Control method and device of fresh air ventilator air conditioner and air conditioner

Abstract

The invention relates to the field of household appliances, and provides a control method and device for a fresh air ventilator air conditioner and an air conditioner. The method comprises the steps that indoor and outdoor environment data and air conditioner power are obtained, and the indoor and outdoor environment data comprise indoor and outdoor air quality data and indoor and outdoor temperature data; according to the indoor and outdoor environment data and the power of the air conditioner, the optimal control power of the fresh air ventilator and the optimal control power of the air conditioner are determined in combination with a multi-target optimization model; and according to the optimal control power of the fresh air ventilator and the optimal control power of the air conditioner, the corresponding fresh air ventilator and the air conditioner are controlled to operate. According to the method, the problem that multiple environmental factors cannot be synthesized for dynamic adjustment based on control of a fixed threshold value and a single parameter is solved, the energy efficiency and the indoor comfort degree are considered at the same time by integrating the environmental data, the lowest energy consumption scheme meeting the requirements of environmental health and room temperature change is found out, and cooperative control of the fresh air ventilator and the air conditioner is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of household appliances, and in particular, to a control method, device and air conditioner for a fresh air conditioner. Background Art

[0002] Since the advent of fresh air conditioners, they have experienced rapid development from simple ventilation to intelligent regulation. In the initial stage, fresh air conditioners mainly solved the problem of indoor and outdoor air exchange. With technological progress, today's fresh air conditioners have integrated multiple functions such as temperature regulation, humidity control, and air purification. Their development not only improves indoor comfort but also achieves remarkable results in energy conservation and environmental protection. However, with the increase in functions, the complexity of the control system has also increased, and precise control has become the key to ensuring the efficient operation of fresh air conditioners.

[0003] Currently, the control methods of fresh air conditioners mainly adopt fixed thresholds and simple timing control. Fixed threshold control means setting specific parameter values (such as CO2 concentration, temperature, etc.). When the actual measured value exceeds or is lower than these thresholds, the system automatically adjusts the fresh air volume or the operating state of the air conditioner. Simple timing control is to turn on or off the fresh air system and air conditioning equipment at a preset time schedule.

[0004] However, the above control methods cannot dynamically balance the heat load changes brought by fresh air introduction. For example, during high-temperature periods in summer, a large amount of fresh air introduction may cause the indoor temperature to rise suddenly, increasing the burden on the air conditioner. Moreover, relying only on a single parameter (such as CO2 or temperature) is prone to control conflicts. For example, increasing the fresh air volume at a high CO2 concentration, but if the outdoor PM2.5 exceeds the standard at this time, it will instead exacerbate indoor pollution. This control method cannot comprehensively consider multiple environmental factors, lacks flexibility and dynamic adjustment ability, and is difficult to achieve optimal indoor environment regulation. Summary of the Invention

[0005] The present invention provides a control method, device and air conditioner for a fresh air conditioner to solve the defect in the prior art that the control based on fixed thresholds and single parameters cannot dynamically adjust by comprehensively considering multiple environmental factors. By integrating environmental data, it simultaneously considers energy efficiency and indoor comfort, finds the lowest energy consumption solution that meets the requirements of environmental health and room temperature changes, and realizes the coordinated control of the fresh air conditioner and the air conditioner.

[0006] The present invention provides a control method for a fresh air conditioner, including: obtaining indoor and outdoor environmental data and the power of the air conditioner, where the indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model; wherein, the multi-objective optimization model is previously constructed based on the total system power as the optimization objective, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine; controlling the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner.

[0007] It should be noted that based on the indoor and outdoor environmental data and the power of the air conditioner, and through the multi-objective optimization model, the optimal control powers of the fresh air machine and the air conditioner are intelligently determined to optimize the total system power, so as to accurately control the fresh air machine and the air conditioner, maintain excellent indoor air quality and comfortable temperature, improve the comfort of the living or working environment, and avoid conflicts and redundant operations between devices by controlling the fresh air machine and the air conditioner to work together, reduce energy consumption, and improve energy utilization efficiency.

[0008] According to the control method for a fresh air conditioner provided by the present invention, before determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model, it includes: constructing a multi-objective optimization model according to the total system power determined by the power of the air conditioner and the power of the fresh air machine, in combination with a first constraint condition and a second constraint condition; wherein, the first constraint condition is used to limit the environmental health index corresponding to the power of the air conditioner and the power of the fresh air machine to be within a preset index range, and the second constraint condition is used to limit the room temperature change rate corresponding to the power of the air conditioner and the power of the fresh air machine to be within a preset rate range.

[0009] It should be noted that by using the multi-objective optimization model and precisely controlling the powers of the fresh air machine and the air conditioner, while considering energy efficiency and indoor comfort, the lowest energy consumption solution that meets the requirements of environmental health and room temperature change is found, so as to achieve the best balance between the two, and in combination with the first constraint condition and the second constraint condition, it is ensured that during the optimization process, the indoor environmental health index always remains within the preset safe range, protecting the health of the occupants, and limiting the room temperature change rate to avoid a decrease in comfort or energy waste caused by too rapid temperature changes.

[0010] According to the present invention, a control method for a fresh air conditioner is provided. Based on indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model, the optimal control power of the fresh air machine and the optimal control power of the air conditioner are determined, including: SA1, selecting the power of the fresh air machine according to the power of the air conditioner, and determining the total power of the first system according to the power of the fresh air machine and the power of the air conditioner; SA2, predicting the indoor environmental data and the power of the air conditioner at the target time according to the power of the fresh air machine and the indoor and outdoor environmental data, to obtain the indoor environmental prediction result and the predicted power of the air conditioner; SA3, determining the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result according to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data; SA4, updating the target optimization model according to the predicted power of the air conditioner and the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result, in combination with the first constraint condition and the second constraint condition, to obtain the total power of the system corresponding to the power of the fresh air machine, and comparing the total power of the system corresponding to the power of the fresh air machine with the total power of the first system. If the total power of the system corresponding to the power of the fresh air machine is greater than the total power of the first system, then update the total power of the first system with the total power of the system corresponding to the power of the fresh air machine, otherwise retain the total power of the first system; wherein, the total power of the system corresponding to the power of the fresh air machine is obtained according to the predicted power of the air conditioner and the power of the fresh air machine; SA5, adjusting the power of the fresh air machine according to the preset power adjustment strategy, and iterating steps SA2-SA4 until the preset end condition is reached, and taking the power of the fresh air machine corresponding to the minimum total power of the system and the predicted power of the air conditioner as the corresponding optimal control power of the fresh air machine and the optimal control power of the air conditioner; wherein, the preset power adjustment strategy is used to limit the size of the total power of the system corresponding to the power of the fresh air machine and determine the corresponding adjustment power of the fresh air machine according to the upper and lower limits of the preset power adjustment of the fresh air machine.

