Air conditioner control method, air conditioner and storage medium

Abstract

The invention provides an air conditioner control method, an air conditioner and a storage medium. The method comprises the steps that thermal data, user state data and air quality data of a current indoor space are obtained in real time; according to the heating power data, the user state data and the air quality data, air supply grade area division is conducted on the current indoor space, and air supply grade area data are obtained; obtaining a computational fluid dynamics simulation model database matched with the current indoor space; predicting based on a computational fluid dynamics simulation model database by utilizing a preset air supply strategy model according to the thermal data, the user state data, the air quality data and the air supply grade area data, and generating a current air supply strategy; and the air conditioner is controlled according to the current air supply strategy. By applying the air conditioner control method, the precision of the air supply strategy can be improved, and the air supply effect is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioners, in particular, to an air conditioner control method, an air conditioner applying the air conditioner control method, and a computer readable storage medium applying the air conditioner control method. BACKGROUND

[0002] At present, air conditioning systems are widely used in residential, office and commercial scenarios, and the air supply system thereof usually adopts a fixed air guide structure or a simple angle-adjustable blade design, and the control mode mainly adopts temperature setting and directional air supply. In recent years, with the rise of smart home, some high-end air conditioner products have introduced infrared sensing and automatic air direction adjustment functions, realizing basic recognition of the position of human body.

[0003] At present, some air conditioner products on the market use infrared sensors to identify the position of human heat sources, and adjust the angle of the air guide blade to avoid direct blowing or regional air supply. For example, some models can automatically adjust the air direction to the area where the user is located or deviate from the person who is resting, thereby improving the problem of direct blowing discomfort. However, such a system has the following technical limitations: the sensing information dimension is single, only the infrared temperature signal is used, the specific activity intensity, the body feeling state (cooling and heating feeling) or the air quality difference of the user cannot be identified, the control strategy is rough, overcooling / overheating adjustment is prone to occur, and the air supply cannot be adjusted according to the influence of the current indoor layout on the air flow.

[0004] Therefore, a more optimized air conditioner control method needs to be considered. SUMMARY

[0005] A first object of the present application is to provide an air conditioner control method capable of improving the accuracy of air supply strategy and optimizing the air supply effect.

[0006] A second object of the present application is to provide an air conditioner capable of improving the accuracy of air supply strategy and optimizing the air supply effect.

[0007] A third object of the present application is to provide a computer readable storage medium capable of improving the accuracy of air supply strategy and optimizing the air supply effect.

[0008] In order to achieve the above-mentioned first object, the air conditioner control method provided by the present application comprises: acquiring thermal data, user state data and air quality data of a current indoor space in real time; dividing the current indoor space into air supply level regions according to the thermal data, the user state data and the air quality data, and obtaining air supply level region data; acquiring a computational fluid dynamics simulation model database matched with the current indoor space; using a preset air supply strategy model to predict based on the computational fluid dynamics simulation model database according to the thermal data, the user state data, the air quality data and the air supply level region data, and generating a current air supply strategy; and controlling the air conditioner according to the current air supply strategy.

[0009] As can be seen from the above scheme, in the air conditioner control method of the present application, by collecting multi-dimensional data of thermal data, user state data and air quality data of the current indoor space, the indoor space is divided into areas of different air supply priority or intensity using multi-dimensional data, which can avoid invalid air supply of the air conditioner to unoccupied areas or low demand areas, and improve energy efficiency and comfort. At the same time, according to the spatial structure arrangement of the current indoor space, such as house type structure and furniture placement, the corresponding pre-built model in the database is called to ensure the accuracy of simulation prediction. By presetting the air supply strategy model, combining multi-dimensional data and computational fluid dynamics model for simulation prediction, the current air supply strategy is generated, which can improve the accuracy of air supply strategy, optimize the air supply effect, and meet the thermal sensation needs of different groups of people.

[0010] In a further scheme, the step of dividing the current indoor space into air supply level areas according to the thermal data, user state data and air quality data includes: dividing the current indoor space into grids of a preset size; determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data in each grid.

[0011] As can be seen, by dividing the current indoor space into grids and determining the air supply level according to the thermal data, user state data and air quality data in each grid, the accuracy of air supply in each area can be improved, and air supply can be targeted to high-level grids to reduce invalid energy consumption of low-level grids and improve energy efficiency.

