CN115654675A

CN115654675A - Air conditioner operation parameter recommendation method and related equipment

Info

Publication number: CN115654675A
Application number: CN202211129613.6A
Authority: CN
Inventors: 陈超; 梁勇超; 袁文昭; 高旭; 邵禹琦; 曾键凯
Original assignee: TCL Air Conditioner Zhongshan Co Ltd
Current assignee: TCL Air Conditioner Zhongshan Co Ltd
Priority date: 2022-09-16
Filing date: 2022-09-16
Publication date: 2023-01-31

Abstract

The application discloses an air conditioner operation parameter recommendation method and related equipment, which can select a target space model corresponding to a target indoor environment from preset space models based on temperature change information of the target indoor environment where an air conditioner is located; estimating the refrigerating capacity of the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperatures corresponding to the air conditioner and the set target temperature; collecting object characteristic information of a target object using an air conditioner; analyzing the human body comfort level of the target object through the object characteristic information to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the target object using the air conditioner, and recommending air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object. The method and the device can improve the accuracy of recommending the air conditioner operation parameters, effectively reduce user operation and enhance the comfort of the user.

Description

Air conditioner operation parameter recommendation method and related equipment

Technical Field

The application relates to the technical field of air conditioners, in particular to an air conditioner operation parameter recommendation method and related equipment.

Background

Along with the increasing improvement of the living standard of people, intelligent household electrical appliances are more and more popular, and the market share of the intelligent air conditioner is also rapidly promoted. The current intelligent air conditioner generally determines recommended operating parameters only based on indoor and outdoor ambient temperature, humidity and target temperature set by a user, so that the user controls the air conditioner according to the recommended operating parameters; under the recommended operation parameters, the air conditioner can achieve faster refrigerating and heating effects, but the scheme is simpler, the recommendation accuracy of the operation parameters of the air conditioner is lower, and the improvement of the comfort level of a user is not facilitated.

Therefore, how to further improve the accuracy of air conditioner parameter recommendation to improve the user experience is a technical problem to be solved at present.

Disclosure of Invention

The embodiment of the application provides an air conditioner operation parameter recommendation method and related equipment, wherein the related equipment can comprise an air conditioner operation parameter recommendation device, electronic equipment, a computer readable storage medium and a computer program product, the accuracy of air conditioner operation parameter recommendation can be improved, user operation is effectively reduced, and the comfort level of a user is enhanced.

The embodiment of the application provides an air conditioner operation parameter recommendation method, which comprises the following steps:

acquiring temperature change information of a target indoor environment where an air conditioner is located, and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information;

estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature;

collecting object characteristic information of a target object using the air conditioner;

analyzing the human body comfort degree of the target object through the object characteristic information to obtain a target comfort temperature matched with the target object;

and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

Correspondingly, the embodiment of the application provides an air conditioner operating parameter recommendation device, including:

the system comprises an acquisition unit, a storage unit and a control unit, wherein the acquisition unit is used for acquiring temperature change information of a target indoor environment where an air conditioner is located and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information;

the pre-estimation unit is used for pre-estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature;

an acquisition unit for acquiring object characteristic information of a target object using the air conditioner;

the analysis unit is used for carrying out human body comfort degree analysis on the target object through the object characteristic information to obtain a target comfort temperature matched with the target object;

and the recommending unit is used for correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

Optionally, in some embodiments of the present application, the obtaining unit may include a model obtaining subunit, a calculating subunit, and a selecting subunit, as follows:

the model obtaining subunit is used for obtaining at least one preset space model, and different preset space models correspond to different air conditioner use scenes;

the calculation subunit is used for calculating the similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to each preset space model;

and the selecting subunit is used for selecting a target space model corresponding to the target indoor environment from the preset space models according to the similarity.

Optionally, in some embodiments of the present application, the recommending unit may include an estimating subunit and a cooling capacity correcting subunit, as follows:

the pre-estimation subunit is used for pre-estimating the temperature distribution information of the target indoor environment in a preset time period under the operation of the air conditioner according to the refrigerating capacity;

and the refrigerating capacity correction subunit is used for correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature, the temperature distribution information and the historical behavior information of the air conditioner used by the target object.

Optionally, in some embodiments of the present application, the estimation unit may be specifically configured to calculate a refrigerant flow rate of the air conditioner according to a suction density, a volumetric efficiency and an operating efficiency of a compressor of the air conditioner; and estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition according to the refrigerant flow of the air conditioner, the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature.

Optionally, in some embodiments of the present application, the analysis unit may include a first obtaining subunit, a comparing subunit, and a first determining subunit, as follows:

the first acquiring subunit is configured to acquire reference characteristic information of at least one reference object and a corresponding reference comfort temperature;

a comparison subunit, configured to perform comparison processing on at least one dimension of human comfort on the reference characteristic information and the object characteristic information;

and the first determining subunit is used for determining a target comfortable temperature matched with the target object from the reference comfortable temperatures according to the comparison result.