[0011] It should be noted that the power of the fresh air machine is selected based on the real-time collected power of the air conditioner and the indoor and outdoor environmental data to ensure that the selection of the power of the fresh air machine meets the current actual needs, and by reasonably selecting the power of the fresh air machine, a good initial condition is provided for the subsequent optimization process, reducing the number of iterations, and by predicting the power of the air conditioner at the target time, a basis is provided for the joint optimization of the fresh air machine and the air conditioner, and by predicting the indoor environmental data at the target time, ensuring that the environmental health index and the room temperature change rate meet the corresponding constraint conditions, ensuring that the optimization process comprehensively considers the indoor environmental quality, and by iteratively adjusting the power of the fresh air machine, comparing and selecting a smaller total power of the system, gradually approaching the optimal solution, realizing the balance between energy consumption and comfort, and improving the intelligent level of control.

[0012] A control method for a fresh air conditioner according to the present invention predicts indoor environmental data and air conditioner power at a target time based on the fresh air conditioner power and indoor and outdoor environmental data, and obtains an indoor environmental prediction result, including: inputting the fresh air conditioner power and indoor and outdoor environmental data into an indoor environmental prediction model to obtain the indoor environmental prediction result output by the indoor environmental prediction model; wherein, the indoor environmental prediction model is trained according to historical fresh air conditioner power, historical indoor and outdoor environments, and their corresponding actual indoor environmental data and actual air conditioner power at historical target times; or, determining the predicted indoor carbon dioxide concentration corresponding to the target time according to the indoor carbon dioxide concentration and the preset target carbon dioxide concentration in the indoor and outdoor environmental data; determining the first fine particle concentration entering the room after being filtered by the fresh air conditioner according to the outdoor fine particle concentration in the indoor and outdoor environmental data and the previously obtained fresh air conditioner filtration efficiency, and combining the indoor fine particle concentration and the target time in the indoor and outdoor environmental data to determine the predicted indoor fine particle concentration corresponding to the target time; determining the predicted indoor temperature corresponding to the target time and the predicted air conditioner power corresponding to the predicted indoor temperature according to the indoor and outdoor temperatures in the indoor and outdoor environmental data and the previously obtained heat exchange efficiency of the air conditioner; obtaining the corresponding predicted indoor environmental data according to the predicted indoor carbon dioxide concentration, predicted indoor fine particle concentration, and predicted indoor temperature corresponding to the target time.

[0013] It should be noted that by using the indoor environmental prediction model trained based on historical data, the indoor environmental data and air conditioner power at the target time can be predicted more accurately, and the model is trained based on actual historical data to ensure that the model can learn the laws and trends of environmental changes, thereby improving the accuracy of prediction; by separately considering the carbon dioxide concentration, fine particle concentration, and temperature, and introducing the preset target carbon dioxide concentration, fresh air conditioner filtration efficiency, and air conditioner heat exchange efficiency corresponding to the room for individual prediction, the prediction is made more in line with the actual situation. By comprehensively considering multiple factors such as indoor and outdoor environmental data, fresh air conditioner filtration efficiency, and air conditioner heat exchange efficiency, the prediction result is more comprehensive and reliable, realizing more refined prediction management of the indoor environment.

[0014] According to the present invention, a control method for a fresh air conditioner is provided. Indoor predicted environmental data includes indoor predicted carbon dioxide concentration, indoor predicted fine particulate matter concentration, and indoor predicted temperature. According to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data, the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result are determined, including: determining the environmental health index according to the indoor predicted carbon dioxide concentration, the indoor predicted fine particulate matter concentration, and the indoor predicted temperature, in combination with a preset weight dynamic allocation rule; wherein the preset weight dynamic allocation rule is used to define the allocation weights of the indoor predicted carbon dioxide concentration, the indoor predicted fine particulate matter concentration, and the indoor predicted temperature corresponding to different time periods; determining the room temperature change rate within the target time according to the indoor predicted temperature and the indoor temperature in the indoor and outdoor environmental data.

[0015] It should be noted that by considering the indoor predicted carbon dioxide concentration, the fine particulate matter concentration, and the temperature simultaneously, the indoor environmental quality can be evaluated more comprehensively, rather than just a single indicator. In combination with the preset weight dynamic allocation rule, the weights of each indicator can be adjusted according to the importance of different time periods or specific requirements, making the environmental health index more flexible and adaptable to actual needs. Thus, according to the obtained environmental health index and the room temperature change rate, instant feedback can be provided to the system, which helps to quickly adjust the operation strategies of the fresh air machine and the air conditioner to maintain the stability and health of the indoor environment.

[0016] According to the present invention, a control method for a fresh air conditioner is provided. The method further includes: monitoring the outdoor fine particulate matter concentration; determining whether the difference in the outdoor fine particulate matter concentration within the first preset duration exceeds the first preset threshold; if the difference in the outdoor fine particulate matter concentration exceeds the first preset threshold, then adjusting the power of the corresponding fresh air machine according to the change trend of the outdoor fine particulate matter concentration within the first preset duration, in combination with a preset power adjustment rule; wherein the preset power adjustment rule is used to define the adjustment coefficients corresponding to the increasing trend and the decreasing trend respectively. Otherwise, the power of the corresponding fresh air machine is retained.

[0017] It should be noted that by monitoring the outdoor fine particulate matter concentration and analyzing it in real time, the environmental changes can be quickly responded to, especially when the particulate matter concentration shows significant fluctuations. Further, by setting a threshold and monitoring the concentration difference, preventive adjustments can be made before the particulate matter concentration reaches the harmful level, reducing the impact on the indoor environment and avoiding over - operation of the fresh air machine when the particulate matter concentration is low, thereby saving energy and achieving energy efficiency optimization.

[0018] According to the present invention, a control method for a fresh air conditioner is provided. The method further includes: monitoring the number of people indoors; determining whether a preset fresh air conditioner trigger condition is met based on the number of people indoors; wherein the preset fresh air conditioner trigger condition is used to define that when the growth rate of the corresponding indoor number of people exceeds a second preset threshold, the super-fast mode of the fresh air conditioner is triggered; if the preset fresh air conditioner trigger condition is met, the wind speed to be adjusted is determined based on the preset adjusted wind speed and the indoor number of people detection data, and the fresh air conditioner is adjusted according to the wind speed to be adjusted; otherwise, the wind speed of the corresponding fresh air conditioner is retained.

