters in response to the air conditioner being in cooling mode or dehumidification mode.

[0380] The processing module 192 is used to process the operating parameters and / or environmental parameters of the air conditioner based on the humidity model and output the humidity prediction value.

[0381] The processing module 192 is also used to display the humidity prediction value on the target interface.

[0382] The processing module 192 is specifically used to collect the operating parameters and / or environmental parameters of the air conditioner in response to the air conditioner being in cooling mode or dehumidification mode when the air conditioner has no humidity sensor or the humidity sensor is damaged.

[0383] Optionally, the processing module 192 is specifically used to process the operating parameters and / or environmental parameters of the air conditioner based on a physical model, numerical model, fitting model or mapping model, and output humidity prediction values.

[0384] Optionally, the processing module 192 is further used to correct the air outlet temperature of the air conditioner based on the air conditioner's operating parameters and environmental parameters, so as to obtain the corrected outer air outlet temperature and the corrected inner air outlet temperature.

[0385] The processing module 192 is also used to determine the heat exchange of the outdoor unit based on the corrected external air outlet temperature, the operating parameters of the air conditioner and the environmental parameters.

[0386] The processing module 192 is further used to determine the air conditioner's internal air outlet status data based on the corrected internal air outlet temperature, wherein the air conditioner's internal air outlet status data includes the air outlet enthalpy value.

[0387] The processing module 192 is also used to determine the return air enthalpy of the air conditioner based on environmental parameters, the heat exchange of the outdoor unit, and the outlet air enthalpy.

[0388] The processing module 192 is also used to determine the moisture content of the return air based on the enthalpy of the return air and the inner ring temperature;

[0389] The processing module 192 is also specifically used to obtain the first humidity data based on the return air humidity.

[0390] The processing module 192 is also used to use the first humidity data as a humidity prediction value.

[0391] Optionally, the processing module 192 is further used to process the outer pipe temperature, outer ring temperature, and first fitting parameters using a preset first physical relationship to obtain the corrected outer outlet air temperature, wherein the first physical relationship is:

[0392]

[0393] in, The outside air outlet temperature, This refers to the temperature of the outer tube. The outer ring temperature, These are the first fitted parameters;

[0394] Processing module 192 is further used to process the inner pipe temperature, inner ring temperature, and second fitting parameters using a preset second physical relationship to obtain the corrected inner outlet air temperature. The second physical relationship is as follows:

[0395]

[0396] in, The temperature of the air outlet on the inside. This refers to the temperature of the inner tube. The inner ring temperature, is the second fitting parameter.

[0397] Optionally, the processing module 192 is also used to determine the outdoor air volume;

[0398] Processing module 192 is further used to process the corrected outer outlet air temperature, outdoor fan input power, outer air density, outdoor air volume, outer ring temperature, and outer air constant pressure specific heat according to a preset energy conservation equation, so as to obtain the heat exchange capacity of the outdoor unit. The energy conservation equation is as follows:

[0399]

[0400] in, For heat exchange of the outdoor unit, The density of the air on the outside. This refers to the outdoor airflow. The specific heat at constant pressure of the outer air. The outside air outlet temperature, This refers to the outer ring temperature.

[0401] Optionally, the processing module 192 is further used to process the corrected inner air outlet temperature based on a preset third physical relationship to obtain the saturated water vapor pressure corresponding to the inner side of the air conditioner, wherein the third physical relationship characterizes the correspondence between the inner air outlet temperature and the saturated water vapor pressure.

[0402] The processing module 192 is further used to determine the partial pressure of water vapor inside the air conditioner by multiplying the saturated water vapor pressure with the preset humidity fitting parameters.

[0403] The processing module 192 is further used to process the water vapor partial pressure inside the air conditioner based on the preset fourth physical relation to obtain the corresponding outlet air humidity. The fourth physical relation characterizes the correspondence between water vapor partial pressure and outlet air humidity.

[0404] The processing module 192 is further used to process the corrected inner outlet air temperature and outlet air moisture content based on the preset fifth physical relation to obtain the outlet air enthalpy value, wherein the fifth physical relation characterizes the correspondence between the inner outlet air temperature, outlet air moisture content and outlet air enthalpy value.