[0012] In a further scheme, the step of determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data in each grid includes: if any two or more of the following conditions are met, the grid is marked as an air supply priority area: there is a human target in the grid; the difference between the body surface temperature of the human target and the indoor temperature is greater than a preset temperature; the human target is in a standing or moving posture; the air quality is outside the safe range.

[0013] As can be seen, if there is a human target in the grid, it means that the temperature demand of the human target needs to be considered. If the difference between the body surface temperature of the human target and the indoor temperature is greater than a preset temperature, it means that the human target needs to be adjusted. If the human target is in a standing or moving posture, it means that the human target is in a high energy consumption state and needs to be adjusted. If the air quality is outside the safe range, it means that the grid needs to be ventilated. Therefore, by using multiple conditions to determine the air supply priority area, the single condition can be avoided.

[0014] In a further aspect, the step of determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data of each grid further comprises: if any two or more of the following conditions are met, the grid is marked as an air supply maintaining area, and the priority level of the air supply maintaining area is lower than that of the air supply priority area: there is a human target in the grid; the difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range; the human target is in a sitting or lying posture; and the air quality is within a safe range.

[0015] As can be seen, the difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range, and the moderate temperature difference means that there is no need for strong cooling / heating, and only the current temperature state needs to be maintained. The user is in a low activity state such as a sitting or lying posture, and the human body produces less heat and is highly sensitive to airflow, so there is no need for strong cooling / heating. When the air quality is good, there is no need to adjust the air supply state. Therefore, according to the above conditions, the air supply maintaining area is determined, and the judgment accuracy is improved.

[0016] In a further aspect, the step of determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data of each grid further comprises: if any two or more of the following conditions are met, the grid is marked as an air supply maintaining area, and the priority level of the air supply maintaining area is lower than that of the air supply priority area: there is a human target in the grid; the difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range; the human target is in a sitting or lying posture; and the air quality is within a safe range.

[0017] As can be seen, the difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range, and the moderate temperature difference means that there is no need for strong cooling / heating, and only the current temperature state needs to be maintained. The user is in a low activity state such as a sitting or lying posture, and the human body produces less heat and is highly sensitive to airflow, so there is no need for strong cooling / heating. When the air quality is good, there is no need to adjust the air supply state. Therefore, according to the above conditions, the air supply maintaining area is determined, and the judgment accuracy is improved.

[0018] In a further aspect, the step of generating the current air supply strategy by using the preset air supply strategy model according to the thermal data, user state data, air quality data and air supply level area data based on the computational fluid dynamics simulation model database comprises: generating a plurality of initial air supply strategies by using the preset air supply strategy model according to the thermal data, user state data, air quality data and air supply level area data; matching corresponding air supply effects from the computational fluid dynamics simulation model database according to the plurality of initial air supply strategies; and selecting an air supply strategy with the optimal air supply effect from the plurality of initial air supply strategies as the current air supply strategy.

[0019] As can be seen, the preset air supply strategy model automatically generates multiple possible air supply parameter combinations based on input thermal data, user status, air quality, and air supply level zone data. Each initial strategy's air supply parameters are input into the model, and simulation calculations are performed to output the corresponding air supply effect data. The optimal air supply effect is then selected as the final strategy from the multiple initial strategies. By comparing multiple strategies, the final strategy ensures that it accurately covers high-demand areas, avoids discomfort risks in suppression zones or maintenance zones, and adapts to changes in the indoor environment in real time.

[0020] In a further solution, when the air conditioner is controlled according to the current air supply strategy, noise data during the operation of the air conditioner is obtained; and the noise data is stored as a parameter of the air supply effect of the current air supply strategy.

[0021] It can be seen that by obtaining and storing the noise data when the current air supply strategy is used to control the air conditioner, the noise data can be used to iterate the preset air supply strategy model and improve the accuracy of air supply strategy prediction.

[0022] In a further solution, after controlling the air conditioner according to the current air supply strategy, the method further includes: obtaining energy efficiency evaluation data of the current air supply strategy, and storing the energy efficiency evaluation data as a parameter of the air supply effect of the current air supply strategy.

[0023] It can be seen that obtaining the energy efficiency evaluation data of the current air supply strategy as a parameter of the air supply effect of the current air supply strategy can be used to optimize the preset air supply strategy model and improve the prediction accuracy of the air supply strategy.