[0019] It should be noted that by monitoring the number of people indoors and triggering the adjustment of the fresh air conditioner based on the change in the number of people, an intelligent response to the fresh air demand is realized, ensuring that the indoor air quality is dynamically adjusted with the change of personnel. By introducing the super-fast mode, when the growth rate of the indoor number of people exceeds the preset threshold, the fresh air conditioner can quickly increase the wind speed and rapidly improve the indoor air quality, effectively coping with the sudden increase in the number of people. Moreover, the super-fast mode is only triggered when the growth rate of the number of people exceeds the threshold, avoiding unnecessary energy waste and ensuring the comfort of indoor personnel at the same time.

[0020] According to the present invention, a control method for a fresh air conditioner is provided. The method includes obtaining indoor and outdoor environmental data and the current power of the air conditioner, including: collecting the indoor carbon dioxide concentration, indoor and outdoor fine particulate matter concentrations, and indoor and outdoor temperatures to obtain indoor and outdoor environmental data; obtaining the power of the air conditioner; and filtering out outliers from the indoor and outdoor environmental data.

[0021] It should be noted that by collecting data such as the indoor carbon dioxide concentration, fine particulate matter concentration, and temperature, it is ensured that the obtained information is accurate and timely, and by filtering out outliers, abnormal data caused by sensor failures, measurement errors, or external interferences is excluded, thereby further improving the reliability of the data.

[0022] The present invention also provides a control device for a fresh air conditioner, including: a data acquisition module for obtaining indoor and outdoor environmental data and the power of the air conditioner, where the indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; a multi-objective optimization module for determining the optimal control power of the fresh air conditioner and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model; wherein the multi-objective optimization model is constructed in advance based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air conditioner; and an optimized control module for controlling the operation of the corresponding fresh air conditioner and air conditioner according to the optimal control power of the fresh air conditioner and the optimal control power of the air conditioner.

[0023] It should be noted that based on the indoor and outdoor environmental data and the air conditioner power obtained by the data acquisition module, and using the multi-objective optimization model through the multi-objective optimization module, the optimal control powers of the fresh air machine and the air conditioner are intelligently determined to optimize the total power of the system. Thus, the fresh air machine and the air conditioner are precisely controlled through the optimization control module to maintain excellent indoor air quality and comfortable temperature, improve the comfort of the living or working environment, and avoid conflicts and redundant operations between devices by controlling the coordinated operation of the fresh air machine and the air conditioner, reduce energy consumption, and improve energy utilization efficiency.

[0024] The present invention also provides an air conditioner, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the control method of the fresh air machine and air conditioner as described in any one of the above are implemented.

[0025] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the control method of the fresh air machine and air conditioner as described in any one of the above are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0027] Figure 1 is one of the flow schematic diagrams of the control method of the fresh air machine and air conditioner provided by the present invention; Figure 2 is another flow schematic diagram of the control method of the fresh air machine and air conditioner provided by the present invention; Figure 3 is the structural schematic diagram of the control device of the fresh air machine and air conditioner provided by the present invention; Figure 4 is the structural schematic diagram of the air conditioner provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0029] Next Figure 1The flowchart of a control method for a fresh air conditioner of the present invention is described. The method includes: S11. Obtain indoor and outdoor environmental data and the power of the air conditioner. The indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; S12. Based on the indoor and outdoor environmental data and the power of the air conditioner, and in combination with a multi-objective optimization model, determine the optimal control power of the fresh air machine and the optimal control power of the air conditioner. Among them, the multi-objective optimization model is previously constructed with the total system power as the optimization target, and the total system power is obtained from the power of the air conditioner and the power of the fresh air machine; S13. Control the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner.

[0030] It should be noted that the step numbers "S1N" in this specification do not represent the sequence of the control method for the fresh air conditioner. The following specifically combines Figure 2 to describe the control method for the fresh air conditioner of the present invention.

[0031] Step S11. Obtain indoor and outdoor environmental data and the power of the air conditioner. The indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data.

[0032] In this embodiment, referring to Figure 2 , obtaining the indoor and outdoor environmental data and the current power of the air conditioner includes: collecting the indoor carbon dioxide concentration, indoor and outdoor fine particulate matter concentrations, and indoor and outdoor temperatures to obtain the indoor and outdoor environmental data; obtaining the power of the air conditioner; and filtering out outliers from the indoor and outdoor environmental data.

[0033] It should be noted that by collecting data such as the indoor carbon dioxide concentration, fine particulate matter concentration, and temperature, it is ensured that the obtained information is accurate and timely, and outliers are filtered out to exclude abnormal data caused by sensor failures, measurement errors, or external interferences, thereby further improving the reliability of the data.

[0034] In addition, when collecting the indoor carbon dioxide concentration, indoor and outdoor fine particulate matter concentrations, and indoor and outdoor temperatures, a carbon dioxide sensor can be used to detect the corresponding indoor carbon dioxide concentration, a laser PM2.5 sensor can be used to detect the indoor and outdoor fine particulate matter concentrations, an indoor temperature sensor can be used to detect the indoor temperature, and an outdoor temperature sensor can be used to detect the outdoor temperature or an outdoor weather station or other meteorological data can be used to determine the corresponding outdoor temperature. Specifically, it can be selected according to actual design requirements and will not be further limited here. In addition, outlier filtering can be selected according to actual design requirements, such as the Tukey's fences method, etc., and data preprocessing such as outlier filtering can be implemented through an edge computing gateway to avoid transmission losses and delays caused by uploading data to the cloud and downloading data from the cloud, which will not be further limited here.

[0035] In an alternative embodiment, when collecting the indoor carbon dioxide concentration, indoor and outdoor fine particulate matter concentrations, and indoor and outdoor temperatures, an infrared human counter is also used to detect the number of people indoors. After using the Tukey's fences method to filter outliers from the indoor and outdoor environmental data, the obtained data is constructed into a matrix in a preset matrix form, so as to facilitate directly transmitting the matrix to a multi-objective optimization model for optimization calculation later. The matrix can be expressed as: Among them, represents the indoor temperature, represents the outdoor temperature, represents the indoor fine particulate matter concentration, represents the indoor fine particulate matter concentration, represents the indoor carbon dioxide concentration, represents the number of people indoors, represents the air conditioner power.

[0036] It should be noted that the outdoor fine particulate matter concentration and the number of people indoors can be used for outdoor PM2.5 mutation detection and indoor sudden increase in the number of people detection. Specifically, it can be referred to as described below and will not be further limited here.

