Method and device for screening types of air conditioners and storage medium
By obtaining the selection parameters and working conditions information entered by the user, and generating and filtering the list of air-conditioning models, the problems of low air-conditioning selection efficiency and high error rate in the existing technology are solved, and the accuracy and efficiency of air-conditioning model screening are improved.
Patent Information
- Application Number
- CN202311305836.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-10-10
- Publication Date
- 2025-04-11
AI Technical Summary
The prior art has low efficiency and high error rate when selecting commercial air conditioners, making it difficult to accurately screen models that meet user needs.
By obtaining the selection parameters and current working conditions input by the user, a target model list is generated, and the data of each model in the list is filtered according to the user's selection needs to obtain the target model that meets the user's needs.
It has achieved the improvement of accuracy and efficiency in air conditioning model screening, reduced error rate, and improved the accuracy and speed of air conditioning model selection.
Smart Images
Figure CN119807726A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of air conditioner model screening, for example, to a method, device and storage medium for screening air conditioner models. Background Art
[0002] As people's living standards continue to improve, smart devices are gradually entering users' lives. At present, the emergence of commercial air conditioners has significantly improved people's quality of life. At the same time, how to select commercial air conditioners more accurately has become the focus of users.
[0003] At present, when selecting commercial air conditioners, it is necessary to select models that meet the requirements based on specific working conditions and cooling capacity requirements. However, developers need to first sort out the possible model range based on experience, then calculate the data of each model according to the required working conditions and cooling capacity, and finally compare all the data to get the optimal solution. However, when there is a lot of selection data, this method of selecting commercial air conditioners has the problems of low efficiency and high error rate. Therefore, how to select air conditioner models more accurately has become a technical problem that needs to be solved urgently.
[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention
[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.
[0006] The embodiments of the present disclosure provide a method, device, and storage medium for screening air conditioner models, which can screen air conditioner models more accurately.
[0007] In some embodiments, the method for screening air conditioning models includes: obtaining selection parameters and current operating condition information input by a user; generating a target model list based on the selection parameters and current operating condition information input by the user; and screening the data of each model in the target model list based on the user's selection requirements to obtain a target model that meets the user's selection requirements.
[0008] In some embodiments, the method for screening air conditioning models includes: screening out a set of target models that meet the selection parameters in a model information library; determining the cooling capacity of each target model in the target model set under full load based on current operating conditions; and generating a target model list based on the cooling capacity of each target model under full load and the target required cooling capacity.
[0009] In some embodiments, the method for screening air conditioning models includes: obtaining a model database, which stores the association between different operating conditions, models and cooling capacity under full load; matching the cooling capacity of different target models under the current operating conditions under full load in the model database, so as to determine it as the cooling capacity of each target model in the target model set under full load.
[0010] In some embodiments, the method for screening air conditioning models includes: obtaining a cooling capacity error of a required cooling capacity input by a user; calculating in turn the absolute value of the difference between the cooling capacity of each target model under full load and the target required cooling capacity; and adding a target model whose absolute value of the difference between the cooling capacity under full load and the target required cooling capacity is lower than the cooling capacity error to a target model list.
[0011] In some embodiments, the method for screening air conditioning models includes: screening out a first model with the largest cooling capacity under standard operating conditions and a second model with the smallest cooling capacity under standard operating conditions from a target model set; determining the cooling capacity of the first model under full load and the cooling capacity of the second model under full load based on current operating condition information; determining the target required cooling capacity based on the cooling capacity of the first model under full load and the cooling capacity of the second model under full load.
[0012] In some embodiments, the method for screening air conditioning models includes: determining an upper limit value and a lower limit value of the required cooling capacity based on the cooling capacity of the first model under full load and the cooling capacity of the second model under full load; determining a target required cooling capacity based on the upper limit value and the lower limit value of the required cooling capacity.
[0013] In some embodiments, the method for screening air conditioner models includes: generating a selection report based on target models that meet user selection requirements; and pushing the selection report to the user so that the user can promptly know the target models that meet the user's selection requirements.