[0024] In order to achieve the second object of the present invention, the present invention provides an air conditioner including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the above-mentioned air conditioning control method are implemented.

[0025] In order to achieve the third objective of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-mentioned air-conditioning control method when executed by a controller. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 4 is a flow chart of an embodiment of the air conditioning control method of the present invention.

[0027] Figure 2 This is a flow chart of the steps for dividing air supply level areas in an embodiment of the air conditioning control method of the present invention.

[0028] Figure 3 This is a flow chart of the steps for generating the current air supply strategy in an embodiment of the air conditioning control method of the present invention.

[0029] The present invention will be further described below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0030] The air conditioning control method of the present invention is an application program applied in an air conditioner, and is used to control the air supply of the air conditioner.

[0031] Air conditioning control method embodiment: like Figure 1 As shown, in this embodiment, the air conditioning control method, during operation, first executes step S1 to acquire real-time thermal data, user status data, and air quality data for the current indoor space. When the air conditioner is in cooling or heating mode, it can acquire real-time thermal data, user status data, and air quality data for the current indoor space. The air conditioner can be equipped with a millimeter-wave radar module, a thermal imaging array, an air quality sensor, and a temperature and humidity sensor. The radar module is used to identify human subjects in the room and their three-dimensional spatial coordinates. The thermal imaging array can extract thermal data such as the skin surface temperature of each human subject and the temperature of each indoor area to construct a spatial heat map. The air quality sensor can acquire air quality data for each area of ​​the indoor space.

[0032] After obtaining the thermal data, user status data, and air quality data for the current indoor space, step S2 is executed to divide the current indoor space into air supply level zones based on the thermal data, user status data, and air quality data, thereby obtaining air supply level zone data. This air supply level zone division based on the thermal data, user status data, and air quality data provides a spatial mapping reference for air supply strategies.

[0033] In this embodiment, see Figure 2 When dividing the current indoor space into air supply level zones based on thermal data, user status data, and air quality data to obtain air supply level zone data, step S11 is first executed to divide the current indoor space into grids of a preset size. The preset size can be pre-set based on experimental data, with a 0.5m×0.5m grid as the division size. Each grid cell is assigned a spatial coordinate number (i, j) and records the following attribute values: presence, user surface temperature, local ambient temperature, air quality, user motion status, etc. User motion status can be obtained by recognizing thermal images, a technique known to those skilled in the art and will not be elaborated upon here.

[0034] After dividing the current indoor space into grids of a preset size, step S12 is executed to determine the corresponding air supply level for each grid based on the thermal data, user status data, and air quality data in each grid. Dividing the current indoor space into grids and determining the air supply level based on the thermal data, user status data, and air quality data in each grid can improve the accuracy of air supply in each area, provide targeted air supply to high-level grids, reduce ineffective energy consumption in low-level grids, and improve energy efficiency.

[0035] In this embodiment, the step of determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data in each grid comprises: marking the grid as an air supply priority area if any two or more of the following conditions are met: there is a human target in the grid; the difference between the body surface temperature of the human target and the indoor temperature is greater than a preset temperature; the human target is in a standing or moving posture; and the air quality is outside the safe range. The preset temperature is set in advance according to experimental data, for example, the preset temperature is 2°C. The presence of a human target in the grid indicates that the temperature demand of the human target needs to be considered. The safe range of air quality can be determined according to the detection of air quality related parameters, for example, when the CO2 concentration exceeds 800 ppm or the TVOC concentration exceeds 0.4 ppm, it is considered that the air quality is outside the safe range. If the difference between the body surface temperature of the human target and the indoor temperature is greater than the preset temperature, it indicates that the human target needs to be temperature adjusted. If the human target is in a standing or moving posture, it indicates that the human target is in a high energy consumption state and needs to be adjusted. If the air quality is outside the safe range, it indicates that the grid needs to be ventilated. Therefore, the air supply priority area is determined by multiple conditions, which can avoid misjudgment of a single condition.