Optionally, in some embodiments of the present application, the recommending unit may include a second obtaining subunit, a second determining subunit, and a modifying subunit, as follows:

the second obtaining subunit is configured to obtain historical behavior information of the target object using an air conditioner, where the historical behavior information includes behavior information of the target object in at least one historical usage scenario;

the second determining subunit is used for determining behavior information in a target historical use scene from the historical behavior information according to the scene that the target object uses the air conditioner currently;

and the correction subunit is used for correcting the refrigerating capacity of the air conditioner based on the target comfortable temperature and the behavior information under the target historical use scene.

The electronic device provided by the embodiment of the application comprises a processor and a memory, wherein the memory stores a plurality of instructions, and the processor loads the instructions to execute the steps in the air conditioner operation parameter recommendation method provided by the embodiment of the application.

The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the method for recommending air conditioner operating parameters provided in the embodiment of the present application.

In addition, a computer program product is further provided in an embodiment of the present application, and includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the steps in the air conditioner operation parameter recommendation method provided in an embodiment of the present application are implemented.

The embodiment of the application provides an air conditioner operation parameter recommendation method and related equipment, which can acquire temperature change information of a target indoor environment where an air conditioner is located, and select a target space model corresponding to the target indoor environment from preset space models based on the temperature change information; based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition; collecting object characteristic information of a target object using the air conditioner; analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object. The method and the device can determine the recommended operating parameters of the air conditioner by combining the target space model of the indoor environment where the air conditioner is located, the object characteristic information and the historical behavior information of the user, so that the accuracy of recommending the operating parameters of the air conditioner is improved, the user operation is effectively reduced, and the comfort level of the user is enhanced.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1a is a scene schematic diagram of an air conditioner operation parameter recommendation method provided in an embodiment of the present application;

fig. 1b is a flowchart of an air conditioner operation parameter recommendation method provided in an embodiment of the present application;

fig. 1c is another flowchart of an air conditioner operation parameter recommendation method according to an embodiment of the present application;

fig. 1d is another flowchart of an air conditioner operation parameter recommendation method according to an embodiment of the present application;

fig. 2 is another flowchart of an air conditioner operation parameter recommendation method provided in an embodiment of the present application;

fig. 3 is a schematic structural diagram of an air conditioner operation parameter recommendation device according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The embodiment of the application provides an air conditioner operation parameter recommendation method and related equipment, and the related equipment can comprise an air conditioner operation parameter recommendation device, electronic equipment, a computer readable storage medium and a computer program product. The air conditioner operation parameter recommending device can be specifically integrated in electronic equipment, and the electronic equipment can be equipment such as a terminal or a server.

It is understood that the air conditioner operation parameter recommendation method of the present embodiment may be executed on the terminal, or may be executed by both the terminal and the server. The above examples should not be construed as limiting the present application.

As shown in fig. 1a, a method for recommending air conditioner operation parameters by a terminal and a server is taken as an example. The air conditioner operation parameter recommendation system provided by the embodiment of the application comprises a terminal 10, a server 11 and the like; the terminal 10 and the server 11 are connected via a network, for example, a wired or wireless network connection, wherein the air conditioner operation parameter recommendation device may be integrated in the terminal.

Wherein, the terminal 10 may be configured to: acquiring object characteristic information of a target object using an air conditioner, and acquiring temperature change information of a target indoor environment where the air conditioner is located, indoor and outdoor environment temperatures and a set target temperature; and transmits the object characteristic information, the temperature change information, the indoor and outdoor ambient temperatures, and the target temperature to the server 11 so that the server 11 determines recommended operation parameters of the air conditioner based on these data; the terminal 10 may also be configured to receive an air conditioner operation parameter corresponding to the corrected cooling capacity sent by the server 11, and recommend the air conditioner operation parameter to the user. The terminal 10 may include a smart air conditioner, a mobile phone, a tablet computer, a notebook computer, a personal computer, or the like.

The server 11 may be configured to: acquiring temperature change information of a target indoor environment where an air conditioner is located, and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information; based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition; collecting object characteristic information of a target object using the air conditioner; analyzing the human body comfort degree of the target object through the object characteristic information to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the terminal 10. The server 11 may be a single server, or a server cluster or a cloud server composed of a plurality of servers.

The embodiment of the application provides an air conditioner operation parameter recommendation method, and relates to a computer vision technology in the field of artificial intelligence.

Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence. Artificial intelligence is the research of the design principle and the realization method of various intelligent machines, so that the machines have the functions of perception, reasoning and decision making. The artificial intelligence technology is a comprehensive subject, and relates to the field of extensive technology, namely the technology of a hardware level and the technology of a software level. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning, automatic driving, intelligent traffic and the like.