[0037] In an alternative embodiment, before determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the air conditioner power in combination with a multi-objective optimization model, it includes: constructing a multi-objective optimization model according to the total system power determined by the air conditioner power and the fresh air machine power, in combination with the first constraint condition and the second constraint condition; where the first constraint condition is used to limit the environmental health index corresponding to the air conditioner power and the fresh air machine power to be within a preset index range, and the second constraint condition is used to limit the room temperature change rate corresponding to the air conditioner power and the fresh air machine power to be within a preset rate range.

[0038] It should be noted that by using the multi-objective optimization model, the power of the fresh air machine and the air conditioner is precisely controlled to simultaneously consider energy efficiency and indoor comfort, find the lowest energy consumption solution that meets the requirements of environmental health and room temperature change, so as to achieve the best balance between the two. Combining the first constraint condition and the second constraint condition, it is ensured that during the optimization process, the indoor environmental health index always remains within the preset safe range, safeguarding the health of the occupants, and limiting the rate of room temperature change to avoid a decrease in comfort or energy waste caused by too rapid temperature change.

[0039] In addition, the multi-objective optimization model is expressed as: Among them, represents the total system power; represents the power of the air conditioner; represents the power of the fresh air machine; ≤80 represents the first constraint condition, represents the environmental health index; represents the second constraint condition; represents the rate of room temperature change within the target time; represents the indoor temperature difference within the target time; ∆t represents the duration of the target time; represents the indoor carbon dioxide concentration; represents the indoor concentration of fine particulate matter; represents the indoor temperature; 、 and are respectively used to characterize the corresponding 、 and allocation weights.

[0040] Step S12, according to the indoor and outdoor environmental data and the power of the air conditioner, combined with the multi-objective optimization model, determine the optimal control power of the fresh air machine and the optimal control power of the air conditioner; among them, the multi-objective optimization model is first constructed based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine.

[0041] In this embodiment, based on the indoor and outdoor environmental data and the air conditioner power, and in combination with the multi-objective optimization model, the optimal control power of the fresh air fan and the optimal control power of the air conditioner are determined, including: SA1, select the fresh air fan power according to the air conditioner power, and determine the total power of the first system according to the fresh air fan power and the air conditioner power; SA2, predict the indoor environmental data and the air conditioner power at the target time according to the fresh air fan power and the indoor and outdoor environmental data, and obtain the indoor environmental prediction result and the predicted air conditioner power; SA3, determine the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result according to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data; SA4, update the target optimization model according to the predicted air conditioner power, the environmental health index corresponding to the indoor environmental prediction result, and the room temperature change rate, in combination with the first constraint condition and the second constraint condition, to obtain the total power of the system corresponding to the fresh air fan power, and compare the total power of the system corresponding to the fresh air fan power with the total power of the first system. If the total power of the system corresponding to the fresh air fan power is greater than the total power of the first system, then update the total power of the first system with the total power of the system corresponding to the fresh air fan power, otherwise retain the total power of the first system; wherein, the total power of the system corresponding to the fresh air fan power is obtained according to the predicted air conditioner power and the fresh air fan power; SA5, adjust the fresh air fan power according to the preset power adjustment strategy, and iterate steps SA2 - SA4 until the preset end condition is reached, and use the fresh air fan power and the predicted air conditioner power corresponding to the minimum total system power as the corresponding optimal control power of the fresh air fan and the optimal control power of the air conditioner; wherein, the preset power adjustment strategy is used to limit the size of the total power of the system corresponding to the corresponding fresh air fan power and the upper and lower limits of the preset fresh air fan power adjustment to determine the corresponding fresh air fan adjustment power.

[0042] It should be noted that the fresh air fan power is selected based on the real-time collected air conditioner power and indoor and outdoor environmental data to ensure that the selection of the fresh air fan power meets the current actual needs, and by reasonably selecting the fresh air fan power, it provides a good initial condition for the subsequent optimization process, reduces the number of iterations, and provides a basis for the joint optimization of the fresh air fan and the air conditioner by predicting the air conditioner power at the target time, and by predicting the indoor environmental data at the target time, it ensures that the environmental health index and the room temperature change rate meet the corresponding constraint conditions, ensures that the optimization process comprehensively considers the indoor environmental quality, and by iteratively adjusting the fresh air fan power, comparing and selecting a smaller total system power, gradually approaching the optimal solution, achieving the balance of energy consumption and comfort, and improving the intelligent level of control.

[0043] Specifically, according to the indoor and outdoor environmental data, the power of the fresh air machine is selected, including: determining the first fresh air volume according to the indoor carbon dioxide concentration and the target indoor carbon dioxide concentration in the indoor and outdoor environmental data; determining the second fresh air volume according to the indoor and outdoor fine particulate matter concentrations and the target indoor fine particulate matter concentration; selecting the largest fresh air volume as the fresh air volume of the fresh air machine according to the first fresh air volume and the second fresh air volume, and determining the corresponding fresh air machine power; or selecting based on prior experience or experimental results, which is not further limited here.

[0044] In addition, the indoor predicted environmental data includes the indoor predicted carbon dioxide concentration, the indoor predicted fine particulate matter concentration, and the indoor predicted temperature; according to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data, the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result are determined, including: determining the environmental health index according to the indoor predicted carbon dioxide concentration, the indoor predicted fine particulate matter concentration, and the indoor predicted temperature, in combination with a preset weight dynamic allocation rule; wherein, the preset weight dynamic allocation rule is used to limit the allocation weights of the indoor predicted carbon dioxide concentration, the indoor predicted fine particulate matter concentration, and the indoor predicted temperature corresponding to different time periods; determining the room temperature change rate within the target time according to the indoor predicted temperature and the indoor temperature in the indoor and outdoor environmental data.

[0045] It should be noted that by simultaneously considering the indoor predicted carbon dioxide concentration, the fine particulate matter concentration, and the temperature, the indoor environmental quality can be evaluated more comprehensively, rather than just a single indicator, and in combination with the preset weight dynamic allocation rule, the weights of each indicator can be adjusted according to the importance of different time periods or specific requirements, making the environmental health index more flexible and adaptable to actual needs. Thus, according to the obtained environmental health index and the room temperature change rate, instant feedback can be provided to the system, which helps to quickly adjust the operation strategies of the fresh air machine and the air conditioner to maintain the stability and health of the indoor environment.

