Air conditioner control method, device and system and air conditioner

Abstract

The invention discloses an air conditioner control method, device and system and an air conditioner, and belongs to the field of air conditioner control. When a preset condition is triggered, executing a target control strategy; generating a plurality of different compressor frequencies; obtaining a target compressor frequency based on a differential evolution algorithm; and controlling the frequency of the compressor to be the target compressor frequency. According to the scheme, the compressor frequency is used as an optimization variable, the differential optimization algorithm is adopted for global search, and the future temperature stability index and the energy consumption index are adopted for optimization, so that the obtained target compressor frequency can solve the problems that energy consumption and stability are difficult to consider, and temperature overshoot or large energy consumption often occurs due to response characteristics of traditional PID; and the air conditioner can automatically find a more energy-saving and more stable working point in a dynamic environment.

Description

Technical Field

[0001] This application relates to the field of air conditioning control technology, and in particular, to an air conditioning control method, apparatus and system, and air conditioner. Background Technology

[0002] Inverter air conditioners are conventional air conditioners equipped with inverters. Their basic structure and refrigeration principle are the same as ordinary air conditioners. The core difference lies in the use of inverter technology to adjust the compressor speed. As the core component, the compressor adjusts the power supply frequency in real time through the inverter to achieve stepless speed regulation. It can dynamically match the cooling / heating capacity according to the indoor load demand, and maintain constant temperature operation at low speed after reaching the set temperature. Compared with fixed-frequency air conditioners, it saves at least 30% energy.

[0003] With the widespread adoption of inverter air conditioners, compressor frequency regulation has become a key control method for improving indoor comfort and energy efficiency. Currently, the industry commonly employs PID control, fuzzy control, or rule-based regulation strategies to adjust compressor output in real time according to indoor temperature deviations. However, due to the large thermal inertia of rooms, complex load changes, and significant impact of wall heat storage, the response characteristics of traditional PID control struggle to balance energy consumption and stability, often resulting in temperature overshoot or excessive energy consumption. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, this application provides an air conditioning control method, device and system and air conditioner to solve the problem that due to the large thermal inertia of the room, the complex load changes and the significant impact of wall heat storage, the response characteristics of traditional PID are difficult to balance energy consumption and stability, and often result in temperature overshoot or high energy consumption.

[0005] The technical solution adopted by this application to solve its technical problem is: Firstly, an air conditioning control method is provided, including: When a preset condition is triggered, a target control strategy is executed, which includes: Generate multiple different compressor frequencies; The compressor frequency is processed by the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index to represent the future temperature stability level and an energy consumption index to represent the future energy consumption level. The compressor frequency is controlled to the target compressor frequency.

[0006] As an optional implementation of this application, the step of determining the candidate compressor frequency for the next generation based on the target index at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

[0007] As an optional implementation of this application, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

[0008] As an optional implementation of this application, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

[0009] As an optional implementation of this application, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

[0010] As an optional implementation of this application, it also includes: The preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

[0011] As an optional implementation of this application, it also includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value; Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein the first preset temperature difference is greater than or equal to the second preset temperature difference; Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value of .

[0012] As an optional implementation of this application, it also includes: When the compressor starts, a preset condition is triggered; Alternatively, a preset condition may be triggered when the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than a third preset temperature difference.

[0013] Secondly, an air conditioning control device is provided, comprising: Execution unit: When a preset condition is triggered, the target control strategy is executed. The execution unit includes: The compressor frequency generation module is used to generate multiple different compressor frequencies; The target frequency acquisition module is used to process the compressor frequency based on the differential evolution algorithm to obtain candidate compressor frequencies, and to determine the candidate compressor frequency to enter the next generation based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index for representing the future temperature stability and an energy consumption index for representing the future energy consumption level. The compressor frequency control module is used to control the compressor frequency to the target compressor frequency.

[0014] Thirdly, an air conditioning control system is provided, comprising: At least one processor and at least one memory; The memory stores the executable instructions of the processor; The processor is configured to perform any of the above-described air conditioning control methods.

[0015] Fourthly, an air conditioner is provided that applies the air conditioning control method described in any of the above-mentioned claims.

