Patent Application
20250237400
The present application relates to the field of air conditioner control, and in particular to a method for controlling an air conditioner, an air conditioner, and a computer-readable storage medium.
Air conditioners consume a large proportion of electricity in home appliances, and low-power air conditioners are often more popular among consumers in the home appliance market. In the relevant technical solutions to reduce the power consumption of air conditioners, energy saving is often achieved by adjusting the operating frequency of the air conditioner, such as the common Ecology Conservation Optimization (ECO) mode.
However, the traditional way of achieving energy saving of air conditioners based on the operating frequency of the air conditioner is prone to fluctuations in the cooling capacity or cooling temperature of the air conditioner due to its backward feedback principle based on Genetic Algorithm (GA), that is, the execution logic of first detection and then execution, and there is a defect that over-temperature may occur.
The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art.
The main objective of the present application is to provide a method for controlling an air conditioner, aiming to solve at least the problem of how to avoid overheating of the air conditioner.
In order to achieve the above objective, the present application provides a method for controlling an air conditioner, including:
In an embodiment, the determining the target operating parameter combination that satisfies the target operating energy efficiency and/or the target output capacity according to the operating energy efficiency and/or the output capacity includes:
In an embodiment, in response to that there are more than two target operating parameter combinations, selecting one parameter combination as the target operating parameter combination according to a preset rule.
In an embodiment, the selecting one parameter combination as the target operating parameter combination according to the preset rule includes:
In an embodiment, the predicting the operating energy efficiency and/or the output capacity corresponding to each parameter combination of controllable operating parameters of the air conditioner includes:
In an embodiment, the determining the operating energy efficiency and/or output capacity corresponding to each of the parameter combinations according to the mapping relationship between the controllable operating parameters, the uncontrollable operating parameters, and the operating energy efficiency and/or the output capacity includes:
In an embodiment, the determining the operating energy efficiency and/or output capacity corresponding to each of the parameter combinations according to the mapping relationship between the controllable operating parameters, the uncontrollable operating parameters, and the operating energy efficiency and/or the output capacity includes:
In an embodiment, before the predicting the operating energy efficiency and/or the output capacity corresponding to the operating parameter combinations of a plurality of controllable operating parameters in a current working cycle of the air conditioner, the method further includes:
In addition, to achieve the above objective, the present application further provides an air conditioner, including a memory, a processor, and a program for controlling the air conditioner stored in the memory and executable on the processor, the program for controlling the air conditioner, when executed by the processor, implements the steps of the method for controlling air conditioner as described above.
In addition, to achieve the above objective, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a control program of an air conditioner, and when executed by a processor, the program for controlling the air conditioner implements the steps of the method for controlling air conditioner as described above.
Embodiments of the present application provides the method for controlling an air conditioner, the air conditioner, and the computer-readable storage medium. The method includes: obtaining uncontrollable operating parameters of the air conditioner; predicting, based on the uncontrollable operating parameters, an operating energy efficiency and/or an output capacity corresponding to each parameter combination of controllable operating parameters of the air conditioner; determining a target operating parameter combination that satisfies a target operating energy efficiency and/or a target output capacity according to the operating energy efficiency and/or the output capacity; and controlling the air conditioner to operate according to the target operating parameter combination. By constructing a capability and/or energy efficiency prediction model to control the operating capacity and/or operational energy efficiency strategy of the air conditioner, adjustments to operating parameters are made before overheating or frequency fluctuation of the air conditioner occurs, in contrast to the traditional GA algorithm's feedback mechanism, preventing the air conditioner from overheating, thereby meeting the thermal load requirements of the air conditioner under different working environments.
The realization of the purposes, functional features, and advantages of the present application will be further explained in conjunction with embodiments and with reference to the accompanying drawings.
At present, with the increasing demand for air conditioners, the power consumption of air conditioners is also increasing. When purchasing an air conditioner, in addition to considering comfort and convenience, power consumption of the air conditioner must also be taken into account, making energy-saving air conditioners a favorable choice. The existing energy-saving solutions for air conditioners are all based on backward feedback, that is, the operating frequency of the compressor is adjusted only when the indoor temperature exceeds or falls below the set temperature. In this way, it is easy for the temperature to fluctuate frequently before reaching the set temperature, or even to over-reach the temperature, which not only causes a poor user experience, but also fails to achieve an improvement in energy saving effects.