[0036] In this embodiment, the step of determining the air supply level corresponding to each grid according to the thermal data, user state data and air quality data in each grid further comprises: marking the grid as an air supply maintenance area if any two or more of the following conditions are met, and the priority level of the air supply maintenance area is lower than that of the air supply priority area: there is a human target in the grid; the difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range; the human target is in a sitting or lying posture; and the air quality is within the safe range. The preset temperature range can be set in advance according to experimental data, for example, the preset temperature range is -2°C to 2°C. If the difference between the body surface temperature of the human target and the indoor temperature is within the preset temperature range, the temperature difference is moderate, which means that strong cooling / heating is not needed and only the current temperature state needs to be maintained. When the user is in a low activity state such as a sitting or lying posture, the human body produces less heat and is highly sensitive to airflow, so strong cooling / heating is not needed. When the air quality is good, the air supply state does not need to be adjusted. Therefore, the air supply maintenance area is determined according to the above conditions, which improves the judgment accuracy.

[0037] In this embodiment, the step of determining the corresponding air supply level of each grid according to the thermal data, user state data and air quality data in each grid further comprises: if any two or more of the following conditions are met, the grid is marked as an air supply inhibition area, and the priority level of the air supply inhibition area is lower than that of the air supply maintenance area: there is no human target or the human target has left the grid for more than a preset time period; the temperature of the grid is stable and the temperature difference with adjacent grids is less than a preset temperature difference; the grid is set as a direct blowing prevention area. The preset time period and the preset temperature difference can be set in advance according to experimental data. The area without people does not need to be supplied with air for human comfort, and only basic adjustment is needed in extreme environment, and the air supply of the area with people is prioritized. The temperature of the grid is within the target range, and the temperature difference with the surrounding grids is small, indicating that the overall environment is uniform and stable, and no additional air supply intervention is needed. The user manually marks an area as a direct blowing prevention area through an APP or a physical button, and then the direct air supply of the area is limited.

[0038] After obtaining the air supply level area data, step S3 is performed to obtain a computational fluid dynamics (CFD) simulation model database matching the current indoor space. The computational fluid dynamics simulation model database can be pre-stored in the air conditioner. To build the computational fluid dynamics simulation model database, a three-dimensional space model can be established by a designer according to the layout structure of the indoor space (including air conditioner installation position, main furniture arrangement, wall boundary, etc.) during the installation or initialization stage of the air conditioning system. Computational fluid dynamics software (such as ANSYS Fluent) is used to simulate air flow for various combinations of air sweeping blade angles, air supply volume, and air type modes (central air supply or scattering air supply). Each simulation result output includes: wind speed vector field distribution, temperature field, air flow coverage area, air flow path trajectory diagram, and air supply effect. These simulation results are stored in the local database in the form of parameter and effect pairs, such as: control parameters: blade angle combination A + air volume configuration X + air type mode Y, corresponding air supply effect: coverage area, temperature change diagram, and noise estimate value. Finally, a computational fluid dynamics simulation model database of input control parameters and air flow effect mapping pairs is formed.

[0039] When obtaining the computational fluid dynamics simulation model database matching the current indoor space, since the layout of the current indoor space may change, the computational fluid dynamics simulation model data of a similar layout is obtained according to the current indoor space.

[0040] After obtaining the computational fluid dynamics (CFD) simulation model database, step S4 is executed, where a preset air supply strategy model is used to generate a current air supply strategy based on the thermal data, user status data, air quality data, and air supply level and area data. In this embodiment, the preset air supply strategy model is generated using reinforcement learning or model predictive control (MPC) methods. The air supply strategy generated based on the CFD simulation model database and the thermal data, user status data, air quality data, and air supply level and area data may include, for example, multiple sweep blade combinations, wind direction patterns, and air volume distribution schemes.

[0041] In this embodiment, see Figure 3 When generating the current air supply strategy, a preset air supply strategy model is used to predict the current air supply strategy based on thermal data, user status data, air quality data, and air supply level and area data using a computational fluid dynamics simulation model database. Step S21 is first executed to generate multiple sets of initial air supply strategies using the preset air supply strategy model based on the thermal data, user status data, air quality data, and air supply level and area data. The preset air supply strategy model automatically generates multiple possible air supply parameter combinations based on the input thermal data, user status data, air quality data, and air supply level and area data. Each initial air supply strategy includes core air conditioning control parameters, such as wind speed (high, medium, or low); wind direction (horizontal and vertical swing angles, such as 30° upward and 60° right); set temperature (such as 24°C, 25°C, and 26°C); and fresh air percentage (such as 20% and 50%, depending on air quality requirements). Differentiated parameter combinations are performed based on regional level differences. For example, for the air supply priority zone, the initial strategy may include "high wind speed + precise directional air supply + low set temperature"; for the air supply suppression zone, the initial strategy may include "low wind speed + non-directional air supply + high set temperature". The differences between multiple groups of strategies are reflected in subtle adjustments to the parameter combination (such as wind speed level difference and angle deviation), thereby forming an alternative pool, for example, generating 5 to 10 groups of initial strategies.