[0046] In addition, the preset weight dynamic allocation rule can be configured according to the requirements of different time periods. For example, during the day, it is necessary to ensure CO2 control in crowded areas, while at night, PM2.5 filtration is emphasized. Accordingly, the allocation weight of the indoor predicted carbon dioxide concentration is set to 0.6, the allocation weight of the indoor predicted fine particulate matter concentration is set to 0.3, and the allocation weight of the indoor predicted temperature is set to 0.1. Within the preset time period corresponding to night or holidays, the allocation weight of the indoor predicted carbon dioxide concentration is set to 0.3, the allocation weight of the indoor predicted fine particulate matter concentration is set to 0.6, and the allocation weight of the indoor predicted temperature is set to 0.1, which is not further limited here.

[0047] In an alternative embodiment, the indoor environmental data and the air conditioner power at a target time are predicted based on the fresh air fan power and the indoor and outdoor environmental data to obtain an indoor environment prediction result, including: inputting the fresh air fan power and the indoor and outdoor environmental data into an indoor environment prediction model to obtain the indoor environment prediction result output by the indoor environment prediction model; wherein, the indoor environment prediction model is trained based on the historical fresh air fan power, the historical indoor and outdoor environment, the actual indoor environmental data and the actual air conditioner power corresponding to the historical target time.

[0048] It should be noted that by using the indoor environment prediction model trained based on historical data, the indoor environmental data and the air conditioner power at the target time can be predicted more accurately, and the model is trained based on actual historical data to ensure that the model can learn the laws and trends of environmental changes, thereby improving the accuracy of prediction.

[0049] In another alternative embodiment, predicting the indoor environmental data and the air conditioner power at a target time based on the fresh air fan power and the indoor and outdoor environmental data to obtain an indoor environment prediction result further includes: determining the predicted indoor carbon dioxide concentration corresponding to the target time according to the indoor carbon dioxide concentration in the indoor and outdoor environmental data and the preset target carbon dioxide concentration; determining the first fine particulate matter concentration entering the indoor after being filtered by the fresh air fan according to the outdoor fine particulate matter concentration in the indoor and outdoor environmental data and the previously obtained fresh air fan filtration efficiency, and combining the indoor fine particulate matter concentration in the indoor and outdoor environmental data and the target time to determine the predicted indoor fine particulate matter concentration corresponding to the target time; determining the predicted indoor temperature corresponding to the target time and the predicted air conditioner power corresponding to the predicted indoor temperature according to the indoor and outdoor temperatures in the indoor and outdoor environmental data and the previously obtained heat exchange efficiency of the air conditioner; obtaining the corresponding predicted indoor environmental data according to the predicted indoor carbon dioxide concentration, the predicted indoor fine particulate matter concentration and the predicted indoor temperature corresponding to the target time.

[0050] It should be noted that by separately considering the carbon dioxide concentration, the fine particulate matter concentration and the temperature, and by introducing the preset target carbon dioxide concentration, the fresh air fan filtration efficiency and the air conditioner heat exchange efficiency corresponding to the indoor for individual prediction, the prediction can be made more in line with the actual situation. By comprehensively considering multiple factors such as the indoor and outdoor environmental data, the fresh air fan filtration efficiency, and the air conditioner heat exchange efficiency, the prediction result is more comprehensive and reliable, realizing more refined prediction management of the indoor environment.

[0051] In addition, the predicted indoor carbon dioxide concentration C(t) corresponding to the target time is expressed as: C(t)= C2+C1-C2e (-Nt) Wherein, C2 represents a preset target carbon dioxide concentration, C1 represents the indoor carbon dioxide concentration in the indoor and outdoor environmental data, t represents the target time, and e represents the base of the natural logarithm.

[0052] The indoor predicted fine particulate matter concentration P(t) corresponding to the target time is expressed as: P(t)=P2’+(P1 - P2’)·e (-Nt) P2’ = P2·(1 - η1) Wherein, P1 represents the indoor fine particulate matter concentration in the indoor and outdoor environmental data, P2 represents the outdoor fine particulate matter concentration in the indoor and outdoor environmental data, P2’ represents the first fine particulate matter concentration entering the room after being filtered by the fresh air machine, η1 represents the filtration efficiency of the fresh air machine, t represents the target time, and e represents the base of the natural logarithm.

[0053] The indoor predicted temperature T(t) corresponding to the target time is expressed as: T(t)=(T in -T out )·(1 - η2)·(1 - e (-Nt) ) Wherein, T in represents the indoor temperature in the indoor and outdoor environmental data, T out represents the outdoor temperature in the indoor and outdoor environmental data, η2 represents the heat exchange efficiency of the air conditioner, t represents the target time, and e represents the base of the natural logarithm.

[0054] In addition, according to the indoor predicted temperature corresponding to the target time, determining the predicted power of the corresponding air conditioner can be determined by conventional algorithms or model prediction, etc., and no further description is made here.

[0055] Step S13, control the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner. It should be noted that after obtaining the optimal control power of the fresh air machine and the optimal control power of the air conditioner, the corresponding fresh air machine and air conditioner are controlled by the actuator respectively.

[0056] In an alternative embodiment, the method further includes: monitoring the outdoor fine particulate matter concentration; determining whether the difference in the outdoor fine particulate matter concentration within the first preset duration exceeds the first preset threshold; if the difference in the outdoor fine particulate matter concentration exceeds the first preset threshold, then adjust the power of the corresponding fresh air machine according to the change trend of the outdoor fine particulate matter concentration within the first preset duration, in combination with the preset power adjustment rule; wherein, the preset power adjustment rule is used to define the adjustment coefficients corresponding to the increasing trend and the decreasing trend respectively; otherwise, retain the power of the corresponding fresh air machine.

[0057] It should be noted that by monitoring the concentration of outdoor fine particulate matter and analyzing it in real time, it can quickly respond to environmental changes, especially when there are significant fluctuations in the particulate matter concentration. Further, by setting a threshold and monitoring the concentration difference, preventive adjustments can be made before the particulate matter concentration reaches the harmful level, reducing the impact on the indoor environment, and avoiding excessive operation of the fresh air fan when the particulate matter concentration is low, thereby saving energy and achieving energy efficiency optimization.

[0058] In addition, monitoring the concentration of outdoor fine particulate matter can also be achieved by regularly obtaining indoor and outdoor environmental data based on a first preset time period. For details, reference can be made to the previous text, and no repeated elaboration will be made here.

[0059] In addition, a preset power adjustment rule is expressed as: P fan =a×P normal ΔPM2.5>bμg / m³ / 5min Wherein, P fan represents the power of the fresh air fan adjusted based on the preset power adjustment rule, P normal represents the rated power of the fresh air fan, ΔPM2.5 is the difference in the concentration of outdoor fine particulate matter within the first preset time period, a represents the coefficient corresponding to the change trend of the outdoor fine particulate matter concentration within the first preset time period, which can be set according to actual design requirements. For example, when the change trend of the outdoor fine particulate matter concentration within the first preset time period is increasing, a can be 1.2; when the change trend of the outdoor fine particulate matter concentration within the first preset time period is decreasing, a can be 0.8. No further limitation is made here. In addition, b represents the first preset threshold, which can be set according to the sudden change amount of fine particulate matter that needs to be monitored in actual design. For example, it can be 50, etc. No further limitation is made here.