Computer Vision technology (CV) is a science for researching how to make a machine look, and more specifically, it refers to that a camera and a Computer are used to replace human eyes to perform machine Vision such as identification, tracking and measurement on a target, and further perform graphic processing, so that the Computer processing becomes an image more suitable for human eyes to observe or transmitted to an instrument to detect. As a scientific discipline, computer vision research-related theories and techniques attempt to build artificial intelligence systems that can capture information from images or multidimensional data. The computer vision technology generally includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content/behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, synchronous positioning and map construction, automatic driving, intelligent transportation and other technologies, and also includes common biometric identification technologies such as face recognition and fingerprint recognition.

The air conditioner operation parameter recommendation method provided by the embodiment of the application further relates to a big data direction in the technical field of cloud.

The Cloud technology (Cloud technology) is a hosting technology for unifying series resources such as hardware, software, network and the like in a wide area network or a local area network to realize calculation, storage, processing and sharing of data. The cloud technology is a general term of network technology, information technology, integration technology, management platform technology, application technology and the like applied based on a cloud computing business model, can form a resource pool, is used as required, and is flexible and convenient. Cloud computing technology will become an important support. Background services of technical network systems require a large amount of computing and storage resources, such as video websites, picture-like websites and more portal websites. With the high development and application of the internet industry, each article may have its own identification mark and needs to be transmitted to a background system for logic processing, data in different levels are processed separately, and various industrial data need strong system background support and can only be realized through cloud computing.

The Big data (Big data) refers to a data set which cannot be captured, managed and processed by a conventional software tool within a certain time range, and is a massive, high-growth-rate and diversified information asset which can have stronger decision-making power, insight discovery power and flow optimization capability only by a new processing mode. With the advent of the cloud era, big data has attracted more and more attention, and the big data needs special technology to effectively process a large amount of data within a tolerance elapsed time. The method is suitable for technologies of big data, including a large-scale parallel processing database, data mining, a distributed file system, a distributed database, a cloud computing platform, the Internet and an extensible storage system.

The following are detailed below. It should be noted that the following description of the embodiments is not intended to limit the preferred order of the embodiments.

The present embodiment will be described in terms of an air conditioner operation parameter recommendation device, which may be specifically integrated in an electronic device, where the electronic device may be a server or a terminal.

As shown in fig. 1b, a specific process of the air conditioner operation parameter recommendation method may be as follows:

101. the method comprises the steps of obtaining temperature change information of a target indoor environment where an air conditioner is located, and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information.

The temperature change information may specifically include a temperature rise time and a temperature fall time of a target indoor environment where the air conditioner is located. The temperature rise time refers to a temperature rise time, and the temperature fall time refers to a temperature fall time.

In this embodiment, the spatial structure of the environment may be determined according to the temperature change information of the current environment. It can be understood that under the condition that the air-conditioning operation parameters are the same, the use comfort of users may be different under the air-conditioning operation environments with different space structures. The embodiment can determine the recommended air conditioner operation parameters by combining with the target space model corresponding to the air conditioner operation environment, so that the comfort level of a user is improved.

Optionally, in this embodiment, the step of "selecting the target space model corresponding to the target indoor environment from preset space models based on the temperature change information" may include:

acquiring at least one preset space model, wherein different preset space models correspond to different air conditioner use scenes;

calculating the similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to each preset space model;

and selecting a target space model corresponding to the target indoor environment from the preset space models according to the similarity.

The air conditioner usage scenario corresponding to the preset space model may include an inner ring temperature, an outer ring temperature, a temperature set by a user, and the like, which is not limited in this embodiment. The inner loop temperature may refer to the indoor ambient temperature and the outer loop temperature may refer to the outdoor ambient temperature.

Before calculating the similarity, a model with the same or similar air conditioner use scene as the current air conditioner operation scene may be selected from the preset space models, the models are used as candidate space models, and then the similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to the candidate space models is calculated, so as to select the target space model corresponding to the target indoor environment from the candidate space models according to the similarity.

The similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to the preset space model may specifically be a difference between the temperature rise time and the temperature fall time corresponding to the target indoor environment and the temperature rise time and the temperature fall time corresponding to the preset space model, and the larger the difference is, the lower the similarity is; conversely, the smaller the difference, the higher the similarity. In this embodiment, the preset space model in which the air conditioner usage scenarios are the same and the similarity of the temperature change information is greater than the preset similarity may be used as the target space model corresponding to the target indoor environment.

In some embodiments, the preset space model in which the difference between the temperature rise time and the temperature fall time is smaller than the preset value and the similarity of the air conditioner use scene is greater than the preset similarity may be selected as the target space model corresponding to the target indoor environment. The preset value and the preset similarity may be set according to actual situations, which is not limited in this embodiment. For example, the setting can be performed according to the accuracy requirement recommended for the air conditioner operation parameters, and if the requirement for the accuracy is higher, the preset value can be set to be smaller, and the preset similarity can be set to be larger.