[0014] In some embodiments, the device for screening air conditioning models includes: an acquisition module, configured to obtain selection parameters input by a user and current operating condition information; a generation module, configured to generate a target model list based on the selection parameters input by the user and current operating condition information; and a screening module, configured to screen the model data in the target model list according to the user's selection requirements to obtain a target model that meets the user's selection requirements.
[0015] In some embodiments, the device for screening air conditioner models includes: a processor and a memory storing program instructions, and the processor is configured to execute the aforementioned method for screening air conditioner models when running the program instructions.
[0016] In some embodiments, the storage medium stores program instructions, and when the program instructions are run, the method for screening air conditioner models as described above is executed.
[0017] The method, device and storage medium for screening air conditioner models provided by the embodiments of the present disclosure can achieve the following technical effects: by obtaining the selection parameters and current working condition information input by the user; and generating a target model list according to the selection parameters and current working condition information input by the user; thereby screening the data of each model in the target model list according to the selection requirements of the user to obtain the target model that meets the selection requirements of the user. With this scheme, the air conditioner models can be initially screened in combination with the selection parameters and current working condition information input by the user to generate a target model list, and then the data of each model in the target model list can be secondary screened in combination with the selection requirements of the user to ensure the accuracy of the air conditioner model screening results, effectively improving the selection efficiency of the air conditioner.
[0018] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:
[0020] Figure 1 is a schematic diagram of a method for screening air conditioner models provided by an embodiment of the present disclosure;
[0021] Figure 2 is a schematic diagram of a method for generating a target model list provided by an embodiment of the present disclosure;
[0022] Figure 3 is a schematic diagram of a method for determining cooling capacity provided by an embodiment of the present disclosure;
[0023] Figure 4 is another schematic diagram of a method for generating a target model list provided by an embodiment of the present disclosure;
[0024] Figure 5 is a schematic diagram of a method for determining target required cooling capacity provided by an embodiment of the present disclosure;
[0025] Figure 6 is another schematic diagram of a method for determining target required cooling capacity provided by an embodiment of the present disclosure;
[0026] Figure 7 is another schematic diagram of a method for screening air conditioner models provided by an embodiment of the present disclosure;
[0027] Figure 8 is a schematic diagram of a device for screening air conditioner models provided by an embodiment of the present disclosure;
[0028] Fig. 9 It is a schematic diagram of another device for screening air conditioner models provided by an embodiment of the present disclosure. DETAILED DESCRIPTION
[0029] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.
[0030] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.
[0031] Unless otherwise stated, the term "plurality" means two or more.
[0032] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.
[0033] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.
[0034] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.
[0035] In the embodiments of the present disclosure, smart home appliances refer to home appliances that are formed by introducing microprocessors, sensor technology, and network communication technology into home appliances. They have the characteristics of intelligent control, intelligent perception, and intelligent application. The operation process of smart home appliances often relies on the application and processing of modern technologies such as the Internet of Things, the Internet, and electronic chips. For example, smart home appliances can be connected to electronic devices to enable users to remotely control and manage the smart home appliances.
[0036] In the embodiments of the present disclosure, the terminal device refers to an electronic device with a wireless connection function. The terminal device can communicate with the above-mentioned smart home appliances by connecting to the Internet, or can directly communicate with the above-mentioned smart home appliances through Bluetooth, WiFi, etc. In some embodiments, the terminal device is, for example, a mobile device, a computer, or a vehicle-mounted device built into a hover car, or any combination thereof. Mobile devices may include, for example, mobile phones, smart home devices, wearable devices, smart mobile devices, virtual reality devices, etc., or any combination thereof, wherein wearable devices include, for example: smart watches, smart bracelets, pedometers, etc.
[0037] Figure 1 is a schematic diagram of a method for screening air conditioner models provided by an embodiment of the present disclosure; Figure 1 As shown, optionally, the embodiment of the present disclosure provides a method for screening air conditioner models, comprising:
[0038] S11, the server obtains the selection parameters and current working condition information input by the user.