[0016] Beneficial effects: This application provides an air conditioning control method, device, system, and air conditioner. When a preset condition is triggered, a target control strategy is executed. This execution includes: generating multiple different compressor frequencies; processing the compressor frequencies using a differential evolution algorithm to obtain candidate compressor frequencies; and determining the next generation of candidate compressor frequencies based on target indicators for each candidate compressor frequency, until a target compressor frequency is obtained. The target indicators include a future temperature stability indicator representing the future temperature stability level and an energy consumption indicator representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. This application uses compressor frequency as the optimization variable and employs a differential optimization algorithm for global search. Because it uses future temperature stability and energy consumption indicators for optimization, the obtained target compressor frequency can solve the problem that traditional PID control often struggles to balance energy consumption and stability, frequently resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an air conditioning control method provided in an embodiment of this application; Figure 2 This is a flowchart of a specific air conditioning control method provided in an embodiment of this application; Figure 3 This is a flowchart of another specific air conditioning control method provided in the embodiments of this application; Figure 4 This is a flowchart of an overall solution provided in an embodiment of this application; Figure 5 This is a schematic diagram of an air conditioning control device provided in an embodiment of this application; Figure 6 This is a schematic diagram of an air conditioning control system provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be described in detail below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] With the development of algorithms, computing power, mechanisms, and data models, the air conditioning industry is gradually trying more intelligent control methods, such as model predictive control (MPC) and data-driven control. However, MPC relies on explicit models, and the modeling and solving complexity is high, making it difficult to run in real time on economical controllers. Although black-box control based on machine learning improves predictive capabilities, it still lacks global optimization capabilities that directly address the goal of "minimum energy consumption + most stable temperature".

[0021] Differential evolution algorithm is a simple, robust, and easily parallelizable global optimization method. It is stable in nonlinear, multimodal, and dynamically constrained problems and does not require model continuity or differentiability. Therefore, it is very suitable for air conditioning systems that are "strongly coupled, nonlinear, and combine prediction and control".

[0022] For example, existing technology provides an energy-saving optimization system for an air conditioning system, comprising: Data processing module: used to obtain the dataset required for air conditioning load forecasting; Preprocess the dataset; Modeling module: Used to build an air conditioning load forecasting model and determine the air conditioning load; based on the air conditioning load forecasting results, construct... Build an air conditioning energy consumption model; Optimization module: Used to optimize equipment parameters with the objective function of minimizing total energy consumption in the air conditioning energy consumption model.

[0023] This solution addresses the challenges of air conditioning load forecasting, air conditioning system energy consumption modeling, and optimized control of air conditioning system equipment operating parameters. Assuming the air conditioning system can intelligently collect data and that pumps and water towers have or are equipped with variable frequency control systems, a method and system for energy-saving optimization of the air conditioning system are proposed. This method utilizes big data algorithms to predict air conditioning load and determine cooling demand in advance. The input features and prediction results of the air conditioning load forecasting model are then used as inputs to establish a nonlinear, random forest-based air conditioning energy consumption model. Simultaneously, an adaptive differential evolution method with global optimization capabilities is employed to optimize equipment parameters, ultimately forming an intelligent analysis and decision-making optimization control method for the air conditioning system, achieving energy-saving optimization.

[0024] However, the above solution optimizes air conditioning energy consumption, resulting in equipment parameters under optimal energy conditions. This may not meet actual needs.

[0025] Based on this, this application introduces the differential evolution algorithm into the online frequency regulation of the air conditioner compressor, and combines it with room temperature prediction and energy consumption prediction models. Using each control cycle as an optimization window, it automatically searches for the compressor frequency with the lowest future energy consumption while ensuring temperature stability. This provides a more direct and intelligent strategy for air conditioner control than PID control. This method can significantly improve control performance without increasing hardware costs and has clear industrial application value.

[0026] To solve this problem, refer to Figure 1 This application provides an air conditioning control method, including: When a preset condition is triggered, a target control strategy is executed, which includes: S11: Generates multiple different compressor frequencies; S12: The compressor frequency is processed based on the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index for representing the future temperature stability level and an energy consumption index for representing the future energy consumption level. It should be noted that in this embodiment, the future temperature refers to the temperature within a specified time period from the current time, or the temperature of the next control cycle.

[0027] S13: Control the compressor frequency to the target compressor frequency.

[0028] Example 1: like Figure 2 As shown: When the compressor starts, a preset condition is triggered, and a target control strategy is executed. The execution of the target control strategy includes: Generate multiple different compressor frequencies; The compressor frequency is processed by the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index to represent the future temperature stability level and an energy consumption index to represent the future energy consumption level. The compressor frequency is controlled to the target compressor frequency.

[0029] The step of determining the candidate compressor frequency for the next generation based on target indicators at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

[0030] In one embodiment, determining the comprehensive evaluation result of the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

[0031] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability and energy consumption indicators can enable the air conditioner to have the advantages of good temperature stability and low energy consumption.

[0032] In another embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

[0033] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability indicators, energy consumption indicators, and frequency change stability indicators can enable air conditioning control to have the advantages of good temperature stability, low energy consumption, and relatively stable subsequent control frequency changes.