[0405] Optionally, the processing module 192 is also used to determine the indoor air volume;

[0406] The processing module 192 is also specifically used to determine the mass flow rate of the indoor air based on the indoor air volume and the indoor air density;

[0407] The processing module 192 is also used to determine the product of the mass flow rate of the inner air and the heat exchange of the outdoor unit, and to sum the product with the outlet enthalpy to obtain the return air enthalpy.

[0408] Optionally, the processing module 192 is further used to process the return air enthalpy and inner ring temperature based on a preset sixth physical relation to obtain the return air moisture content, wherein the sixth physical relation characterizes the correspondence between the return air enthalpy, inner ring temperature and return air moisture content.

[0409] Optionally, the processing module 192 is further used to process the return air humidity based on the preset seventh physical relation to obtain the corresponding water vapor partial pressure, wherein the seventh physical relation characterizes the correspondence between the return air humidity and the water vapor partial pressure.

[0410] The processing module 192 is also specifically used to determine the saturated water vapor pressure at the inner ring temperature based on the preset eighth physical relation.

[0411] The processing module 192 is also used to determine the ratio of water vapor partial pressure to saturated water vapor pressure as the first humidity data.

[0412] Optionally, the processing module 192 is further used to process the indoor fan speed and indoor fan current to obtain the indoor air volume.

[0413] The outer ring temperature, inner pipe temperature, inner ring temperature, indoor air volume, compressor operating frequency, exhaust temperature and outer pipe temperature are processed to obtain the corresponding latent heat.

[0414] The processing module 192 is specifically used to process the inner pipe temperature, inner ring temperature, latent heat and indoor air volume to obtain the corresponding indoor unit outlet dry bulb temperature.

[0415] The processing module 192 is specifically used to process the inner tube temperature, inner ring temperature and indoor unit outlet dry bulb temperature to obtain the corresponding inner outlet wet bulb temperature.

[0416] The processing module 192 is specifically used to process the dry bulb temperature of the indoor unit's outlet air and the wet bulb temperature of the inner outlet air to obtain the corresponding outlet air humidity content.

[0417] The processing module 192 is also used to obtain the corresponding return air humidity based on the outlet air humidity.

[0418] The processing module 192 is specifically used to process the return air humidity and inner ring temperature to obtain second humidity data;

[0419] The processing module 192 is also used to use the second humidity data as a humidity prediction value.

[0420] Optionally, the processing module 192 is further used to determine the predicted air volume value corresponding to the air conditioner, and to perform fitting processing on the predicted air volume value, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or environmental parameters based on the fitting model to obtain the third humidity data. The first humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the physical model, and the second humidity data is the humidity prediction value obtained by processing the operating parameters of the air conditioner and / or environmental parameters based on the numerical model.

[0421] Processing module 192 is specifically used to perform fitting processing on the outer ring temperature, outer ring humidity and air pressure based on the fitting model to obtain the fourth humidity data;

[0422] The processing module 192 is specifically used to, or, perform fitting processing on the operating parameters of the air conditioner based on the fitting model to obtain the fifth humidity data;

[0423] The processing module 192 is also used to use the third humidity data, the fourth humidity data, or the fifth humidity data as humidity prediction values.

[0424] Optionally, the processing module 192 is further used to normalize the predicted air volume value, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or environmental parameters.

[0425] The processing module 192 is further used to input the normalized predicted air volume value, the first humidity data, the second humidity data, the air conditioner's operating parameters and / or environmental parameters as input data into the humidity prediction model, wherein the humidity prediction model is a neural network model based on the Transformer architecture, used to predict humidity values.

[0426] The processing module 192 is further used to process the input data using the multi-head attention mechanism of the humidity prediction model to obtain the processing results corresponding to each attention head.

[0427] The processing module 192 is further used to splice the processing results corresponding to each attention point to obtain the corresponding splicing result;

[0428] The processing module 192 is specifically used to process the splicing results using a preset normalization formula to obtain third humidity data.

[0429] Optionally, the processing module 192 is also used to determine the gating score corresponding to each attention point through a sparse gating mechanism;

[0430] Processing module 192 is also used to determine the attention head to be activated based on the gating score corresponding to each attention head;

[0431] The processing module 192 is also used to activate the attention head to be activated.