[0060] In an alternative embodiment, the method further includes: monitoring the number of people indoors; determining whether the preset fresh air fan trigger condition is met based on the number of people indoors; wherein the preset fresh air fan trigger condition is used to limit that when the growth rate of the corresponding number of people indoors exceeds a second preset threshold, the super-fast mode of the fresh air fan is triggered; if the preset fresh air fan trigger condition is met, the wind speed to be adjusted is determined based on the preset adjusted wind speed and the indoor number detection data, and the fresh air fan is adjusted according to the wind speed to be adjusted; otherwise, the wind speed of the corresponding fresh air fan is retained.

[0061] It should be noted that by monitoring the number of people indoors and triggering the adjustment of the fresh air machine based on the change in the number of people, an intelligent response to the fresh air demand is achieved, ensuring that the indoor air quality is dynamically adjusted according to the change in the number of people. By introducing the ultra-fast mode, when the growth rate of the number of people indoors exceeds the preset threshold, the fresh air machine can quickly increase the wind speed, rapidly improve the indoor air quality, effectively respond to the sudden increase in the number of people, and only trigger the ultra-fast mode when the growth rate of the number of people exceeds the threshold, avoiding unnecessary energy waste and ensuring the comfort of indoor personnel at the same time.

[0062] In addition, monitoring the number of people indoors can also be achieved based on obtaining indoor and outdoor environmental data. When obtaining the corresponding indoor environmental data, an infrared human counter can also be used to collect the number of people indoors. For details, please refer to the previous text and no repeated description will be made here.

[0063] In addition, the wind speed to be adjusted is expressed as: Among them, N human represents the number of people indoors, and 1500 represents the preset adjusted wind speed.

[0064] In summary, the embodiments of the present invention are based on indoor and outdoor environmental data and the power of the air conditioner, and through a multi-objective optimization model, the optimal control power of the fresh air machine and the air conditioner are intelligently determined to achieve the optimization of the total system power, thereby accurately controlling the fresh air machine and the air conditioner, maintaining excellent indoor air quality and comfortable temperature, improving the comfort of the living or working environment, and avoiding conflicts and redundant operations between devices by controlling the coordinated operation of the fresh air machine and the air conditioner, reducing energy consumption, and improving energy utilization efficiency.

[0065] Next, the control device of the fresh air machine and air conditioner provided by the present invention will be described. The control device of the fresh air machine and air conditioner described below can be mutually corresponding and referred to the control method of the fresh air machine and air conditioner described above.

[0066] Figure 3 Fig. shows a schematic structural diagram of a control device of a fresh air machine and air conditioner. The structure includes: A data acquisition module 31 that acquires indoor and outdoor environmental data and the power of the air conditioner. The indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; A multi-objective optimization module 32 that determines the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model. Among them, the multi-objective optimization model is previously constructed based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine; The optimization control module 33 controls the corresponding fresh air unit and air conditioner to operate according to the optimal control power of the fresh air unit and the optimal control power of the air conditioner.

[0067] In this embodiment, the data acquisition module 31 includes: a first data acquisition unit that collects the indoor carbon dioxide concentration, the indoor and outdoor fine particulate matter concentrations, and the indoor and outdoor temperatures to obtain indoor and outdoor environmental data; a second data acquisition unit that acquires the air conditioner power; and a preprocessing unit that filters out outliers from the indoor and outdoor environmental data.

[0068] In an alternative embodiment, the device includes: a model construction module that constructs a multi-objective optimization model based on the total system power determined according to the air conditioner power and the fresh air unit power, in combination with a first constraint condition and a second constraint condition, before determining the optimal control power of the fresh air unit and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the air conditioner power, in combination with the multi-objective optimization model; wherein, the first constraint condition is used to limit the environmental health index corresponding to the air conditioner power and the fresh air unit power to be within a preset index range, and the second constraint condition is used to limit the room temperature change rate corresponding to the air conditioner power and the fresh air unit power to be within a preset rate range.

[0069] The multi-objective optimization module 32 includes: an initialization unit that selects the fresh air unit power according to the air conditioner power and determines the first total system power according to the fresh air unit power and the air conditioner power; an environmental prediction unit that predicts the indoor environmental data and the air conditioner power at the target time according to the fresh air unit power and the indoor and outdoor environmental data to obtain an indoor environmental prediction result and a predicted air conditioner power; an environmental detection unit that determines the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result according to the indoor temperature in the indoor environmental prediction result and the indoor and outdoor environmental data; an optimization unit that updates the target optimization model according to the predicted air conditioner power and the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result, in combination with the first constraint condition and the second constraint condition, to obtain the total system power corresponding to the fresh air unit power, and compares the total system power corresponding to the fresh air unit power with the first total system power. If the total system power corresponding to the fresh air unit power is greater than the first total system power, then updates the first total system power with the total system power corresponding to the fresh air unit power, otherwise retains the first total system power; wherein, the total system power corresponding to the fresh air unit power is obtained according to the predicted air conditioner power and the fresh air unit power; an iteration unit that adjusts the fresh air unit power according to a preset power adjustment strategy and repeats the execution of the environmental prediction unit to the optimization unit until a preset end condition is reached, and takes the fresh air unit power and the predicted air conditioner power corresponding to the minimum total system power as the corresponding optimal control power of the fresh air unit and the optimal control power of the air conditioner; wherein, the preset power adjustment strategy is used to limit the adjustment power of the fresh air unit to be determined according to the magnitude of the total system power corresponding to the fresh air unit power and the upper and lower limits of the preset fresh air unit power adjustment.

[0070] Specifically, an initialization unit is configured to: determine a first fresh air volume according to the indoor carbon dioxide concentration and the target indoor carbon dioxide concentration in the indoor and outdoor environmental data; determine a second fresh air volume according to the indoor and outdoor fine particulate matter concentrations and the target indoor fine particulate matter concentration; select the maximum fresh air volume as the fresh air volume of the fresh air machine according to the first fresh air volume and the second fresh air volume, and determine the corresponding fresh air machine power; or select based on prior experience or experimental results, which is not further limited herein.