[0034] In the third embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

[0035] Furthermore, the preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

[0036] Understandably, the penalty terms imposed by adding start-stop and reliability constraints, as well as comfort boundary constraints, can ensure that air conditioning control possesses advantages such as good temperature stability, low energy consumption, and relatively smooth subsequent control frequency changes, while also taking into account user comfort and operational reliability. This greatly improves the user experience.

[0037] In one alternative implementation, All are preset fixed values.

[0038] As a preferred implementation of the embodiments of this application, it further includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value can be increased by simply increasing a preset fixed value, or the increase can be determined based on the absolute value of the temperature difference between the indoor temperature and the set temperature and the rate of change of the indoor temperature. The larger the absolute value of the temperature difference between the indoor temperature and the set temperature or the greater the rate of change of the indoor temperature, the larger the increase value.

[0039] Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein the first preset temperature difference is greater than or equal to the second preset temperature difference; it is possible to increase only the preset fixed value, or to determine the increase value based on the absolute value of the temperature difference between the indoor temperature and the set temperature. The smaller the absolute value of the temperature difference between the indoor temperature and the set temperature, the greater the increase value.

[0040] Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value can be increased by either a preset fixed value or by determining the increase based on the number of compressor frequency adjustments within a preset time period. The more times the compressor frequency is adjusted within the preset time period, the greater the increase.

[0041] That is, in the embodiments of this application, It can be changed based on different situations. The value of .

[0042] Example 2: like Figure 3 As shown: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than a third preset temperature difference, a preset condition is triggered, and a target control strategy is executed. The execution of the target control strategy includes: Generate multiple different compressor frequencies; The compressor frequency is processed by the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index to represent the future temperature stability level and an energy consumption index to represent the future energy consumption level. The compressor frequency is controlled to the target compressor frequency.

[0043] Furthermore, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than or equal to a third preset temperature difference, the target compressor frequency is adjusted based on a traditional PID control scheme. The specific scheme is a commonly used technique in this field and will not be detailed here.

[0044] The step of determining the candidate compressor frequency for the next generation based on target indicators at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

[0045] In one embodiment, determining the comprehensive evaluation result of the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

[0046] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability and energy consumption indicators can enable the air conditioner to have the advantages of good temperature stability and low energy consumption.

[0047] In another embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

[0048] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability indicators, energy consumption indicators, and frequency change stability indicators can enable air conditioning control to have the advantages of good temperature stability, low energy consumption, and relatively stable subsequent control frequency changes.

[0049] In the third embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

[0050] Furthermore, the preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

[0051] Understandably, the penalty terms imposed by adding start-stop and reliability constraints, as well as comfort boundary constraints, can ensure that air conditioning control possesses advantages such as good temperature stability, low energy consumption, and relatively smooth subsequent control frequency changes, while also taking into account user comfort and operational reliability. This greatly improves the user experience.

[0052] In one alternative implementation, All are preset fixed values.

[0053] As a preferred implementation of the embodiments of this application, it further includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value can be increased by simply increasing a preset fixed value, or the increase can be determined based on the absolute value of the temperature difference between the indoor temperature and the set temperature and the rate of change of the indoor temperature. The larger the absolute value of the temperature difference between the indoor temperature and the set temperature or the greater the rate of change of the indoor temperature, the larger the increase value.

[0054] Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein, the first preset temperature difference is greater than or equal to the second preset temperature difference, and the second preset temperature difference is greater than the third preset temperature difference; it is possible to increase only the preset fixed value, or to determine the increase value based on the absolute value of the temperature difference between the indoor temperature and the set temperature, the smaller the absolute value of the temperature difference between the indoor temperature and the set temperature, the greater the increase value.

[0055] Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value can be increased by either a preset fixed value or by determining the increase based on the number of compressor frequency adjustments within a preset time period. The more times the compressor frequency is adjusted within the preset time period, the greater the increase.

[0056] That is, in the embodiments of this application, It can be changed based on different situations. The value of .

[0057] It should be noted that any process or method description in the flowchart or otherwise described herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, as should be understood by those skilled in the art to which the embodiments of this application pertain.

[0058] Furthermore, in the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0059] The air conditioning control method provided in this application executes a target control strategy when a preset condition is triggered. Executing the target control strategy includes: generating multiple different compressor frequencies; processing the compressor frequencies using a differential evolution algorithm to obtain candidate compressor frequencies; determining the next generation of candidate compressor frequencies based on target indicators for each candidate compressor frequency, until a target compressor frequency is obtained. The target indicators include a future temperature stability indicator representing the future temperature stability level and an energy consumption indicator representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. This application's solution uses compressor frequency as the optimization variable and employs a differential optimization algorithm for global search. Because it uses future temperature stability and energy consumption indicators for optimization, the obtained target compressor frequency can solve the problem that traditional PID response characteristics often fail to balance energy consumption and stability, frequently resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment.