In a specific embodiment, a room space model (i.e., a target space model in the above-mentioned embodiment) corresponding to the current air conditioner operation may be established, specifically, the air conditioner operates at a set temperature (e.g., 27 ℃) for a period of time, and records the room temperature rise time and the room temperature fall time, and then, the temperature rise time and the temperature fall time of the rooms in the similar scene may be compared with the big data in the same area, and the closer the time, the more similar the room space model is determined to be, and the building load is equivalent. For example, a room in the same town as the target indoor environment may be obtained, a room in which the usage scene of the air conditioner is similar to the target indoor environment may be used as a candidate space model, the temperature rise time and the temperature fall time of the candidate space model may be recorded, and the temperature rise time and the temperature fall time of the candidate space model may be compared with the temperature rise time and the temperature fall time of the target indoor environment, so as to determine the target space model corresponding to the target indoor environment.

102. And estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets the preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and the set target temperature.

The indoor and outdoor ambient temperatures may include an indoor ambient temperature and an outdoor ambient temperature, and the target temperature is a temperature corresponding to an air conditioner set by a user (i.e., a target object).

The refrigerating capacity of the air conditioner is specifically the heat exchange capacity when the temperature of the target indoor environment meets the preset temperature change condition, namely the temperature rise and the temperature drop of the target indoor environment. The preset temperature variation condition may be specifically that the indoor temperature is maintained within a certain variation range during the operation of the air conditioner, and the variation range may be determined according to actual conditions.

In some embodiments, the heat exchange amount required when the room meets temperature rise and temperature drop can be estimated through a flow method according to a target space model corresponding to the room, the current inner ring temperature, the current outer ring temperature and the user set temperature. The flow method is an estimation calculation mode of the refrigerating capacity of the air conditioner, and in order to ensure that the user using behavior and the actual using state of the air conditioner are unchanged, interference to the user is avoided, and no additional device is added, the flow of the refrigerant can be indirectly calculated by adopting a compressor volumetric efficiency method in the embodiment, so that the refrigerating capacity of the air conditioner is deduced.

Optionally, in this embodiment, the step of estimating, based on the target space model, the indoor and outdoor environment temperatures corresponding to the air conditioner, and the set target temperature, the cooling capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition may include:

calculating the refrigerant flow of the air conditioner according to the suction density, the volumetric efficiency and the operating efficiency of a compressor of the air conditioner;

and estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition according to the refrigerant flow of the air conditioner, the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature.

The refrigerant flow rate may specifically be a cooling capacity per second of the air conditioner.

The calculation process of estimating the refrigerant flow based on the compressor volumetric efficiency method can be as shown in formula (1):

m _ref ＝ρ _ref ×(η _v V _d )×f (1)

wherein m is _ref Which indicates the flow rate of the refrigerant of the air conditioner,ρ _ref for the suction density of the compressor, the unit may be kg/m ³ ；η _v Is volume efficiency; v _d The unit of the theoretical volume gas transmission can be m ³ S; f is the compressor frequency and can be in units of 1/s.

Wherein the volumetric efficiency may be a ratio of an actual air output to a theoretical air output of the air conditioner. The present embodiment can calculate the refrigerant flow rate of the air conditioner by combining the suction density, the volumetric efficiency and the operating frequency of the compressor. In addition, in some embodiments, the relative clearance volume correction, the linear function of the compressor motor speed, and the like can also be considered in the calculation process of the refrigerant flow.

103. Object feature information of a target object using the air conditioner is collected.

There may be one or more target objects using the air conditioner. Specifically, the present embodiment may perform recommendation of the air conditioner operation parameters in combination with the object feature information of the user, which is beneficial to improving the accuracy of recommendation.

The object feature information may include the age, sex, and scene mode of each target object, where the scene mode may include a sleep mode, a sport mode, a sedentary mode, and the like.

In some embodiments, object characteristic information of the target object may be collected by an infrared sensor.

104. And analyzing the comfort level of the target object through the characteristic information of the object to obtain a target comfort temperature matched with the target object.

Optionally, in this embodiment, the step of performing human comfort analysis on the target object through the object feature information to obtain a target comfort temperature matched with the target object may include:

acquiring reference characteristic information of at least one reference object and corresponding reference comfortable temperature;

comparing the reference characteristic information with the object characteristic information in at least one human body comfort degree dimension;

and determining a target comfortable temperature matched with the target object from the reference comfortable temperatures according to the comparison result.

The reference characteristic information of the reference object may include an age, a sex, and a scene mode of the reference object. The reference characteristic information of the reference object can be obtained through big data acquisition. The reference comfort temperature corresponding to the reference object is specifically a comfort temperature of the reference object corresponding to the specific scene mode.