[0071] In addition, the indoor predicted environmental data includes the predicted indoor carbon dioxide concentration, the predicted indoor fine particulate matter concentration, and the predicted indoor temperature; the environmental detection unit includes: an index determination subunit, which determines an environmental health index according to the predicted indoor carbon dioxide concentration, the predicted indoor fine particulate matter concentration, and the predicted indoor temperature, in combination with a preset weight dynamic distribution rule; wherein the preset weight dynamic distribution rule is used to limit the distribution weights of the predicted indoor carbon dioxide concentration, the predicted indoor fine particulate matter concentration, and the predicted indoor temperature corresponding to different time periods; a temperature change determination subunit, which determines the room temperature change rate within a target time according to the predicted indoor temperature and the indoor temperature in the indoor and outdoor environmental data.

[0072] In an alternative embodiment, the environmental prediction unit includes: a model prediction unit, which inputs the fresh air machine power and the indoor and outdoor environmental data into an indoor environmental prediction model to obtain an indoor environmental prediction result output by the indoor environmental prediction model; wherein the indoor environmental prediction model is trained according to the historical fresh air machine power, the historical indoor and outdoor environment, and the actual indoor environmental data and the actual air conditioner power corresponding to the historical target time.

[0073] In another alternative embodiment, the environmental prediction unit further includes: a first prediction subunit, which determines the predicted indoor carbon dioxide concentration corresponding to a target time according to the indoor carbon dioxide concentration in the indoor and outdoor environmental data and the preset target carbon dioxide concentration; a second prediction subunit, which determines the first fine particulate matter concentration entering the room after being filtered by the fresh air machine according to the outdoor fine particulate matter concentration in the indoor and outdoor environmental data and the previously obtained fresh air machine filtration efficiency, and combines the indoor fine particulate matter concentration in the indoor and outdoor environmental data and the target time to determine the predicted indoor fine particulate matter concentration corresponding to the target time; a third prediction subunit, which determines the predicted indoor temperature corresponding to the target time and the predicted air conditioner power corresponding to the predicted indoor temperature according to the indoor and outdoor temperatures in the indoor and outdoor environmental data, in combination with the previously obtained heat exchange efficiency of the air conditioner; a data determination subunit, which obtains the corresponding indoor predicted environmental data according to the predicted indoor carbon dioxide concentration, the predicted indoor fine particulate matter concentration, and the predicted indoor temperature corresponding to the target time.

[0074] In an alternative embodiment, the device further includes a pollution interception module, which is configured to: monitor the concentration of outdoor fine particulate matter; determine whether the difference in the concentration of outdoor fine particulate matter within a first preset duration exceeds a first preset threshold; if the difference in the concentration of outdoor fine particulate matter exceeds the first preset threshold, adjust the power of the corresponding fresh air unit according to the change trend of the concentration of outdoor fine particulate matter within the first preset duration in combination with a preset power adjustment rule; wherein the preset power adjustment rule is used to define the adjustment coefficients corresponding to the increasing trend and the decreasing trend respectively. Otherwise, retain the power of the corresponding fresh air unit.

[0075] In an alternative embodiment, the device further includes a sudden increase in the number of people detection module, which is configured to: monitor the number of people indoors; determine whether the preset fresh air unit trigger condition is met based on the number of people indoors; wherein the preset fresh air unit trigger condition is used to define that when the growth rate of the corresponding number of people indoors exceeds a second preset threshold, trigger the ultra-fast mode of the fresh air unit; if the preset fresh air unit trigger condition is met, determine the wind speed to be adjusted based on the preset adjusted wind speed and the indoor number of people detection data, and adjust the fresh air unit according to the wind speed to be adjusted; otherwise, retain the wind speed of the corresponding fresh air unit.

[0076] In summary, the embodiment of the present invention is based on the indoor and outdoor environment data and the air conditioner power obtained by the data acquisition module, and uses a multi-objective optimization model through the multi-objective optimization module to intelligently determine the optimal control power of the fresh air unit and the air conditioner, realize the optimization of the total system power, and thus accurately control the fresh air unit and the air conditioner through the optimization control module to keep the indoor air quality excellent and the temperature comfortable, improve the comfort of the living or working environment, and avoid conflicts and redundant operations between devices by controlling the fresh air unit and the air conditioner to work together, reduce energy consumption, and improve energy utilization efficiency.

[0077] Figure 4 An example of a schematic physical structure diagram of an air conditioner is as Figure 4As shown, the air conditioner may include: a processor 410, a communications interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communications interface 420, and the memory 430 complete communication with each other through the communication bus 440. The processor 410 may call the logical instructions in the memory 430 to execute the control method of the fresh air conditioner. The method includes: obtaining indoor and outdoor environmental data and the power of the air conditioner, where the indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; determining the optimal control power of the fresh air conditioner and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model; where the multi-objective optimization model is constructed in advance based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air conditioner; controlling the corresponding fresh air conditioner and air conditioner to operate according to the optimal control power of the fresh air conditioner and the optimal control power of the air conditioner.

[0078] In addition, when the logical instructions in the above-mentioned memory 430 can be implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0079] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the control method of the fresh air conditioner provided by the above-mentioned various methods. The method includes: obtaining indoor and outdoor environmental data and the power of the air conditioner. The indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model. Among them, the multi-objective optimization model is constructed in advance based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine; controlling the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner.

[0080] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the control method of the fresh air conditioner provided by the above-mentioned various methods. The method includes: obtaining indoor and outdoor environmental data and the power of the air conditioner. The indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model. Among them, the multi-objective optimization model is constructed in advance based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine; controlling the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner.

[0081] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0082] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A control method for a fresh air conditioner, characterized in that, Including: Obtaining indoor and outdoor environmental data and the power of the air conditioner, where the indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data; Determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model; wherein, the multi-objective optimization model is constructed in advance based on the total system power as the optimization objective, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air machine; Controlling the corresponding fresh air machine and air conditioner to operate according to the optimal control power of the fresh air machine and the optimal control power of the air conditioner.

2. The control method of the fresh air conditioner according to claim 1, characterized in that Before determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model, it includes: Constructing a multi-objective optimization model according to the total system power determined by the power of the air conditioner and the power of the fresh air machine, in combination with a first constraint condition and a second constraint condition; wherein, the first constraint condition is used to limit the environmental health index corresponding to the power of the air conditioner and the power of the fresh air machine within a preset index range, and the second constraint condition is used to limit the room temperature change rate corresponding to the power of the air conditioner and the power of the fresh air machine within a preset rate range.