The present application aims to improve the energy-saving effect of air conditioners. The present application provides a method for controlling an air conditioner. Specifically, the present application realizes the control of operating energy efficiency and/or capacity by constructing a predictive energy efficiency and/or capacity model. Compared with the backward feedback principle of the traditional Genetic Algorithm (GA), the operating parameters are adjusted before overheating or frequency fluctuation of the air conditioner occurs, so as to avoid overheating of the air conditioner, thereby meeting the heat load of the air conditioner under different working environments.
In order to better understand the above technical solution, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.
As an implementation solution,
As shown in
Those skilled in the art will appreciate that the air conditioner structure shown in
As shown in
In the air conditioner shown in
In an embodiment, the air conditioner includes: a memory 1005, a processor 1001, and a program for controlling the air conditioner stored in the memory and executable on the processor, where:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
When the processor 1001 calls the program for controlling the air conditioner stored in the memory 1005, the following operations are performed:
According to the hardware structure of the air conditioner based on the above-mentioned air conditioning control technology, an embodiment of the method for controlling the air conditioner of the present application is provided.
As shown in
Step S10, obtaining uncontrollable operating parameters of the air conditioner;
Step S20, predicting, based on the uncontrollable operating parameters, an operating energy efficiency and/or an output capacity corresponding to each parameter combination of controllable operating parameters of the air conditioner.
In an embodiment, the uncontrollable operating parameters of the air conditioner are first obtained, and then based on the obtained uncontrollable operating parameters, according to the operating parameter combination formed by multiple controllable operating parameters in the current working cycle, a possible operating energy efficiency of the operating power of the air conditioner in the next cycle is predicted, and/or according to the operating parameter combination formed by multiple controllable operating parameters in the current working cycle, a possible output capacity of the operating power of the air conditioner in the next cycle is predicted.
It should be noted that the operating energy efficiency is the ratio between the power consumption and the cooling/heating capacity during the operation of the air conditioner. The output capacity is the quantitative value of the cooling/heating capacity of the air conditioner per unit time.
It should be noted that the controllable operating parameters include, for example, one or more of the internal fan speed, the external fan speed, or the compressor operating frequency. The controllable operating parameters can be set to correspond to one or more parameter combinations, and the size and number of parameter combinations corresponding to the controllable operating parameters of different models of air conditioners are different. If there are two or more controllable operating parameters, each parameter combination of the controllable operating parameters can constitute a parameter combination.
The air conditioner is preset with an interval working cycle T, and the operating parameters of the air conditioner are collected every preset interval cycle T. In an embodiment, the working cycle can be set to 30 seconds. The operating parameters of the air conditioner include controllable operating parameters and uncontrollable operating parameters. The controllable operating parameters are characterized as the controllable operating parameters of the air conditioner itself, such as the internal fan speed, the external fan speed and the compressor frequency, etc. The uncontrollable parameters are characterized as the uncontrollable parameters of the air conditioner itself, such as the indoor and outdoor temperature, the indoor and outdoor humidity, the exhaust valve temperature and other environmental parameters that affect the operation of the air conditioner but cannot be set, or the user-set parameters such as the target temperature and the set target wind speed. The operating energy efficiency is characterized as the power consumption during the operation of the air conditioner. The output capacity is characterized as the cooling capacity during the operation of the air conditioner. The operating energy efficiency is characterized as the predicted operating energy efficiency of the next cycle and the operating energy efficiency change value of the current operating energy efficiency. The output capacity is characterized as the output capacity change value of the predicted output capacity of the next cycle and the current output capacity.
In an embodiment, the operating energy efficiency may be determined by monitoring the power consumption on an electric meter associated with the air conditioner.
In an embodiment, the output capacity may be determined according to the operating frequency and the operating power of the air conditioner.
In an embodiment, the step of predicting the operating energy efficiency may be: first, obtaining a parameter combination of uncontrollable parameters in the air conditioner (including but not limited to indoor and outdoor temperature, indoor and outdoor humidity, exhaust valve temperature, set temperature, etc.), then determining each parameter combination of the controllable operating parameters of the air conditioner (including but not limited to the internal fan speed, the external fan speed and the compressor frequency, etc.), constructing a mapping relationship between the controllable operating parameters, the uncontrollable operating parameters and the operating energy efficiency, and based on the mapping relationship, determining the operating energy efficiency corresponding to each parameter combination.