[0060] To more clearly illustrate the solution proposed in this application, a specific implementation method is provided as follows: (1) Equipment composition and main functions of each module The embodiments of this application mainly include the following modules: 1. Environmental Parameter Acquisition Module: Responsible for collecting data such as indoor temperature, set temperature, humidity, outdoor temperature, current compressor frequency, fan status, and possibly wall temperature and personnel activity.

[0061] 2. Temperature Prediction Module: Predicts the room temperature change trend over a short period (e.g., 5-10 minutes) based on current environmental data and historical conditions. Statistical models, thermophysical models, or machine learning models can be used.

[0062] 3. Energy Consumption Prediction Module: Predicts future energy consumption levels based on candidate compressor frequencies. Power prediction models can be used, such as learning models based on features like current, voltage, and load.

[0063] 4. Differential Evolution Optimization Module: The core of the system, responsible for generating several candidate compressor frequencies in each control cycle, forming an evolutionary process through genetic mutation, crossover, selection and other operations, and evaluating them in conjunction with a prediction model.

[0064] 5. Execution Module: Receives the optimal frequency output from the optimization module and sends it to the air conditioner compressor to achieve real-time frequency adjustment.

[0065] 6. System Feedback Module: Collects the actual operating status of the air conditioner to form a closed-loop control, providing real input for optimization in the next cycle.

[0066] (2) Overall Solution Process like Figure 4 As shown: When the system starts up or enters a certain control cycle, it first collects the current operating status of the air conditioner and indoor and outdoor environmental data, and inputs them into the temperature prediction model and energy consumption prediction model. The differential evolution algorithm then generates multiple candidate compressor frequencies, each frequency representing a possible future control strategy. The prediction model simulates each candidate to obtain its future temperature stability and energy consumption performance. The optimization module selects the candidate frequency with the best overall performance based on the target preference (such as energy consumption priority or comfort priority) and sends it to the compressor for execution. The system continues this process in the next cycle to achieve real-time online optimization.

[0067] (3) Detailed technical implementation process Data Acquisition and Preprocessing The system first acquires real-time data on the air conditioning operating environment and equipment status through a data acquisition module. This includes indoor temperature, humidity, air conditioning set temperature, compressor current frequency, fan speed, outdoor temperature, and factors that may affect the room's heat load (such as human activity or external thermal disturbances). This data undergoes unified preprocessing before entering the control algorithm, including signal denoising, missing value handling, and data normalization, to meet the input consistency requirements of the prediction model and optimization module. This process ensures that data from various sensors can be stably and reliably input into subsequent algorithm processing stages.

[0068] Temperature prediction and energy consumption prediction models The system integrates a temperature and energy consumption prediction model to estimate short-term room temperature trends and corresponding energy consumption. Since this approach does not rely on the differentiability and continuity of the model, any type of black-box prediction model can be used, such as empirical regression models, air conditioning mechanism models, tree-based machine learning models, or neural network models. The prediction model's input consists of current environmental parameters and candidate compressor frequencies, while the output includes the future direction of room temperature and energy consumption levels. The prediction results directly serve as the basis for evaluating the merits of candidate solutions in the optimization algorithm, enabling the selection of compressor frequencies to be forward-looking.

[0069] Differential Evolutionary Optimization Process Within each air conditioning control cycle, the differential evolution module initiates a new round of optimization based on current environmental data. The system first generates an initial set of candidate schemes covering different compressor frequencies, serving as the search population to be optimized. Subsequently, differential evolution constructs new frequency values ​​through the differential relationships between different candidates in the population, achieving random perturbation of the search space and thus enabling it to escape local optima. The newly generated frequencies are combined with the original candidates, allowing the search space to continuously expand. Each candidate frequency is fed into a prediction model to evaluate its future temperature stability, energy consumption level, frequency change smoothness, and whether it meets equipment operating constraints. The system determines the merits of the candidates based on the evaluation results; candidates with better evaluations are retained and enter the next generation, while those with poor performance are eliminated. Through continuous iterative updates, the algorithm gradually improves the overall quality of the candidate population and outputs the final optimal compressor frequency after reaching a set number of rounds or time limits, ensuring that each cycle achieves a better decision based on local operating conditions.

[0070] Optimization goals and constraints considerations The optimization goal of this scheme is not simply to minimize temperature error, but rather to comprehensively consider multiple performance factors. When evaluating candidate schemes, the system comprehensively considers multiple indicators such as future temperature stability, energy consumption level, smoothness of frequency changes, compressor start-stop risk, and comfort boundaries. Start-up and reliability constraints, set The minimum continuous operating frequency of the compressor is Start-stop risk range is When the candidate compressor frequency meets: If this frequency is considered to pose a start-stop risk, then this indicator is used to prevent the compressor from frequently entering and stopping states in the low-frequency range, thereby improving system reliability and service life.