Wherein, the at least one human comfort dimension may include a comfort dimension in terms of age, a comfort dimension in terms of gender, a comfort dimension in terms of scene mode, and the like.

Through the comparison processing, the reference characteristic information matched with the object characteristic information of the target object can be determined, and the reference comfortable temperature of the reference object corresponding to the reference characteristic information is determined as the target comfortable temperature.

In some embodiments, the object feature information of the target object may be acquired by a sensor, and the object feature information may specifically include: user age (e.g., child, adult, elderly), gender (male, female), usage scenario pattern, and the like. Then, obtaining a target comfortable temperature matched with the target object by comparing the target comfortable temperature with the big data; therefore, the refrigerating capacity of different use scenes can be corrected according to the target comfortable temperature and different use crowds, and the correction mode can comprise the improvement of the heat exchange capacity or the reduction of the heat exchange capacity.

Specifically, an image including the target object may be acquired by the image sensor, and then image recognition may be performed, and for the image recognition result, object feature information of the target object may be acquired.

For example, the big data comparison shows that the old people are at a comfortable temperature of a room of 28 ℃ in a sleep mode, the ordinary adults are at a comfortable temperature of the room of 26 ℃ in the sleep mode, and after the heat exchange quantity of the air conditioner is obtained through estimation, the output refrigerating capacity of the air conditioner can be improved according to the collected object characteristic information, and the comfort model of the air conditioner is corrected.

105. And correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

Optionally, in this embodiment, the step of "correcting the cooling capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the target object using the air conditioner" may include:

estimating temperature distribution information of the target indoor environment in a preset time period under the operation of the air conditioner according to the refrigerating capacity;

and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature, the temperature distribution information and the historical behavior information of the target object using the air conditioner.

The preset time period may be one hour or two hours, and the present embodiment does not limit this.

In the embodiment, the required refrigerating capacity of the air conditioner can be estimated according to the current corresponding target space model, indoor and outdoor environment temperature and set target temperature, and further the room temperature distribution condition under the accumulated running time of 1h, 2h, 8230, 8230and 6h (hours) of the room can be estimated. Based on the temperature distribution information, whether the indoor temperature is uniformly distributed (if the upper and lower layers are layered) or not and whether the temperature is too high or too low can be known; so that the cooling capacity can be corrected according to the temperature distribution information.

In some embodiments, temperature distribution information may be collected by an infrared sensor.

acquiring historical behavior information of the target object using an air conditioner, wherein the historical behavior information comprises behavior information of the target object in at least one historical use scene;

according to the scene that the target object uses the air conditioner currently, behavior information under a target historical use scene is determined from the historical behavior information;

and correcting the refrigerating capacity of the air conditioner based on the target comfortable temperature and the behavior information under the target historical use scene.

The historical usage scenario may include indoor and outdoor ambient temperatures, a set target temperature, and a scenario mode in which the target object is located when the user uses the air conditioner within the historical time period. The behavior information in the historical usage scenario may specifically be behaviors of the target object to increase or decrease the set temperature, the windshield, shut down, and the like to change the setting of the air conditioner.

Wherein, the historical use scene matched with the current scene using the air conditioner can be used as the target historical use scene; and then, based on the behavior information under the target historical use scene and the target comfortable temperature, the refrigerating capacity of the air conditioner is corrected.

Optionally, in some embodiments, the usage habits of the user can be learned through big data, so that the air conditioner can directly operate according to similar scenes when being started next time.

In this embodiment, the refrigerating capacity output by the air conditioner may be corrected by a comfort model, specifically, the comfort model is a model established based on big data, and it may analyze the human comfort of the target object by the object feature information to obtain a target comfort temperature matching the target object; and the refrigerating capacity of the air conditioner can be corrected according to the target comfortable temperature and the historical behavior information of the target object using the air conditioner.

According to the air conditioner operation parameter recommendation method, the using habits of the users, the using crowds, the cold and hot sensitivity of the users and the conditions (such as the area) of the rooms where the users are located can be obtained through big data, the refrigerating capacity needed by an air conditioning system is estimated by comparing the using scenes with similar regionality or history, a comfort model of the room is established, comfortable and energy-saving air conditioner operation parameters are intelligently recommended to the users, and therefore the using comfort of the users can be improved.

In an embodiment, as shown in fig. 1c, a flowchart corresponding to the air conditioner operation parameter recommendation method provided in the present application is specifically described as follows:

1. in the air conditioner operation stage, a room space model (namely, the target space model in the above embodiment) is established by comparing the temperature rise or temperature drop time of the room under the condition of the similar inner ring, the similar outer ring and the user-set temperature;

2. estimating the refrigerating capacity required to be output by the air conditioner through a flow method;

3. acquiring object characteristic information corresponding to a user through a sensor, and comparing the object characteristic information with big data to obtain a target comfortable temperature meeting the requirements of the user in the current use scene;

4. and correcting the refrigerating capacity of the air conditioner according to the use behavior habit of the user, and uploading corresponding parameters to the cloud.