[0432] Optionally, the processing module 192 is further configured to determine the query vector, key vector, and value vector corresponding to each activated attention head through input data, and to normalize the query vector, key vector, and value vector to obtain the processing result corresponding to the attention head.

[0433] The processing module 192 is further used to set the processing result corresponding to each inactive attention head to zero.

[0434] Optionally, the processing module 192 is further used to determine the gating weight corresponding to each activated attention head by using a preset gating weight relationship and the gating score corresponding to the attention head.

[0435] The processing module 192 is further used to reset the gating weight corresponding to each inactive attention head to zero;

[0436] The processing module 192 is further used to process the splicing results based on the gating weights corresponding to each attention head and through a preset normalization formula to obtain the third humidity data.

[0437] Optionally, the processing module 192 is further used to establish a mapping relationship between the operating parameters and / or environmental parameters of the air conditioner and humidity, forming a mapping table or mapping curve.

[0438] The processing module 192 is further used to collect the operating parameters and environmental parameters of the air conditioner, input the mapping table or mapping curve for table lookup or interpolation processing, and output the corresponding humidity prediction value.

[0439] Optionally, the processing module 192 is also used to dynamically display the humidity prediction value of the air conditioner through the air conditioner's display screen;

[0440] The processing module 192 is also used to dynamically display the humidity prediction value of the air conditioner, either directly or through preset software on the user terminal.

[0441] Optionally, the processing module 192 is also used to determine whether the air conditioner has its humidity display function enabled;

[0442] The processing module 192 is also used to control the target interface of the air conditioner not to display the humidity prediction value if it is determined that the humidity display function of the air conditioner is not turned on.

[0443] The optional processing module 192 is also used to switch the operating mode of the air conditioner based on the humidity prediction value.

[0444] The specific implementation process of the air conditioner control device provided in this embodiment can be found in the above method embodiment. The implementation principle and technical effect are similar, and will not be repeated here.

[0445] This disclosure also provides an air conditioner, including: a memory and a display screen; the memory stores computer-executed instructions; the computer-executed instructions stored in the memory are executed to implement the air conditioner control method as described in any of the first aspects above; the display screen is used to dynamically display the humidity prediction value of the air conditioner.

[0446] Optionally, the device for executing computer-executable instructions stored in memory can be a local processor of the air conditioner. Figure 20 This is a structural diagram of the air conditioner disclosed herein, such as... Figure 20As shown, the air conditioner includes a memory 502, a display screen 503, a processor 501, and a communication component 504. The processor 501, memory 502, display screen 503, and communication component 504 are connected via a bus. In specific implementation, at least one processor 501 executes computer execution instructions stored in the memory 502, causing at least one processor 501 to perform the aforementioned air conditioner control method. The specific implementation process of the processor 501 can be found in the above-described method embodiment, and its implementation principle and technical effects are similar; therefore, it will not be repeated here.

[0447] Alternatively, the instructions executed by the storage computer can also be processed collaboratively by the cloud server. For the specific implementation process, please refer to the above method embodiments. The implementation principle and technical effect are similar, and will not be repeated here.

[0448] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0449] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0450] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0451] This disclosure also provides a computer program product, including a computer program that, when executed, implements the methods described above. Similarly, the computer program can be executed by an air conditioner's local processor or a cloud server.

[0452] This disclosure also provides a computer-readable storage medium storing computer-executable instructions that, when executed, implement the above-described method. Similarly, the computer-executable instructions can be executed by a local processor of an air conditioner or a cloud server.

[0453] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0454] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0455] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0456] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0457] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0458] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0459] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0460] Those skilled in the art will also understand that the various illustrative logical blocks and steps listed in the embodiments of this disclosure can be implemented by electronic hardware, computer software, or a combination of both. Whether such functionality is implemented in hardware or software depends on the specific application and the overall system design requirements. Those skilled in the art can implement the functionality using various methods for each specific application, but such implementation should not be construed as exceeding the scope of protection of the embodiments of this disclosure.