[0071] Comfort boundary constraint index, assuming the comfort temperature range is: If there exists any prediction time that satisfies: or The candidate compressor frequency is then determined to be insufficient to meet comfort requirements.

[0072] Comprehensive evaluation and optimal frequency selection Ultimately, the frequency of each candidate compressor This corresponds to a comprehensive evaluation result: in: Weighting coefficients Penalty refers to constraints and penalties such as start-stop risk and exceeding comfort limits. The differential evolution algorithm aims to minimize the overall evaluation result and searches for the globally optimal compressor frequency.

[0073] It should be noted that in this invention, the weight parameters in the comprehensive evaluation function are not fixed, but dynamically adjusted according to the operating status, environmental conditions, and control stage of the air conditioning system to improve the adaptability and practicality of the control strategy under different operating conditions. Specifically, the system pre-sets basic weight values ​​for the temperature stability index, energy consumption index, and frequency change stability index. During actual operation, the weight adjustment module adaptively corrects the above basic weights based on real-time operating parameters. The operating parameters include, but are not limited to: the deviation between the current room temperature and the set temperature, the rate of room temperature change, changes in environmental heat load, the continuous operating time of the air conditioner, and the current control stage. When a large deviation between the room temperature and the set temperature is detected, or when the system is in a rapid cooling phase, the system automatically increases the weight corresponding to the temperature stability index, making the optimization process more focused on rapidly and stably approaching the target temperature; when the room temperature approaches the set value and enters the constant temperature operation phase, the system correspondingly increases the weight of the energy consumption index, guiding the differential evolution algorithm to prioritize the compressor frequency with lower energy consumption; when frequent compressor frequency adjustments are detected, the system increases the weight of the frequency change stability index to suppress drastic adjustments.

[0074] The penalty term is used to adversely affect the candidate compressor frequency that does not meet the constraints. When the candidate compressor frequency meets all the constraints, the penalty term takes a zero value or a minimum value. When there is a risk of start-stop or a risk of exceeding the comfort limit, the penalty term takes a non-zero value to reduce the overall evaluation result of the candidate compressor frequency.

[0075] This application's solution enables the optimization process to achieve a balance between comfort, energy efficiency, and equipment reliability. By combining these objectives into a comprehensive evaluation result, the differential evolution algorithm can automatically weigh the trade-offs among the objectives and search for the optimal compressor frequency strategy globally, achieving a control effect that better meets actual needs.

[0076] Control execution and feedback After each optimization cycle, the system sends the optimal compressor frequency obtained through differential evolution to the execution module, which then directly adjusts the compressor's operating status via the air conditioning main control unit. Subsequently, new data generated by the actual operation of the air conditioner (such as real-time temperature changes and energy consumption feedback) enters the data acquisition phase of the next cycle, forming a continuous closed-loop feedback process. This structure enables the system to adapt to various dynamic operating conditions. Whether it's people suddenly entering the room, thermal disturbance caused by opening doors and windows, or load fluctuations due to changes in external sunlight, the system can maintain stable operation thanks to the forward-looking planning capabilities of differential evolution optimization and predictive models, achieving faster and more energy-efficient dynamic comfort control.

[0077] (4) Actual operation process of air conditioning application scenarios In summer cooling scenarios, after the air conditioner is turned on, the system first detects the deviation between the room temperature and the set temperature. When the room temperature is high, it automatically initiates a differential evolutionary optimization process to find a suitable compressor frequency. During this stage, the algorithm generates multiple candidate frequencies and calls a predictive model to evaluate the rate of temperature decrease and energy consumption performance in the near future. If the room is under high heat load (e.g., strong sunlight), the system tends to choose a higher frequency to accelerate cooling. As the temperature gradually approaches the set value, the predictive model may determine that high-frequency operation will cause temperature overshoot, thus lowering its score. The differential evolutionary algorithm then prioritizes a more stable low-to-medium frequency scheme. Once the temperature reaches a constant level, the system continuously optimizes to maintain the lowest energy consumption operating frequency, preventing the compressor from oscillating back and forth at low frequencies like in traditional PID control. When someone enters the room or a new thermal disturbance occurs, the algorithm immediately re-executes the optimization based on the latest data to obtain the optimal frequency for the current environment. The entire process requires no manual intervention. The system completes frequency search, evaluation, and execution through the collaborative operation of the predictive model and the differential evolutionary algorithm, achieving adaptive, efficient, and stable cooling control.