[0039] S12, the server generates a target model list according to the selection parameters input by the user and the current working condition information.
[0040] S13, the server screens the data of each model in the target model list according to the user's selection requirements to obtain a target model that meets the user's selection requirements.
[0041] In this solution, the server can be a cloud server or deployed on a smart device. The server can obtain the selection parameters input by the user. Here, the selection parameters input by the user include the compressor type, the refrigerant type, and the power type. The server can also obtain the current operating condition information. Among them, the current operating condition information includes the current inlet water temperature of the air conditioner evaporator, the current outlet water temperature of the evaporator, the current inlet water temperature of the condenser, and the current outlet water temperature of the condenser. As an example, the current operating condition information can be obtained through temperature sensors set at different positions of the air conditioner. In this way, accurate acquisition of selection parameters and current operating condition information can be achieved.
[0042] Furthermore, after the server obtains the selection parameters and current operating condition information input by the user, it can generate a list of target models in combination with the selection parameters and current operating condition information input by the user. Specifically, the server generates a list of target models based on the selection parameters and current operating condition information input by the user, including: the server selects a set of target models that meet the selection parameters in the model information library; the server determines the cooling capacity of each target model in the target model set under full load based on the current operating condition information; the server generates a list of target models based on the cooling capacity of each target model under full load and the target required cooling capacity. In this way, the selection parameters and current operating condition information input by the user can be combined to perform a preliminary screening of air conditioning models, thereby achieving accurate generation of a list of target models.
[0043] Furthermore, after generating the target model list, the server can filter the data of each model in the target model list according to the user's selection requirements to obtain the target model that meets the user's selection requirements. Here, the user's selection requirements can be sent to the server in advance by the user. Specifically, filtering the data of each model in the target model list according to the user's selection requirements includes: obtaining the data of each model in the target model list; filtering the data of each model in the target model list according to the user's selection requirements. Among them, the data of each model in the target model list can be the cooling capacity and power of each model under different load conditions. Here, different load conditions can include full load state, 75% load state, 50% load state and 25% load state, etc.
[0044] The method for screening air conditioner models provided by the embodiment of the present disclosure is adopted, by obtaining the selection parameters and current working condition information input by the user; and generating a target model list according to the selection parameters and current working condition information input by the user; thereby screening the data of each model in the target model list according to the selection requirements of the user to obtain the target model that meets the selection requirements of the user. With this scheme, the air conditioner models can be preliminarily screened in combination with the selection parameters and current working condition information input by the user to generate a target model list, and then the data of each model in the target model list can be secondary screened in combination with the selection requirements of the user to ensure the accuracy of the air conditioner model screening results, effectively improving the selection efficiency of the air conditioner.
[0045] Figure 2 is a schematic diagram of a method for generating a target model list provided by an embodiment of the present disclosure; Figure 2 As shown, optionally, in S12, the server generates a target model list according to the selection parameters input by the user and the current working condition information, including:
[0046] S21, the server selects a target model set that meets the selection parameters from the model information database.
[0047] S22, the server determines the cooling capacity of each target model in the target model set under full load according to the current working condition information.
[0048] S23, the server generates a list of target models according to the cooling capacity of each target model under full load and the target required cooling capacity.
[0049] In this solution, the server can obtain a model information library, which stores information such as compressor type, refrigerant type, and power type of different models. In this way, the server selects a target model set that meets the selection parameters in the model information library, including: the server selects a target model with the same selection parameters as the user input in the model information library, and adds it to the target model set. In this way, the target model set can be accurately determined.
[0050] Furthermore, after determining the target model set, the server can determine the cooling capacity of each target model in the target model set under full load in combination with the current working condition information. Specifically, the server determines the cooling capacity of each target model in the target model set under full load based on the current working condition information, including: the server obtains a model database, and the model database stores the association between different working conditions, models and cooling capacity under full load; the server matches the cooling capacity of different target models under the current working conditions in the model database under full load to determine it as the cooling capacity of each target model in the target model set under full load. In this way, the cooling capacity of each target model under full load can be accurately determined.