In a specific embodiment, after the air conditioner is operated for a period of time, behaviors that a user raises or lowers a set temperature, a windshield, a shutdown and the like to change the air conditioner setting may occur, a heat exchange amount output by the air conditioner before the air conditioner setting is changed and a room temperature distribution condition may be preliminarily calculated, and it is determined that the heat exchange amount (i.e., a cooling amount) output by the air conditioner at the time is low or high, that is, the heat exchange amount output by the current air conditioner does not meet a user use requirement, and meanwhile, the heat exchange amount output by the current air conditioner may be transmitted to a comfort model as a reference for correcting the comfort model.

For example, as shown in fig. 1d, after the air conditioner is turned on, the operating frequency F of the air conditioning system and the current usage scenario may be recorded, and before the user changes the setting of the air conditioner, the cooling capacity Q1 output by the air conditioner within the operating time t1 may be calculated by using a refrigerant flow method, where the specific calculation process is as described in the foregoing embodiment and is not described herein again. Then, comparing the refrigerating output Q of the air conditioner in the running time t under the same use scene, and the temperature of the upper layer and the lower layer of the room is uniformly distributed; when Q1 is less than Q, the current output refrigerating capacity is low, and the room temperature is layered, otherwise, when Q1 is greater than Q, the current output refrigerating capacity is high.

If the user changes the set temperature, it may be determined whether the user increases or decreases the set temperature of the air conditioner based on a difference between the set temperature before the change and the set temperature after the change. If the difference between the two is less than zero, the temperature is increased, and the output cooling capacity Q1 of the current air conditioner is larger than the requirement of a user, then under the same scene encountered by the air conditioner, the frequency of the compressor can be reduced by XHz on the basis of the operation time t1 and the frequency F of the compressor, and X can be determined according to the actual situation. If the difference between the two is greater than zero, the temperature is turned down, and the output cooling capacity Q1 of the current air conditioner is smaller than the requirement of a user, then under the same scene encountered by the air conditioner, the frequency of the compressor can be increased by XHz on the basis of the operation time t1 and the frequency F of the compressor.

Optionally, in this embodiment, corresponding feature extraction may be performed on all user control data of the air conditioners in each area, so as to formulate an overall control strategy of the air conditioners in each area in a corresponding time period and in a corresponding weather.

As can be seen from the above, in this embodiment, temperature change information of a target indoor environment where an air conditioner is located may be obtained, and based on the temperature change information, a target space model corresponding to the target indoor environment is selected from preset space models; based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition; collecting object characteristic information of a target object using the air conditioner; analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object. According to the method and the device, the recommended operation parameters of the air conditioner can be determined by combining the target space model of the indoor environment where the air conditioner is located, the object characteristic information and the historical behavior information of the user, so that the accuracy of recommending the operation parameters of the air conditioner is improved, the user operation is effectively reduced, and the comfort level of the user is enhanced.

The following is a detailed description of an example in which the air conditioner operation parameter recommendation device is specifically integrated in a server according to the method described in the previous embodiment.

An embodiment of the present application provides an air conditioner operation parameter recommendation method, as shown in fig. 2, a specific process of the air conditioner operation parameter recommendation method may be as follows:

201. the server acquires temperature change information of a target indoor environment where the air conditioner is located, and selects a target space model corresponding to the target indoor environment from preset space models based on the temperature change information.

Optionally, in this embodiment, the step "selecting, based on the temperature change information, a target space model corresponding to the target indoor environment from preset space models" may include:

The air conditioner usage scenario corresponding to the preset space model may include an inner ring temperature, an outer ring temperature, a temperature set by a user, and the like, which is not limited in this embodiment.

Before calculating the similarity, models in which the air conditioner using scene is the same as or similar to the current air conditioner operating scene may be selected from the preset space models, the models are used as candidate space models, and then the similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to the candidate space models is calculated, so that the target space model corresponding to the target indoor environment is selected from the candidate space models according to the similarity.

202. And the server pre-estimates the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets the preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and the set target temperature.

The refrigerating capacity of the air conditioner is specifically the heat exchange capacity when the temperature of the target indoor environment meets the preset temperature change condition, namely the temperature rise and the temperature drop of the target indoor environment. The preset temperature variation condition may specifically be that the indoor temperature is maintained within a certain variation range during the operation of the air conditioner, and the variation range may be determined according to an actual situation.

203. The server collects object characteristic information of a target object using the air conditioner.

204. And the server analyzes the human body comfort level of the target object according to the object characteristic information to obtain a target comfort temperature matched with the target object.

comparing the reference characteristic information with the object characteristic information in at least one dimension of human comfort level;

Through comparison processing, reference characteristic information matched with the object characteristic information of the target object can be determined, and the reference comfortable temperature of the reference object corresponding to the reference characteristic information is determined as the target comfortable temperature.