[0461] In the above detailed description, reference has been made to the accompanying drawings, which illustrate specific aspects of this disclosure by way of illustration. In this regard, terms indicating direction or positional relationship, such as “center,” “longitudinal,” “lateral,” “length,” “width,” “thickness,” “upper,” “lower,” “front,” “rear,” “left,” “right,” “vertical,” “horizontal,” “top,” “bottom,” “inner,” “outer,” “clockwise,” “counterclockwise,” “axial,” “radial,” and “circumferential,” are used with reference to the orientation of the described figures. Since components of the described device can be positioned in multiple different orientations, directional terms are used for illustrative purposes and not for limitation. It should be understood that other aspects can be utilized and structural or logical changes can be made without departing from the concept of this disclosure. Therefore, the following detailed description should not be considered limiting.

[0462] It should be understood that, unless otherwise specifically indicated, features of various embodiments of this disclosure described herein can be combined with each other. As used herein, the term "and / or" includes any one of the relevant listed items and any combination of any two or more.

[0463] It should be understood that, unless otherwise expressly specified and limited, the terms "joining," "attaching," "installing," "connecting," "linking," "fixing," etc., used in the embodiments of this disclosure should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms herein based on the specific circumstances.

[0464] Furthermore, the term "above" as used herein with respect to components, elements, or material layers formed or located "above" a surface may be used to indicate that the component, element, or material layer is "indirectly" positioned (e.g., placed, formed, deposited, etc.) on the surface such that one or more additional components, elements, or layers are arranged between the surface and the component, element, or material layer. However, the term "above" as used with respect to components, elements, or material layers formed or located "above" a surface may also optionally have a specific meaning: that the component, element, or material layer is "directly" positioned (e.g., placed, formed, deposited, etc.) on the surface, for example, in direct contact with the surface.

[0465] Although terms such as “first,” “second,” and “third” may be used herein to describe various components, parts, regions, layers, or sections, these components, parts, regions, layers, or sections are not limited to these terms. Rather, these terms are used only to distinguish one component, part, region, layer, or section from another. Therefore, without departing from the teachings of the examples described herein, the first component, part, region, layer, or section mentioned in the examples may also be referred to as the second component, part, region, layer, or section. Furthermore, the terms “first” and “second” are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as “first” or “second” may explicitly or implicitly include at least one of that feature. In the description herein, “a plurality” means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0466] It should be understood that spatial relative terms, such as “above,” “upper,” “below,” and “lower,” are used herein to describe the relationship between one element and another shown in the figures. In addition to the orientation depicted in the figures, these spatial relative terms are also intended to encompass different orientations of the device in use or operation. For example, if the device in the figures is flipped, an element described as “above” or “upper” relative to another element would be “below” or “lower” relative to that other element. Thus, depending on the spatial orientation of the device, the term “above” encompasses both above and below orientations. Devices may have other orientations (e.g., rotated 90 degrees or in other orientations), and the spatial relative terms used herein should be interpreted accordingly.

[0467] Furthermore, the term “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as advantageous compared to other aspects or designs. Rather, the use of the term “exemplary” is intended to present the concept in a concrete manner. As used herein, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise specified or clear from the context, “X applies A or B” is intended to mean any of the natural inclusive arrangements. That is, “X applies A or B” satisfies any of the foregoing instances if X applies A; X applies B; or both X applies A and B. Additionally, unless otherwise specified or clear from the context to refer to the singular form, the articles “a” and “an” as used in this disclosure and the appended claims are generally understood to mean “one or more.”

[0468] Similarly, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components described above (e.g., elements, resources, etc.), unless otherwise indicated, the terminology used to describe such components is intended to correspond to any component (functionally equivalent) that performs the specific function of the described component, even if structurally not equivalent to the disclosed structure. Furthermore, although specific features of this disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, as may be desired and advantageous to any given or particular application. Moreover, with regard to the terms “comprising,” “owning,” “having,” “having,” or variations thereof as used in the detailed description or claims, such terms are intended to be inclusive in a manner similar to the term “including.”

[0469] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0470] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for controlling an air conditioner, characterized in that, include: In response to the air conditioner being in cooling or dehumidification mode, collect the air conditioner's operating parameters and / or environmental parameters; The operating parameters and / or environmental parameters of the air conditioner are processed based on the humidity model to output a humidity prediction value. The predicted humidity value is displayed on the target interface.