[0042] In a specific example, the input parameters of the preset air supply strategy model include: current user position coordinates; body surface temperature and thermal sensation state of each user; temperature distribution and air quality of each space grid; air duct structure characteristics (such as air outlet passage resistance, air flow path); current air speed and air pressure at the air outlet; current system operating state (including air volume range, motor speed limit, noise level); past several times of strategy execution effect data (such as temperature change trend, noise response, user score) and the like. The preset air supply strategy model calculates the air supply strategy according to the model predictive control (MPC) or reinforcement learning strategy, and the air supply strategy includes control parameters such as air supply wind type mode and air volume distribution ratio, target angle value of the air sweeping blade, which is used to construct the air supply direction structure. The air supply wind type mode is used to determine the wind type control (such as directional concentrated wind or soft scattered wind). The air volume distribution ratio coefficient is used for air volume adjustment and total air pressure distribution between multiple air supply paths.

[0043] After generating the multiple sets of initial air supply strategies, step S22 is performed to match corresponding air supply effects from the computational fluid dynamics simulation model database according to the multiple sets of initial air supply strategies. The air supply parameters of each set of initial strategy are matched with the computational fluid dynamics simulation model database, and corresponding air supply effect data are output. The parameters of the initial strategy are input into the model, simulation calculation is performed, and corresponding air supply effect data are output. The air supply effect data include: air flow effect: wind speed of each grid, air flow uniformity (avoiding local vortex or dead angle); temperature effect: temperature compliance time of the priority zone / holding zone (such as whether the priority zone needs 5 minutes or 8 minutes to reduce from 30°C to 26°C); comfort effect: whether there are uncomfortable scenes such as “directly blowing on the user” and “temperature sudden change”; energy consumption effect: estimated energy consumption (such as power consumption, running time and the like) of the air conditioner under the strategy.

[0044] After obtaining the air supply effect data corresponding to the multiple sets of initial air supply strategies, step S23 is performed to select one with the optimal air supply effect from the multiple sets of initial air supply strategies as the current air supply strategy according to the air supply effect. The judgment standard of the optimal air supply effect can be set as needed, for example: priority zone coverage: whether the air flow can accurately reach all high-priority grids (such as the wind speed of the user area meeting the standard); air flow uniformity: small difference in wind speed or temperature in the same area (such as the temperature difference of each grid in the priority zone being less than 1°C); no uncomfortable scene: avoiding problems such as directly blowing on the suppression zone, high wind speed in the holding zone, and slow temperature reduction in the priority zone; energy efficiency balance: on the premise of meeting the above conditions, the energy consumption is as low as possible (such as selecting a strategy with lower power under the same effect). The optimal air supply strategy can be determined by comparing the comprehensive scores of multiple candidate strategies under the conditions of “maximum air supply coverage”, “maximum user comfort”, “minimum system energy consumption”, “noise lower than the threshold” and the like through a preset scoring system.

[0045] After the current air supply strategy is generated, step S5 is performed to control the air conditioner according to the current air supply strategy. According to the generated current air supply strategy, instructions are directly sent to the fan, compressor, air sweeping plate, fresh air valve and other components of the air conditioner to achieve dynamic control. At the same time, the process can be real-time cycled, such as repeating data collection and strategy updating every 1-5 minutes to ensure adaptation to changes in the environment and user state.

[0046] In this embodiment, when the air conditioner is controlled according to the current air supply strategy, noise data during air conditioner operation is obtained; the noise data is stored as a parameter of the air supply effect of the current air supply strategy. The noise data is strongly related to the current air supply strategy, so it needs to be collected synchronously during strategy execution. The noise data during air conditioner operation is collected in real time by the noise sensor (such as a microphone) built in the air conditioner or the acoustic sensor arranged indoors, and the noise data includes: noise intensity, noise frequency and noise change trend. By obtaining the noise signal when the air conditioner is controlled according to the current air supply strategy and storing it, the noise data can be used to iterate the preset air supply strategy model to improve the prediction accuracy of the air supply strategy.