205. And the server corrects the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommends the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

according to the refrigerating capacity, temperature distribution information of the target indoor environment in a preset time period under the operation of the air conditioner is estimated;

In the embodiment, the required refrigerating capacity of the air conditioner can be estimated according to the current corresponding target space model, indoor and outdoor environment temperature and set target temperature, and further the room temperature distribution condition under the accumulated running time of 1h, 2h, 8230, 8230and 6h (hours) of the room can be estimated. Based on the temperature distribution information, whether the indoor temperature is uniformly distributed (whether the upper layer and the lower layer are layered) or not and whether the temperature is too high or too low can be known; so that the cooling capacity can be corrected according to the temperature distribution information.

The historical usage scenario may include indoor and outdoor ambient temperatures corresponding to the usage of the air conditioner by the user within the historical time period, the set target temperature, and the scenario mode in which the target object is located. The behavior information in the historical usage scenario may specifically be behaviors of the target object to raise or lower a set temperature, a windshield, shut down, and the like to change a setting of the air conditioner.

Wherein, the historical use scene matched with the current scene using the air conditioner can be used as the target historical use scene; and correcting the refrigerating capacity of the air conditioner based on the behavior information under the target historical use scene and the target comfortable temperature.

As can be seen from the above, in this embodiment, the temperature change information of the target indoor environment where the air conditioner is located may be obtained by the server, and based on the temperature change information, the target space model corresponding to the target indoor environment is selected from the preset space models; based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition; collecting object characteristic information of a target object using the air conditioner; analyzing the human body comfort degree of the target object through the object characteristic information to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object. According to the method and the device, the recommended operation parameters of the air conditioner can be determined by combining the target space model of the indoor environment where the air conditioner is located, the object characteristic information and the historical behavior information of the user, so that the accuracy of recommending the operation parameters of the air conditioner is improved, the user operation is effectively reduced, and the comfort level of the user is enhanced.

In order to better implement the above method, an embodiment of the present application further provides an air conditioner operation parameter recommendation device, as shown in fig. 3, the air conditioner operation parameter recommendation device may include an obtaining unit 301, an estimating unit 302, an acquiring unit 303, an analyzing unit 304, and a recommending unit 305, as follows:

(1) An acquisition unit 301;

the air conditioner comprises an acquisition unit, a storage unit and a control unit, wherein the acquisition unit is used for acquiring temperature change information of a target indoor environment where an air conditioner is located and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information.

the calculating subunit is used for calculating the similarity between the temperature change information of the target indoor environment and the temperature change information corresponding to each preset space model;

and the selecting subunit is used for selecting the target space model corresponding to the target indoor environment from the preset space models according to the similarity.

(2) A pre-estimation unit 302;

and the pre-estimation unit is used for pre-estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets the preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and the set target temperature.

Optionally, in some embodiments of the present application, the estimation unit may be specifically configured to calculate a refrigerant flow rate of the air conditioner according to a suction density, a volumetric efficiency, and an operating efficiency of a compressor of the air conditioner; and estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition according to the refrigerant flow of the air conditioner, the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature.

(3) An acquisition unit 303;

and an acquisition unit for acquiring object characteristic information of a target object using the air conditioner.

(4) An analysis unit 304;

and the analysis unit is used for carrying out human body comfort analysis on the target object through the object characteristic information to obtain a target comfort temperature matched with the target object.

the comparison subunit is used for carrying out comparison processing on at least one human body comfort degree dimension on the reference characteristic information and the object characteristic information;

(5) A recommendation unit 305;

Optionally, in some embodiments of the present application, the recommending unit may include an estimating sub-unit and a refrigerating capacity modifying sub-unit, as follows:

the estimation subunit is used for estimating the temperature distribution information of the target indoor environment in a preset time period under the operation of the air conditioner according to the refrigerating capacity;

As can be seen from the above, in this embodiment, the obtaining unit 301 may obtain the temperature change information of the target indoor environment where the air conditioner is located, and select the target space model corresponding to the target indoor environment from the preset space models based on the temperature change information; estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature through an estimation unit 302; collecting object characteristic information of a target object using the air conditioner by a collecting unit 303; analyzing the human comfort level of the target object by the analysis unit 304 according to the object characteristic information to obtain a target comfort temperature matched with the target object; and modifying the cooling capacity of the air conditioner through a recommending unit 305 according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending an air conditioner operation parameter corresponding to the modified cooling capacity to the target object. The method and the device can determine the recommended operating parameters of the air conditioner by combining the target space model of the indoor environment where the air conditioner is located, the object characteristic information and the historical behavior information of the user, so that the accuracy of recommending the operating parameters of the air conditioner is improved, the user operation is effectively reduced, and the comfort level of the user is enhanced.