2. The method according to claim 1, characterized in that, The step of collecting the air conditioner's operating parameters and / or environmental parameters in response to the air conditioner being in cooling or dehumidifying mode further includes: When the air conditioner has no humidity sensor or the humidity sensor is damaged, the operating parameters of the air conditioner and / or environmental parameters are collected in response to the air conditioner being in cooling mode or dehumidification mode.

3. The method according to claim 2, characterized in that, The operating parameters of the air conditioner include one or more of the following: indoor fan speed, outdoor fan speed, indoor fan current, outdoor fan current, compressor operating frequency, expansion valve opening, exhaust temperature, inner pipe temperature and outer pipe temperature, indoor fan damper and outdoor fan input power; The environmental parameters include one or more of the following: inner ring temperature, outer ring temperature, outer ring humidity, air pressure, outer air density, outer air specific heat at constant pressure, and inner air density.

4. The method according to claim 3, characterized in that, The process of processing the operating parameters and / or environmental parameters of the air conditioner based on the humidity model to output predicted humidity values ​​includes: The operating parameters and / or environmental parameters of the air conditioner are processed based on physical models, numerical models, fitting models, or mapping models to output humidity prediction values.

5. The method according to claim 4, characterized in that, The operating parameters of the air conditioner processed by the physical model include: outdoor fan speed, outdoor fan current, outdoor pipe temperature, inner pipe temperature, and outdoor fan input power; the environmental parameters processed by the physical model include: outer ring temperature, inner ring temperature, outer air density, outer air specific heat at constant pressure, and inner air density.

6. The method according to claim 5, characterized in that, The operating parameters and / or environmental parameters of the air conditioner are processed based on a physical model to output predicted humidity values, including: The air outlet temperature of the air conditioner is corrected based on the operating parameters and environmental parameters of the air conditioner to obtain the corrected outer air outlet temperature and the corrected inner air outlet temperature. The heat exchange capacity of the outdoor unit is determined based on the corrected external air outlet temperature, the operating parameters of the air conditioner, and the environmental parameters. The air conditioner's internal air outlet status data is determined based on the corrected internal air outlet temperature, wherein the air conditioner's internal air outlet status data includes the air outlet enthalpy value. Based on the aforementioned environmental parameters, the heat exchange capacity of the outdoor unit, and the outlet air enthalpy, the return air enthalpy of the air conditioner is determined. The moisture content of the return air is determined based on the return air enthalpy and the inner ring temperature. Based on the moisture content of the return air, the first humidity data is obtained; The first humidity data is used as the predicted humidity value.

7. The method according to claim 6, characterized in that, The step of correcting the air outlet temperature of the air conditioner based on its operating parameters and environmental parameters to obtain corrected outer and inner air outlet temperatures includes: The outer pipe temperature, outer ring temperature, and first fitting parameters are processed using a preset first physical relationship to obtain the corrected outer outlet air temperature. The first physical relationship is: in, The outside air outlet temperature, This refers to the temperature of the outer tube. The outer ring temperature, These are the first fitted parameters; The inner pipe temperature, inner ring temperature, and second fitting parameter are processed using a preset second physical relationship to obtain the corrected inner outlet air temperature. The second physical relationship is as follows: in, The temperature of the air outlet on the inside. This refers to the temperature of the inner tube. The inner ring temperature. is the second fitting parameter.

8. The method according to claim 6, characterized in that, The process of determining the heat exchange capacity of the outdoor unit based on the corrected external air outlet temperature, the operating parameters of the air conditioner, and environmental parameters includes: Determine the outdoor air volume; Based on a preset energy conservation equation, the corrected external outlet air temperature, external fan input power, external air density, outdoor air volume, external ring temperature, and external air specific heat at constant pressure are processed to obtain the heat exchange capacity of the outdoor unit. The energy conservation equation is as follows: in, For heat exchange of the outdoor unit, The density of the air on the outside. This refers to the outdoor airflow. The specific heat at constant pressure of the outer air. The outside air outlet temperature, This refers to the outer ring temperature.