[0078] It should be noted that the embodiments of this application do not continuously perform differential evolution optimization in all stages of air conditioning operation, but rather adaptively initiate the optimization process when there is a significant adjustment need in the system. This is based on the following technical considerations: When the deviation between the indoor temperature and the set temperature is large, the air conditioning system is in the forced cooling or rapid response stage. At this time, the selection of the compressor frequency has a decisive impact on the cooling speed, energy consumption level, and subsequent temperature stability. If a fixed strategy or traditional PID method is still used, it is easy to cause problems such as high energy consumption or subsequent temperature overshoot. Therefore, initiating the differential evolution optimization process when a large deviation between the room temperature and the set temperature can give full play to the advantages of the predictive model and the global optimization algorithm, ensuring rapid cooling while avoiding high energy consumption and control oscillations in advance, thereby improving overall operating efficiency and control quality. When the system enters the small temperature difference and steady-state maintenance stage, the frequency change space is limited, and the benefits of continuously executing complex optimizations are low. At this time, the execution frequency of differential evolution can be reduced or paused to reduce the consumption of computing resources and improve the system's real-time performance and engineering feasibility.

[0079] This application's embodiments utilize a differential evolution algorithm combined with a predictive model to achieve online global optimization of the compressor frequency, enabling the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment. By using the compressor frequency as an optimization variable and combining it with a predictive model and differential evolution global search, this invention can achieve effects such as improved temperature stability, reduced energy consumption, reduced frequency fluctuations, and enhanced adaptability, which are superior to traditional PID control methods.

[0080] Based on the same inventive concept, such as Figure 5 As shown, this application embodiment provides an air conditioning control device 50, including: Execution unit: When a preset condition is triggered, the target control strategy is executed. The execution unit includes: The compressor frequency generation module 51 is used to generate multiple different compressor frequencies; In one embodiment, a preset condition is triggered when the compressor starts; In another embodiment, a preset condition is triggered when the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than a third preset temperature difference.

[0081] The target frequency acquisition module 52 is used to process the compressor frequency based on the differential evolution algorithm to obtain candidate compressor frequencies, and to determine the candidate compressor frequency to enter the next generation based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index for representing the future temperature stability level and an energy consumption index for representing the future energy consumption level. The step of determining the candidate compressor frequency for the next generation based on target indicators at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

[0082] In one embodiment, determining the comprehensive evaluation result of the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

[0083] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability and energy consumption indicators can enable the air conditioner to have the advantages of good temperature stability and low energy consumption.

[0084] In another embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

[0085] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability indicators, energy consumption indicators, and frequency change stability indicators can enable air conditioning control to have the advantages of good temperature stability, low energy consumption, and relatively stable subsequent control frequency changes.

[0086] In the third embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

[0087] Furthermore, the preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

[0088] Understandably, the penalty terms imposed by adding start-stop and reliability constraints, as well as comfort boundary constraints, can ensure that air conditioning control possesses advantages such as good temperature stability, low energy consumption, and relatively smooth subsequent control frequency changes, while also taking into account user comfort and operational reliability. This greatly improves the user experience.

[0089] In one alternative implementation, All are preset fixed values.

[0090] As a preferred implementation of the embodiments of this application, it further includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value can be increased by simply increasing a preset fixed value, or the increase can be determined based on the absolute value of the temperature difference between the indoor temperature and the set temperature and the rate of change of the indoor temperature. The larger the absolute value of the temperature difference between the indoor temperature and the set temperature or the greater the rate of change of the indoor temperature, the larger the increase value.

[0091] Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein the first preset temperature difference is greater than or equal to the second preset temperature difference; it is possible to increase only the preset fixed value, or to determine the increase value based on the absolute value of the temperature difference between the indoor temperature and the set temperature. The smaller the absolute value of the temperature difference between the indoor temperature and the set temperature, the greater the increase value.

[0092] Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value can be increased by either a preset fixed value or by determining the increase based on the number of compressor frequency adjustments within a preset time period. The more times the compressor frequency is adjusted within the preset time period, the greater the increase.

[0093] That is, in the embodiments of this application, It can be changed based on different situations. The value of .

[0094] The compressor frequency control module 53 is used to control the compressor frequency to the target compressor frequency.

[0095] The air conditioning control device provided in this application executes a target control strategy when a preset condition is triggered. Executing the target control strategy includes: generating multiple different compressor frequencies; processing the compressor frequencies using a differential evolution algorithm to obtain candidate compressor frequencies; and determining the next generation of candidate compressor frequencies based on target indicators for each candidate compressor frequency, until a target compressor frequency is obtained. The target indicators include a future temperature stability indicator representing the future temperature stability level and an energy consumption indicator representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. This application's solution uses compressor frequency as the optimization variable and employs a differential optimization algorithm for global search. Because it uses future temperature stability and energy consumption indicators for optimization, the obtained target compressor frequency can solve the problem that traditional PID response characteristics often fail to balance energy consumption and stability, frequently resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment.