An electronic device according to an embodiment of the present application is further provided, as shown in fig. 4, which shows a schematic structural diagram of the electronic device according to the embodiment of the present application, where the electronic device may be a terminal or a server, and specifically:

the electronic device may include components such as a processor 401 of one or more processing cores, memory 402 of one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. Wherein:

the processor 401 is a control center of the electronic device, connects various parts of the whole electronic device by various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby performing overall monitoring of the electronic device. Alternatively, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 401.

The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 access to the memory 402.

The electronic device further comprises a power supply 403 for supplying power to the various components, and preferably, the power supply 403 is logically connected to the processor 401 through a power management system, so that the functions of charging, discharging, and power consumption management are managed through the power management system. The power supply 403 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.

The electronic device may further include an input unit 404, and the input unit 404 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 402 according to the following instructions, and the processor 401 runs the application program stored in the memory 402, thereby implementing various functions as follows:

acquiring temperature change information of a target indoor environment where an air conditioner is located, and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information; based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition; collecting object characteristic information of a target object using the air conditioner; analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.

As can be seen from the above, in this embodiment, temperature change information of a target indoor environment where an air conditioner is located may be obtained, and based on the temperature change information, a target space model corresponding to the target indoor environment is selected from preset space models; estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature; collecting object characteristic information of a target object using the air conditioner; analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object. According to the method and the device, the recommended operation parameters of the air conditioner can be determined by combining the target space model of the indoor environment where the air conditioner is located, the object characteristic information and the historical behavior information of the user, so that the accuracy of recommending the operation parameters of the air conditioner is improved, the user operation is effectively reduced, and the comfort level of the user is enhanced.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.

To this end, embodiments of the present application provide a computer-readable storage medium, in which a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps in any one of the air conditioner operation parameter recommendation methods provided in the embodiments of the present application. For example, the instructions may perform the steps of:

acquiring temperature change information of a target indoor environment where an air conditioner is located, and selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature change information; estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature; collecting object characteristic information of a target object using the air conditioner; analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object; and correcting the refrigerating capacity of the air conditioner according to the target comfortable temperature and the historical behavior information of the air conditioner used by the target object, and recommending the air conditioner operation parameters corresponding to the corrected refrigerating capacity to the target object.

Wherein the computer-readable storage medium may include: read Only Memory (ROM), random Access Memory (RAM), magnetic or optical disks, and the like.

Since the instructions stored in the computer-readable storage medium may execute the steps in any air conditioner operation parameter recommendation method provided in the embodiment of the present application, beneficial effects that can be achieved by any air conditioner operation parameter recommendation method provided in the embodiment of the present application may be achieved, which are detailed in the foregoing embodiments and will not be described herein again.

According to an aspect of the application, a computer program product or computer program is provided, comprising computer instructions, the computer instructions being stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to execute the method provided in the various optional implementation modes of the air conditioner operation parameter recommendation aspect.

The air conditioner operation parameter recommendation method and the related devices provided by the embodiments of the present application are described in detail above, and specific examples are applied in the present application to explain the principles and embodiments of the present application, and the description of the above embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An air conditioner operation parameter recommendation method is characterized by comprising the following steps:

based on the target space model, the indoor and outdoor environment temperature corresponding to the air conditioner and a set target temperature, estimating the refrigerating capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition;

analyzing the comfort level of the target object by the characteristic information of the object to obtain a target comfort temperature matched with the target object;

2. The method according to claim 1, wherein the selecting a target space model corresponding to the target indoor environment from preset space models based on the temperature variation information comprises:

3. The method of claim 1, wherein the modifying the cooling capacity of the air conditioner according to the target comfort temperature and the historical behavior information of the target object using the air conditioner comprises:

4. The method according to claim 1, wherein the estimating of the cooling capacity corresponding to the air conditioner when the temperature of the target indoor environment meets a preset temperature change condition based on the target space model, the indoor and outdoor environment temperatures corresponding to the air conditioner, and a set target temperature comprises:

5. The method according to claim 1, wherein the performing a human comfort analysis on the target object through the object feature information to obtain a target comfort temperature matched with the target object comprises:

6. The method of claim 1, wherein the modifying the cooling capacity of the air conditioner according to the target comfort temperature and the historical behavior information of the target object using the air conditioner comprises:

7. An air conditioner operating parameter recommendation device, comprising:

8. An electronic device comprising a memory and a processor; the memory stores an application program, and the processor is configured to execute the application program in the memory to perform the operations of the air conditioner operation parameter recommendation method according to any one of claims 1 to 6.

9. A computer readable storage medium storing a plurality of instructions, the instructions being suitable for being loaded by a processor to execute the steps of the air conditioner operation parameter recommendation method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program or instructions, characterized in that the computer program or instructions, when executed by a processor, implement the steps in the air conditioner operating parameter recommendation method according to any one of claims 1 to 6.