[0051] Furthermore, the server can generate a list of target models based on the cooling capacity of each target model under full load and the target required cooling capacity. Specifically, the server generates a list of target models based on the cooling capacity of each target model under full load and the target required cooling capacity, including: the server obtains the cooling capacity error of the required cooling capacity input by the user; the server calculates the absolute value of the difference between the cooling capacity of each target model under full load and the target required cooling capacity in turn; the server adds the target model whose absolute value of the difference between the cooling capacity under full load and the target required cooling capacity is lower than the cooling capacity error to the list of target models. In this way, the preliminary screening of air-conditioning models can be achieved in combination with the cooling capacity of each target model under full load and the target required cooling capacity, so that the air-conditioning models that have passed the preliminary screening can be added to the list of target models.
[0052] Figure 3 is a schematic diagram of a method for determining cooling capacity provided by an embodiment of the present disclosure; Figure 3 As shown, optionally, in S22, the server determines the cooling capacity of each target model in the target model set under a full load state according to the current working condition information, including:
[0053] S31, the server obtains a model database, which stores the association between different working conditions, models and cooling capacity under full load.
[0054] S32, the server matches the cooling capacity of different target models under the current working condition in the model database under the full load state, and determines it as the cooling capacity of each target model in the target model set under the full load state.
[0055] In this solution, the server obtains a model database. Specifically, the model database stores the association between different working conditions, models and cooling capacity under full load. In this way, in order to more accurately determine the cooling capacity of each target model in the target model set under full load, the server can sequentially match the cooling capacity of each target model under the current working condition under full load in the model database. With this solution, the cooling capacity of each target model under full load can be accurately determined.
[0056] In another example, if the selection parameters input by the user also include information such as fouling factor and ethylene glycol concentration, the cooling capacity of each target model under full load can be calculated based on the fouling factor, ethylene glycol concentration and inlet and outlet water temperatures of the heat exchanger.
[0057] Figure 4 is another schematic diagram of a method for generating a target model list provided by an embodiment of the present disclosure; Figure 4 As shown, optionally, in S23, the server generates a target model list according to the cooling capacity of each target model under full load and the target required cooling capacity, including:
[0058] S41, the server obtains the cooling capacity error of the required cooling capacity input by the user.
[0059] S42, the server calculates the absolute value of the difference between the cooling capacity of each target model under full load and the target required cooling capacity in turn.
[0060] S43, the server adds the target model whose absolute value of the difference between the cooling capacity under full load and the target required cooling capacity is lower than the cooling capacity error to the target model list.
[0061] In this solution, the server can obtain the cooling capacity error of the required cooling capacity input by the user. Here, the cooling capacity error of the required cooling capacity refers to the deviation value of the allowed required cooling capacity. As an example, the cooling capacity error can be 5%.
[0062] Furthermore, after determining the cooling capacity of each target model under full load and the target required cooling capacity, the server can sequentially calculate the absolute value of the difference between the cooling capacity of each target model under full load and the target required cooling capacity. For example, if the cooling capacity of each target model under full load is a1, a2, a3, etc., and the target required cooling capacity is b, |a1-b|, |a2-b|, and |a2-b| are calculated sequentially.
[0063] Furthermore, the server can determine the relationship between the absolute value of the difference between the cooling capacity under full load and the target required cooling capacity and the obtained cooling capacity error, and add the target model whose absolute value of the difference between the cooling capacity under full load and the target required cooling capacity is lower than the cooling capacity error to the target model list. In this way, the preliminary screening of air conditioner models can be achieved by combining the cooling capacity and the target required cooling capacity of each target model under full load, so that the air conditioner models that have passed the preliminary screening can be added to the target model list.