[0096] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the air conditioning control method provided in any of the above embodiments.

[0097] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0098] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0100] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0101] The computer-readable storage medium provided in this application embodiment stores a computer program, which, when executed by a processor, implements the steps of the air conditioning control method provided in any of the above embodiments. Thus, when a preset condition is triggered, a target control strategy is executed. Executing the target control strategy includes: generating multiple different compressor frequencies; processing the compressor frequencies using a differential evolution algorithm to obtain candidate compressor frequencies; and determining the candidate compressor frequency to enter the next generation based on target indicators for each candidate compressor frequency, until a target compressor frequency is obtained. The target indicators include a future temperature stability indicator representing the future temperature stability level and an energy consumption indicator representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. This application's solution uses the compressor frequency as the optimization variable and employs a differential optimization algorithm for global search. Because it uses future temperature stability and energy consumption indicators for optimization, the obtained target compressor frequency can solve the problem that traditional PID response characteristics often struggle to balance energy consumption and stability, frequently resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment.

[0102] Based on the same inventive concept, such as Figure 6 As shown, this application also provides an air conditioning control system 60, including: At least one processor 61 and at least one memory 62; The memory stores the executable instructions of the processor; The processor is configured to execute the air conditioning control method provided in the above embodiments.

[0103] The air conditioning control system provided in this application stores executable instructions of the processor in a memory. When the executable instructions are executed, the processor can execute a target control strategy when a preset condition is triggered. The execution of the target control strategy includes: generating multiple different compressor frequencies; processing the compressor frequencies based on a differential evolution algorithm to obtain candidate compressor frequencies; and determining the candidate compressor frequency to enter the next generation based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index for representing the future temperature stability and an energy consumption index for representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. The solution in this application uses the compressor frequency as the optimization variable and uses a differential optimization algorithm for global search. Because it uses the future temperature stability index and the energy consumption index for optimization, the obtained target compressor frequency can solve the problem that the response characteristics of traditional PID control are difficult to balance energy consumption and stability, often resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment.

[0104] Based on the same inventive concept, this application provides an air conditioner that applies the following air conditioning control method: When a preset condition is triggered, a target control strategy is executed, which includes: Generate multiple different compressor frequencies; The compressor frequency is processed by the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index to represent the future temperature stability level and an energy consumption index to represent the future energy consumption level. The compressor frequency is controlled to the target compressor frequency.

[0105] In one embodiment, a preset condition is triggered when the compressor starts; In another embodiment, a preset condition is triggered when the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than a third preset temperature difference.

[0106] The step of determining the candidate compressor frequency for the next generation based on target indicators at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

[0107] In one embodiment, determining the comprehensive evaluation result of the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

[0108] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability and energy consumption indicators can enable the air conditioner to have the advantages of good temperature stability and low energy consumption.

[0109] In another embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

[0110] It is understandable that the candidate compressor frequency obtained by optimizing future temperature stability indicators, energy consumption indicators, and frequency change stability indicators can enable air conditioning control to have the advantages of good temperature stability, low energy consumption, and relatively stable subsequent control frequency changes.

[0111] In the third embodiment, the comprehensive evaluation result of determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

[0112] Furthermore, the preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

[0113] Understandably, the penalty terms imposed by adding start-stop and reliability constraints, as well as comfort boundary constraints, can ensure that air conditioning control possesses advantages such as good temperature stability, low energy consumption, and relatively smooth subsequent control frequency changes, while also taking into account user comfort and operational reliability. This greatly improves the user experience.

[0114] In one alternative implementation, All are preset fixed values.

[0115] As a preferred implementation of the embodiments of this application, it further includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value can be increased by simply increasing a preset fixed value, or the increase can be determined based on the absolute value of the temperature difference between the indoor temperature and the set temperature and the rate of change of the indoor temperature. The larger the absolute value of the temperature difference between the indoor temperature and the set temperature or the greater the rate of change of the indoor temperature, the larger the increase value.

[0116] Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein the first preset temperature difference is greater than or equal to the second preset temperature difference; it is possible to increase only the preset fixed value, or to determine the increase value based on the absolute value of the temperature difference between the indoor temperature and the set temperature. The smaller the absolute value of the temperature difference between the indoor temperature and the set temperature, the greater the increase value.

[0117] Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value can be increased by either a preset fixed value or by determining the increase based on the number of compressor frequency adjustments within a preset time period. The more times the compressor frequency is adjusted within the preset time period, the greater the increase.