9. The method according to claim 6, characterized in that, The process of determining the air conditioner's inner outlet air status data based on the corrected inner outlet air temperature includes: The modified inner outlet air temperature is processed based on a preset third physical relationship to obtain the corresponding saturated water vapor pressure inside the air conditioner. The third physical relationship represents the correspondence between the inner outlet air temperature and the saturated water vapor pressure. The product of the saturated water vapor pressure and the preset humidity fitting parameters is determined as the water vapor partial pressure inside the air conditioner. The water vapor partial pressure inside the air conditioner is processed based on a preset fourth physical relation to obtain the corresponding outlet air humidity. The fourth physical relation characterizes the correspondence between water vapor partial pressure and outlet air humidity. The modified inner outlet air temperature and outlet air humidity are processed based on the preset fifth physical relation to obtain the outlet air enthalpy value, wherein the fifth physical relation characterizes the correspondence between the inner outlet air temperature, outlet air humidity and outlet air enthalpy value.

10. The method according to claim 6, characterized in that, The determination of the return air enthalpy value of the air conditioner based on the environmental parameters, the heat exchange capacity of the outdoor unit, and the outlet air enthalpy value includes: Determine the indoor air volume; The mass flow rate of the inner air is determined based on the indoor side air volume and the inner side air density. The product of the mass flow rate of the inner air and the heat exchange of the outdoor unit is determined, and the product is summed with the outlet air enthalpy to obtain the return air enthalpy.

11. The method according to claim 6, characterized in that, Determining the moisture content of the return air based on the return air enthalpy and the inner ring temperature includes: The return air enthalpy and inner ring temperature are processed based on a preset sixth physical relation to obtain the return air moisture content. The sixth physical relation represents the correspondence between the return air enthalpy, inner ring temperature and return air moisture content.

12. The method according to claim 6, characterized in that, The process of obtaining the first humidity data based on the return air humidity includes: The return air humidity is processed based on the preset seventh physical relation to obtain the corresponding water vapor partial pressure, wherein the seventh physical relation characterizes the correspondence between the return air humidity and the water vapor partial pressure. The saturated water vapor pressure at the inner ring temperature is determined based on the preset eighth physical relation. The ratio of the water vapor partial pressure to the saturated water vapor pressure is determined as the first humidity data.

13. The method according to claim 4, characterized in that, The numerical model processes the following operating parameters of the air conditioner: indoor fan speed, indoor fan current, compressor operating frequency, exhaust temperature, outer pipe temperature, and inner pipe temperature; the numerical model processes the following environmental parameters: outer ring temperature and inner ring temperature.

14. The method according to claim 13, characterized in that, The operating parameters and / or environmental parameters of the air conditioner are processed based on a numerical model to output predicted humidity values, including: The indoor fan speed and indoor fan current are processed to obtain the indoor air volume; The outer ring temperature, inner pipe temperature, inner ring temperature, indoor air volume, compressor operating frequency, exhaust temperature, and outer pipe temperature are processed to obtain the corresponding latent heat. The inner tube temperature, inner ring temperature, latent heat, and indoor air volume are processed to obtain the corresponding indoor unit outlet dry bulb temperature. The inner tube temperature, inner ring temperature, and indoor unit outlet dry bulb temperature are processed to obtain the corresponding inner outlet wet bulb temperature. The dry bulb temperature of the indoor unit's outlet air and the wet bulb temperature of the inner outlet air are processed to obtain the corresponding outlet air moisture content; The corresponding return air humidity is obtained based on the outlet air humidity. The return air humidity and inner ring temperature are processed to obtain second humidity data; The second humidity data is used as the predicted humidity value.

15. The method according to claim 3, characterized in that, The operating parameters and / or environmental parameters of the air conditioner are processed based on the fitting model to output predicted humidity values, including: The predicted air volume value corresponding to the air conditioner is determined. Based on the fitting model, the predicted air volume value, the first humidity data, the second humidity data, the operating parameters and / or environmental parameters of the air conditioner are fitted to obtain the third humidity data. The first humidity data is the humidity prediction value obtained by processing the operating parameters and / or environmental parameters of the air conditioner based on the physical model. The second humidity data is the humidity prediction value obtained by processing the operating parameters and / or environmental parameters of the air conditioner based on the numerical model. Alternatively, the outer ambient temperature, outer ambient humidity, and air pressure can be fitted based on the aforementioned fitting model to obtain the fourth humidity data; Alternatively, the operating parameters of the air conditioner can be fitted based on the fitting model to obtain the fifth humidity data; The third, fourth, or fifth humidity data is used as the predicted humidity value.