[0047] In this embodiment, after the air conditioner is controlled according to the current air supply strategy, it further includes: obtaining energy efficiency evaluation data of the current air supply strategy, and storing the energy efficiency evaluation data as a parameter of the air supply effect of the current air supply strategy. The energy efficiency evaluation data is a quantitative indicator of the running efficiency of the air conditioner under the current air supply strategy, mainly including: direct energy consumption data: power of the air conditioner running (such as 1.2 kW), cumulative power consumption (such as 1.2 degrees of power consumption for 1 hour of operation), running time (such as 20 minutes of strategy execution); energy efficiency ratio (EER / COP): the ratio of refrigerating capacity (or heating capacity) to power consumption (such as refrigerating capacity 3000W / power consumption 1000W=3.0), the higher the ratio, the better the energy efficiency; energy consumption effectiveness: the "effectiveness rate" under unit energy consumption (such as consuming 0.5 degrees of electricity to reduce the temperature in the priority area by 4℃, which is better than the strategy of consuming 1 degree of electricity to reduce the temperature by 5℃). The energy efficiency data is calculated and output in real time by the power sensor, compressor and fan operation parameter collection module built in the air conditioner, and is accurately bound with the execution period of the current air supply strategy. By obtaining the energy efficiency evaluation data of the current air supply strategy as a parameter of the air supply effect of the current air supply strategy, it can be used to optimize the preset air supply strategy model and provide decision basis for energy efficiency dimension for subsequent strategy screening, for example, in two strategies with similar comfort levels, the "higher energy efficiency" solution is preferred, to improve the prediction accuracy of the air supply strategy.

[0048] From the above, in the air conditioner control method, the indoor space is divided into different air supply priority or intensity regions by using multi-dimensional data of thermal data, user state data and air quality data of the current indoor space, which can avoid invalid air supply of the air conditioner to unoccupied areas or low demand areas, and improve energy efficiency and comfort. At the same time, according to the spatial structure arrangement of the current indoor space, such as the house type structure and furniture arrangement, the corresponding pre-built model in the database is called to ensure the accuracy of simulation prediction. The current air supply strategy is generated by simulating and predicting the preset air supply strategy model combined with multi-dimensional data and computational fluid dynamics model, which can improve the accuracy of air supply strategy, optimize the air supply effect, and meet the thermal sensation needs of different groups of people.

[0049] The air conditioner embodiment includes a controller, and the controller implements the steps in the air conditioner control method embodiment when executing a computer program. The air conditioner of the embodiment includes a controller, and the controller implements the steps in the air conditioner control method embodiment when executing a computer program.

[0050] For example, the computer program can be divided into one or more modules, and the one or more modules are stored in the memory and executed by the controller to complete the present application. One or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the air conditioner.

[0051] The air conditioner can include, but is not limited to, a controller, a memory. Those skilled in the art can understand that the air conditioner can include more or fewer components, or combine certain components, or different components, for example, the air conditioner can also include an input / output device, a network access device, a bus, etc.

[0052] For example, the controller can be a central processing unit (CPU), and can also be other general-purpose controllers, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose controller can be a microcontroller, or the controller can also be any conventional controller, etc. The controller is the control center of the air conditioner, and connects all parts of the air conditioner through various interfaces and lines.

[0053] The memory can be used to store computer programs and / or modules. The controller implements various functions of the air conditioner by running or executing the computer programs and / or modules stored in the memory and accessing data stored in the memory. For example, the memory may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (e.g., a voice reception function, a voice-to-text function, etc.); the data storage area may store data generated based on the use of the mobile phone (e.g., audio data, text data, etc.). Furthermore, the memory may include high-speed random access memory (RAM) and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a SmartMediaCard (SMC), a Secure Digital (SD) card, a flash memory card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0054] Computer readable storage medium embodiment: If the air conditioner integrated module of the above-mentioned embodiment is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the process described in the above-mentioned air conditioning control method embodiment can also be implemented by a computer program instructing the relevant hardware. The computer program can be stored in a computer-readable storage medium. When executed by a controller, the computer program can implement the steps of the above-mentioned air conditioning control method embodiment. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Storage media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content of the computer-readable medium can be appropriately expanded or reduced based on the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, legislation and patent practice do not require that computer-readable media include electric carrier signals and telecommunications signals.