[0118] That is, in the embodiments of this application, It can be changed based on different situations. The value of .

[0119] The air conditioner provided in this application embodiment executes a target control strategy when a preset condition is triggered. Executing the target control strategy includes: generating multiple different compressor frequencies; processing the compressor frequencies using a differential evolution algorithm to obtain candidate compressor frequencies; determining the next generation of candidate compressor frequencies based on target indicators for each candidate compressor frequency, until a target compressor frequency is obtained. The target indicators include a future temperature stability indicator representing the future temperature stability level and an energy consumption indicator representing the future energy consumption level; and controlling the compressor frequency to be the target compressor frequency. This application's solution uses compressor frequency as the optimization variable and employs a differential optimization algorithm for global search. Because it uses future temperature stability and energy consumption indicators for optimization, the obtained target compressor frequency can solve the problem that traditional PID control often struggles to balance energy consumption and stability, frequently resulting in temperature overshoot or high energy consumption. This allows the air conditioner to automatically find a more energy-efficient and stable operating point in a dynamic environment.

[0120] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0121] It should be noted that in the description of this application, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means at least two.

[0122] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An air conditioning control method, characterized in that, include: When a preset condition is triggered, a target control strategy is executed, which includes: Generate multiple different compressor frequencies; The compressor frequency is processed by the differential evolution algorithm to obtain candidate compressor frequencies, and the candidate compressor frequency to enter the next generation is determined based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index to represent the future temperature stability level and an energy consumption index to represent the future energy consumption level. The compressor frequency is controlled to the target compressor frequency.

2. The method according to claim 1, characterized in that: The process of determining the candidate compressor frequencies for the next generation based on target metrics at each candidate compressor frequency includes: The comprehensive evaluation result of the frequency of each candidate compressor is determined based on the aforementioned target indicators; Candidate compressor frequencies whose comprehensive evaluation results are less than the threshold will be used as candidate compressor frequencies for the next generation.

3. The method according to claim 2, characterized in that: The comprehensive evaluation result for determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, These are the weighting coefficients.

4. The method according to claim 2, characterized in that: The comprehensive evaluation result for determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. These are the weighting coefficients.

5. The method according to claim 2, characterized in that: The comprehensive evaluation result for determining the frequency of each candidate compressor based on the target index includes: in, For candidate compressor frequency The comprehensive evaluation results As an indicator of future temperature stability, As an energy consumption indicator, The frequency stability index is used to describe the degree of smoothness of frequency variation. The penalty item for the preset constraint indicator, These are the weighting coefficients.

6. The method according to claim 5, characterized in that, Also includes: The preset constraint indicators include at least one of the following: start-stop and reliability constraint indicators and comfort boundary constraint indicators; Among them, the start-stop and reliability constraints include: When it is determined that there is a risk of start-stop failure, improve... value; The preset minimum continuous operating frequency of the compressor. The preset frequency threshold; Comfort boundary constraint indicators include: when the predicted future temperature is outside the preset comfort range, it is determined that the comfort requirements are not met, and improvements are made. value.

7. The method according to claim 4 or 5, characterized in that: Also includes: When the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than the first preset temperature difference, or when the rate of change of the indoor temperature is greater than the preset rate of change, increase... The value; Alternatively, when the absolute value of the temperature difference between the indoor temperature and the set temperature is less than the second preset temperature difference, the temperature can be increased. The value; wherein the first preset temperature difference is greater than or equal to the second preset temperature difference; Alternatively, if the compressor frequency is adjusted more times than a preset number within a preset time period, the frequency should be increased. The value of .

8. The method according to claim 1, characterized in that, Also includes: When the compressor starts, a preset condition is triggered; Alternatively, a preset condition may be triggered when the absolute value of the temperature difference between the indoor temperature and the set temperature is greater than a third preset temperature difference.

9. An air conditioning control device, characterized in that, include: Execution unit: When a preset condition is triggered, the target control strategy is executed. The execution unit includes: The compressor frequency generation module is used to generate multiple different compressor frequencies; The target frequency acquisition module is used to process the compressor frequency based on the differential evolution algorithm to obtain candidate compressor frequencies, and to determine the candidate compressor frequency to enter the next generation based on the target index under each candidate compressor frequency, until the target compressor frequency is obtained. The target index includes a future temperature stability index for representing the future temperature stability and an energy consumption index for representing the future energy consumption level. The compressor frequency control module is used to control the compressor frequency to the target compressor frequency.

10. An air conditioning control system, characterized in that, include: At least one processor and at least one memory; The memory stores the executable instructions of the processor; The processor is configured to perform the method according to any one of claims 1-8.

11. An air conditioner, characterized in that, The method described in any one of claims 1-8.

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