16. The method according to claim 15, characterized in that, The process of fitting the predicted air volume, the first humidity data, the second humidity data, the operating parameters of the air conditioner, and / or environmental parameters based on the fitting model to obtain the third humidity data includes: The predicted air volume, the first humidity data, the second humidity data, the operating parameters of the air conditioner, and / or the environmental parameters are normalized. The normalized predicted air volume, the first humidity data, the second humidity data, the operating parameters of the air conditioner and / or environmental parameters are input into the humidity prediction model as input data. The humidity prediction model is a neural network model based on the Transformer architecture, which is used to predict humidity values. The input data is processed using the multi-head attention mechanism of the humidity prediction model to obtain the processing results corresponding to each attention head. The processing results corresponding to each attention point are concatenated to obtain the corresponding concatenation result; The splicing results are processed using a preset normalization formula to obtain the third humidity data.

17. The method according to claim 16, characterized in that, Before processing the input data using the multi-head attention mechanism of the humidity prediction model, the method further includes: The gating score corresponding to each attention head is determined by a sparse gating mechanism; Based on the gating score corresponding to each attention head, the attention heads to be activated are determined; The attention head to be activated is activated.

18. The method according to claim 17, characterized in that, The multi-head attention mechanism of the humidity prediction model is used to process the input data to obtain the processing results corresponding to each attention head, including: For each activated attention head, the query vector, key vector, and value vector corresponding to the attention head are determined through the input data. The query vector, key vector, and value vector are then normalized to obtain the processing result corresponding to the attention head. For each attention head that is not activated, the processing result corresponding to that attention head is set to zero.

19. The method according to claim 18, characterized in that, The step of processing the splicing result using a preset normalization formula to obtain the third humidity data includes: For each activated attention head, the gating weight corresponding to the attention head is determined by using a preset gating weight relationship and the gating score corresponding to the attention head; For each inactive attention head, reset the gating weight corresponding to that attention head to zero; Based on the gating weights corresponding to each attention point, the splicing result is processed by a preset normalization formula to obtain the third humidity data.

20. The method according to claim 4, characterized in that, The operating parameters and / or environmental parameters of the air conditioner are processed based on a mapping model to output predicted humidity values, including: Establish a mapping relationship between the operating parameters and / or environmental parameters of the air conditioner and humidity, forming a mapping table or mapping curve; The operating parameters and environmental parameters of the air conditioner are collected, and the data are input into the mapping table or mapping curve for lookup or interpolation processing, and the corresponding humidity prediction value is output.

21. The method according to any one of claims 1-20, characterized in that, The step of displaying the predicted humidity value on the target interface includes: The predicted humidity value of the air conditioner is dynamically displayed on the air conditioner's display screen. Alternatively, the humidity prediction value of the air conditioner can be dynamically displayed through preset software on the user terminal.

22. The method according to claim 1, characterized in that, The humidity model is stored in the local storage of the air conditioner or in a cloud server.

23. The method according to claim 1, characterized in that, Also includes: Determine whether the humidity display function of the air conditioner is turned on; If it is determined that the humidity display function of the air conditioner is not turned on, then the target interface of the air conditioner is controlled not to display the humidity prediction value.

24. A control device for an air conditioner, the control device for the air conditioner being used to process the control method for the air conditioner according to any one of claims 1-23, characterized in that, include: The response module is used to collect the operating parameters of the air conditioner and / or environmental parameters in response to whether the air conditioner is in cooling mode or dehumidification mode. The processing module is used to process the operating parameters and / or environmental parameters of the air conditioner based on the humidity model and output the humidity prediction value. The processing module is also used to display the humidity prediction value on the target interface.

25. An air conditioner, characterized in that, include: Memory and display screen; The memory stores computer-executed instructions; The computer execution instructions stored in the memory are executed to implement the air conditioner control method as described in any one of claims 1-23; The display screen is used to dynamically display the humidity prediction value of the air conditioner.

26. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, are used to implement the air conditioning control method as described in any one of claims 1-23.

27. A computer program product, characterized in that, It includes a computer program, which, when executed, implements the air conditioning control method as described in any one of claims 1-23.

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