[0055] It should be noted that the above are only preferred embodiments of the present invention, but the design concept of the invention is not limited thereto. Any non-substantial modifications made to the present invention using this concept also fall within the scope of protection of the present invention.

Claims

1. An air conditioning control method, characterized in that: include: Real-time acquisition of thermal data, user status data, and air quality data for the current indoor space; Dividing the current indoor space into air supply level zones according to the thermal data, the user status data, and the air quality data to obtain air supply level zone data; Acquiring a computational fluid dynamics simulation model database matching the current indoor space; Using a preset air supply strategy model to make predictions based on the computational fluid dynamics simulation model database according to the thermal data, the user status data, the air quality data, and the air supply level area data, to generate a current air supply strategy; The air conditioner is controlled according to the current air supply strategy.

2. The air conditioning control method according to claim 1, wherein: The step of dividing the current indoor space into air supply level zones according to the thermal data, the user status data, and the air quality data, and obtaining the air supply level zone data comprises: Dividing the current indoor space into grids of a preset size; The air supply level corresponding to each grid is determined according to the thermal data, the user status data and the air quality data in each grid.

3. The air conditioning control method according to claim 2, wherein: The step of determining the air supply level corresponding to each grid according to the thermal data, the user status data and the air quality data in each grid comprises: If any two or more of the following conditions are met, the grid is marked as an air supply priority area: There are human targets in the grid; The difference between the body surface temperature of the human target and the indoor temperature is greater than a preset temperature; The human target is in a standing, moving posture; The air quality is outside the safe range.

4. The air conditioning control method according to claim 3, wherein: The step of determining the air supply level corresponding to each grid according to the thermal data, the user status data and the air quality data in each grid further includes: If any two or more of the following conditions are met, the grid is marked as an air supply holding zone, and the priority of the air supply holding zone is lower than that of the air supply priority zone: There is a human target in the grid; The difference between the body surface temperature of the human target and the indoor temperature is within a preset temperature range; The human target is in a sitting or lying position; The air quality is within the safe range.

5. The air conditioning control method according to claim 4, characterized in that: The step of determining the air supply level corresponding to each grid according to the thermal data, the user status data and the air quality data in each grid further includes: If any two or more of the following conditions are met, the grid is marked as an air supply suppression zone, and the priority of the air supply suppression zone is lower than that of the air supply maintenance zone: There is no human target in the grid or the human target has been away for more than a preset time; The temperature of the grid is stable and the temperature difference between the grid and the adjacent grid is less than a preset temperature difference; The grid is configured as a direct blow prevention area.

6. The air conditioning control method according to any one of claims 1 to 5, characterized in that: The step of using a preset air supply strategy model to predict based on the thermal data, the user status data, the air quality data, and the air supply level area data based on the computational fluid dynamics simulation model database to generate a current air supply strategy includes: Generate multiple sets of initial air supply strategies based on the thermal data, the user status data, the air quality data, and the air supply level area data using a preset air supply strategy model; Matching corresponding air supply effects from the computational fluid dynamics simulation model database according to the multiple groups of initial air supply strategies; According to the air supply effect, an air supply strategy with the best air supply effect is selected from multiple groups of the initial air supply strategies as the current air supply strategy.

7. The air conditioning control method according to claim 6, wherein: When the air conditioner is controlled according to the current air supply strategy, noise data of the air conditioner during operation is obtained; The noise data is stored as a parameter of the air supply effect of the current air supply strategy.

8. The air conditioning control method according to claim 6, wherein: After the air conditioner is controlled according to the current air supply strategy, the method further includes: Energy efficiency evaluation data of the current air supply strategy is acquired, and the energy efficiency evaluation data is stored as a parameter of the air supply effect of the current air supply strategy.

9. An air conditioner comprising a processor and a memory, characterized in that: The memory stores a computer program, and when the computer program is executed by the processor, the steps of the air conditioning control method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the controller, the steps of the air conditioning control method according to any one of claims 1 to 8 are implemented.

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