In an embodiment, the step of predicting the output capacity may be: first, obtaining a parameter combination of uncontrollable parameters in the air conditioner (including but not limited to indoor and outdoor temperature, indoor and outdoor humidity, exhaust valve temperature, set temperature, etc.), then determining each parameter combination of the controllable operating parameters of the air conditioner (including but not limited to the internal fan speed, the external fan speed and the compressor frequency, etc.), constructing a mapping relationship between the controllable operating parameters, the uncontrollable operating parameters and the output capacity, and based on the mapping relationship, determining the output capacity corresponding to each parameter combination.
In an embodiment, taking the operation energy efficiency as an example, in some embodiments, it is assumed that the air conditioner is in the fifth cycle (i.e., 120-150 seconds after startup), and the uncontrollable operating parameters obtained in the current cycle are: indoor temperature Tin5=27.6, outdoor temperature Tout5=34.3, indoor humidity Hin5=62, outdoor humidity Hout5-65, exhaust valve temperature Tp5=45, user set temperature Ts5=24, user set wind speed Ws5-60, and then add the statistics of the first to fifth cycle: average indoor temperature Avg(Tin)=28.3, maximum compressor operating frequency Max(Pr)=46, and use the above parameters as the characteristics of cycle 5. Then the controllable operating parameters obtained are: indoor fan speed Sin=1200, outdoor fan speed Sout=820, and compressor frequency Pr=50.
Then, the historical running combination (Tin, Tout, Hin, Hout, Tp, Ts, Ws, Sin, Sout, Pr) is obtained.
The operating energy efficiency Q5 of the air conditioner in the working cycle is 6400. The above historical parameter combination is used as the independent variable, and the operating energy efficiency Q5 is used as the dependent variable. The energy efficiency model yi(Q) reflecting the mapping relationship between the historical parameter combination and the historical operating energy efficiency is trained using the machine learning/deep learning algorithm:
yi(Q)=fi(Tin, Tout, Hin, Hout, Tp, Ts, Ws, Sin, Sout, Pr)
Based on the energy efficiency model yi(Q), the operating energy efficiency of the sixth cycle (i.e., 150-180 seconds after startup) is predicted to be Q6=6300.
It should be noted that the output capability determined based on the capability model is similar and will not be repeated here.
Step S30, determining a target operating parameter combination that satisfies a target operating energy efficiency and/or a target output capacity according to the operating energy efficiency and/or the output capacity;
In an embodiment, after the operation energy efficiency and/or the output capacity are predicted, a target operating parameter combination of the air conditioner that satisfies the next working cycle is determined according to the operation energy efficiency and/or the output capacity.
In an embodiment, if the prediction is for operating energy efficiency, the step of determining the target operating parameter combination may be: determining, based on a preset energy efficiency prediction model, each operating energy efficiency predicted in a current cycle, determining a parameter combination corresponding to an operating energy efficiency greater than a preset energy efficiency value among each of the operating energy efficiencies; and determining a parameter combination that satisfies the target operating energy efficiency as the target operating parameter combination.
In an embodiment, if the prediction is for output capacity, the step of determining the target operating parameter combination may be: determining, based on a preset capacity prediction model, each output capacity predicted in the current cycle, determining a parameter combination corresponding to an output capacity greater than a preset output capacity value among each of the output capacities, and determining the parameter combination that satisfies the target output capacity as the target operating parameter combination.
In an embodiment, if the prediction is for operating energy efficiency and output capacity, the step of determining the target operating parameter combination may be: determining each operating energy efficiency predicted for the current cycle based on a preset energy efficiency prediction model, and determining each output capacity predicted for the current cycle based on a preset capacity prediction model, and then determining each operating energy efficiency and each output capacity predicted for the current cycle, determining, among each operating energy efficiency and each output capacity, a parameter combination corresponding to an operating energy efficiency and an output capacity that are both greater than a preset energy efficiency value and a preset output capacity value, and using the parameter combination as the target operating parameter combination.
In an embodiment, the controllable operating parameters may include at least two, the predicted operating power variation corresponds to a parameter combination including respective parameter combinations of all controllable operating parameters.
In an embodiment, in order to make the power consumption of the air conditioner sufficiently low while maintaining the operating energy efficiency as high as possible, the preset rule may be: taking the parameter combination with the smallest frequency change of the air conditioner compressor as the target operating parameter combination.
Step S40: controlling the air conditioner to operate according to the target operating parameter combination.
In an embodiment, after the target operating parameter combination is determined, the air conditioner is controlled to operate according to the determined target operating parameter combination.