3. The control method of the fresh air conditioner according to claim 2, wherein Determining the optimal control power of the fresh air machine and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model, includes: SA1, Selecting the power of the fresh air machine according to the indoor and outdoor environmental data, and determining the first total system power according to the power of the fresh air machine and the power of the air conditioner; SA2, Predicting the indoor environmental data and the power of the air conditioner at the target time according to the power of the fresh air machine and the indoor and outdoor environmental data, to obtain the indoor environmental prediction result and the predicted power of the air conditioner; SA3, Determining the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result according to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data; SA4, Updating the target optimization model according to the predicted power of the air conditioner and the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result, in combination with the first constraint condition and the second constraint condition, to obtain the total system power corresponding to the power of the fresh air machine, and comparing the total system power corresponding to the power of the fresh air machine with the first total system power. If the total system power corresponding to the power of the fresh air machine is greater than the first total system power, then updating the first total system power with the total system power corresponding to the power of the fresh air machine, otherwise retaining the first total system power; wherein, the total system power corresponding to the power of the fresh air machine is obtained according to the predicted power of the air conditioner and the power of the fresh air machine; SA5. Adjust the power of the fresh air unit according to the preset power adjustment strategy, and iterate steps SA2 - SA4 until the preset end condition is reached. Take the power of the fresh air unit corresponding to the minimum total system power and the predicted power of the air conditioner as the corresponding optimal control power of the fresh air unit and the optimal control power of the air conditioner. Among them, the preset power adjustment strategy is used to determine the adjustment power of the corresponding fresh air unit according to the magnitude of the total system power corresponding to the power of the corresponding fresh air unit and the upper and lower limits of the preset fresh air unit power adjustment.

4. The control method of the fresh air conditioner according to claim 3, wherein Predict the indoor environmental data and the power of the air conditioner at the target time according to the power of the fresh air unit and the indoor and outdoor environmental data, and obtain the indoor environmental prediction result, including: Input the power of the fresh air unit and the indoor and outdoor environmental data into the indoor environmental prediction model to obtain the indoor environmental prediction result output by the indoor environmental prediction model. Among them, the indoor environmental prediction model is trained according to the historical power of the fresh air unit, the historical indoor and outdoor environment, and their corresponding actual indoor environmental data and actual air conditioner power at the historical target time; or, Determine the predicted indoor carbon dioxide concentration corresponding to the target time according to the indoor carbon dioxide concentration in the indoor and outdoor environmental data and the preset target carbon dioxide concentration. Determine the first fine particle concentration entering the room after being filtered by the fresh air unit according to the outdoor fine particle concentration in the indoor and outdoor environmental data and the previously obtained fresh air unit filtration efficiency, and combine the indoor fine particle concentration in the indoor and outdoor environmental data and the target time to determine the predicted indoor fine particle concentration corresponding to the target time. Determine the predicted indoor temperature corresponding to the target time and the predicted power of the air conditioner corresponding to the predicted indoor temperature according to the indoor and outdoor temperatures in the indoor and outdoor environmental data and the previously obtained heat exchange efficiency of the air conditioner. Obtain the corresponding predicted indoor environmental data according to the predicted indoor carbon dioxide concentration, predicted indoor fine particle concentration, and predicted indoor temperature corresponding to the target time.

5. The control method of the fresh air conditioner according to claim 3, characterized in that, The predicted indoor environmental data includes the predicted indoor carbon dioxide concentration, predicted indoor fine particle concentration, and predicted indoor temperature. Determine the environmental health index and the room temperature change rate corresponding to the indoor environmental prediction result according to the indoor environmental prediction result and the indoor temperature in the indoor and outdoor environmental data, including: Determine the environmental health index according to the predicted indoor carbon dioxide concentration, predicted indoor fine particle concentration, and predicted indoor temperature, in combination with the preset weight dynamic allocation rule. Among them, the preset weight dynamic allocation rule is used to limit the allocation weights of the predicted indoor carbon dioxide concentration, predicted indoor fine particle concentration, and predicted indoor temperature corresponding to different time periods. Determine the room temperature change rate within the target time according to the predicted indoor temperature and the indoor temperature in the indoor and outdoor environmental data.

6. The control method of the fresh air conditioner according to any one of claims 1-5, characterized in that, The method further includes: Monitor the outdoor fine particle concentration. Determine whether the difference in the outdoor fine particle concentration within the first preset time period exceeds the first preset threshold. If the difference in outdoor fine particulate matter concentration exceeds the first preset threshold, adjust the power of the corresponding fresh air unit according to the change trend of the outdoor fine particulate matter concentration within the first preset duration, in combination with a preset power adjustment rule; wherein, the preset power adjustment rule is used to define the adjustment coefficients corresponding to the increasing trend and the decreasing trend respectively. Otherwise, retain the power of the corresponding fresh air unit.

7. The control method of the fresh air conditioner according to any one of claims 1-5, characterized in that, The method further includes: Monitoring the number of people indoors. Based on the number of people indoors, determining whether the preset fresh air unit trigger condition is met; wherein, the preset fresh air unit trigger condition is used to define that when the growth rate of the corresponding number of people indoors exceeds the second preset threshold, the ultra-fast mode of the fresh air unit is triggered. If the preset fresh air unit trigger condition is met, determine the wind speed to be adjusted based on the preset adjusted wind speed and the indoor number detection data, and adjust the fresh air unit according to the wind speed to be adjusted. Otherwise, retain the wind speed of the corresponding fresh air unit.

8. The control method of the fresh air conditioner according to claim 1, characterized in that, Obtain indoor and outdoor environmental data and the current power of the air conditioner, including: Collect the indoor carbon dioxide concentration, indoor and outdoor fine particulate matter concentrations, and indoor and outdoor temperatures to obtain indoor and outdoor environmental data. Obtain the power of the air conditioner. Filter outliers from the indoor and outdoor environmental data.

9. A control device for a fresh air conditioner, characterized in that, It includes: A data acquisition module that obtains indoor and outdoor environmental data and the power of the air conditioner, and the indoor and outdoor environmental data includes indoor and outdoor air quality data and indoor and outdoor temperature data. A multi-objective optimization module that determines the optimal control power of the fresh air unit and the optimal control power of the air conditioner according to the indoor and outdoor environmental data and the power of the air conditioner, in combination with a multi-objective optimization model; wherein, the multi-objective optimization model is previously constructed based on the total system power as the optimization target, and the total system power is obtained according to the power of the air conditioner and the power of the fresh air unit. An optimization control module that controls the operation of the corresponding fresh air unit and air conditioner according to the optimal control power of the fresh air unit and the optimal control power of the air conditioner.

10. An air conditioner, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the control method of the fresh air unit air conditioner according to any one of claims 1 to 8.

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