In the technical solution provided in this embodiment, the operating energy efficiency and/or output capacity corresponding to the controllable operating parameters of the air conditioner are predicted, and the target operating parameter combination that meets the target operating power is determined according to the operating energy efficiency and/or output capacity. The air conditioner is then controlled to operate according to the target operating parameter combination. The operating energy efficiency and/or capacity control is achieved by constructing a predictive energy efficiency and/or capacity model. Compared with the backward feedback principle of the traditional GA algorithm, the operating parameters are adjusted before overheating or frequency fluctuation of the air conditioner occurs, so as to avoid overheating of the air conditioner and thereby meet the heat load of the air conditioner under different working environments.
In addition, as another implementation solution, the flowchart of the second embodiment of the method for controlling the air conditioner of the present application can be shown in
In an embodiment, during the operation of the air conditioner, part of the operation data of the air conditioner is collected at intervals, including the operating status, user settings and working settings. The operating status includes indoor temperature, outdoor temperature, indoor humidity, outdoor humidity Hout, exhaust valve temperature, which are parameters that affect the operation of the air conditioner but cannot be set. The user settings include the set temperature, set wind speed and other parameters actively set by the user. The working settings include the internal fan speed, the external fan speed, the compressor operating frequency and other parameters set by the air conditioner itself. Then, the working setting parameters of the air conditioner are changed to obtain a variety of operating parameter combinations, for example, combination 1, combination 2 . . . combination N. Based on the above collected operating data, the features in the combination are extracted, and then the output capacity Q/operating energy efficiency E (i.e., target operating energy efficiency/target output capacity) of the combination is predicted according to the features. The prediction method is to predict through a preset capacity/energy efficiency prediction model. The training steps of the capacity/energy efficiency prediction model are as follows: collecting the historical operating data of the air conditioner, the historical operating data including the historical operating status, historical user settings and historical working settings, and then extracting the feature data in the historical operating data, taking the feature data as the independent variable, taking the historical operating power of the air conditioner as the dependent variable, and inputting the independent variable and the dependent variable into the power prediction model for training; and controlling the air conditioner to operate according to the control strategy corresponding to the capacity/energy efficiency (i.e., the operating parameters corresponding to the target operating capacity/operating energy efficiency).
In addition, it can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the air conditioner to implement the process steps of the embodiment of the above method.
Therefore, the present application also provides a computer-readable storage medium, which stores a program for controlling an air conditioner. When the program for controlling the air conditioner is executed by a processor, the steps of the method for controlling the air conditioner described in the above embodiment are implemented.
The computer-readable storage medium may be a universal serial bus (USB) flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage medium that can store program codes.
It should be noted that since the storage medium provided in the embodiment of the present application is the storage medium used to implement the method of the embodiment of the present application, based on the method introduced in the embodiment of the present application, those skilled in the art can understand the specific structure and deformation of the storage medium, so it is not repeated here. All storage medium used in the method of the embodiment of the present application belong to the scope of protection of the present application.
Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage medium (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer-usable program codes.
The present application is described with reference to the flowcharts and/or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the processes and/or boxes in the flowchart and/or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate a device for implementing the functions specified in one process or multiple processes in the flowchart and/or one box or multiple boxes in the block diagram.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
It should be noted that in the claims, any reference signs placed between brackets shall not be construed as limiting the claims. The word “comprising” does not exclude the presence of components or steps not listed in the claims. The word “a” or “an” preceding a component does not exclude the presence of a plurality of such components. The present application may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc., does not indicate any order. These words may be interpreted as names.
Although some embodiments of the present application have been described, those skilled in the art, once aware of the basic inventive concept, may make further changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as encompassing the embodiments as well as all changes and modifications that fall within the scope of the present application.
It is apparent that those skilled in the art may make various modifications and variations to the present application without departing from its spirit and scope. Accordingly, if such modifications and variations fall within the scope of the claims of the present application and their equivalents, the present application is also intended to encompass these modifications and variations.
| Number | Date | Country | Kind |
|---|---|---|---|
| 202211243266.X | Oct 2022 | CN | national |
This application is a continuation application of PCT International Patent Application No. PCT/CN2023/104218 filed on Jun. 29, 2023, which claims priority to and benefits of Chinese Patent Application No. 202211243266.X filed on Oct. 11, 2022, the entire contents of each of which are incorporated herein by reference for all purposes. No new matter has been introduced.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/CN2023/104218 | Jun 2023 | WO |
| Child | 19174415 | US |