[0064] Figure 5 is a schematic diagram of a method for determining target required cooling capacity provided by an embodiment of the present disclosure; Figure 5 As shown, optionally, the target required cooling capacity is determined by:
[0065] S51, the server selects a first model with the largest cooling capacity under standard working conditions and a second model with the smallest cooling capacity under standard working conditions from the target model set.
[0066] S52, the server determines the cooling capacity of the first model under full load and the cooling capacity of the second model under full load according to the current working condition information.
[0067] S53, the server determines the target required cooling capacity according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load.
[0068] In this solution, the server can obtain the cooling capacity of each model in the target model set under standard conditions. Specifically, the cooling capacity of each model under standard conditions can be matched in the model database. Furthermore, the server can compare the cooling capacity of each model under standard conditions to screen out the first model with the largest cooling capacity under standard conditions and the second model with the smallest cooling capacity under standard conditions. In this way, the first model and the second model can be accurately determined.
[0069] Furthermore, the server matches the cooling capacity of the first model under full load and the cooling capacity of the second model under full load in the model database based on the current operating condition information, so as to accurately determine the cooling capacity of the first model under full load and the cooling capacity of the second model under full load.
[0070] Furthermore, the server can determine the target required cooling capacity based on the cooling capacity of the first model under full load and the cooling capacity of the second model under full load. Specifically, the server determines the target required cooling capacity based on the cooling capacity of the first model under full load and the cooling capacity of the second model under full load, including: the server determines the upper limit value of the required cooling capacity and the lower limit value of the required cooling capacity based on the cooling capacity of the first model under full load and the cooling capacity of the second model under full load; the server determines the target required cooling capacity based on the upper limit value of the required cooling capacity and the lower limit value of the required cooling capacity. In this way, the target required cooling capacity can be accurately determined.
[0071] Figure 6 is another schematic diagram of a method for determining target required cooling capacity provided by an embodiment of the present disclosure; Figure 6 As shown, optionally, in S53, the server determines the target required cooling capacity according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load, including:
[0072] S61, the server determines an upper limit value and a lower limit value of the required cooling capacity according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load.
[0073] S62: The server determines the target required cooling capacity according to the upper limit value and the lower limit value of the required cooling capacity.
[0074] In this solution, the server can determine the upper limit value and the lower limit value of the required cooling capacity according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load. Specifically, the upper limit value of the required cooling capacity = the cooling capacity of the first model under full load + the cooling capacity error of the required cooling capacity; the lower limit value of the required cooling capacity = the cooling capacity of the second model under full load - the cooling capacity error of the required cooling capacity. In this way, the upper limit value and the lower limit value of the required cooling capacity can be accurately determined.
[0075] Furthermore, the server determines the target demand cooling capacity according to the upper limit value of the demand cooling capacity and the lower limit value of the demand cooling capacity, including: the server determines the range of the demand cooling capacity according to the upper limit value of the demand cooling capacity and the lower limit value of the demand cooling capacity; the server pushes the range of the demand cooling capacity to the user so that the user can determine the target demand cooling capacity according to the range of the demand cooling capacity. The target demand cooling capacity is any value in the range of the demand cooling capacity selected by the user. For example, if the upper limit value of the demand cooling capacity is 100 and the lower limit value of the demand cooling capacity is 20, the range of the demand cooling capacity is determined to be 20 to 100, and the target demand cooling capacity can be any value between 20 and 100 selected by the user. In this way, the accurate determination of the target demand cooling capacity can be achieved.
[0076] Figure 7is another schematic diagram of a method for screening air conditioner models provided by an embodiment of the present disclosure; Figure 7 As shown, optionally, after obtaining the target model that meets the user's selection requirements, it also includes:
[0077] S71, the server generates a selection report according to the target model that meets the user's selection requirements.
[0078] S72, the server pushes the selection report to the user, so that the user can promptly know the target model that meets the user's selection requirements.
[0079] In this solution, after obtaining the target model that meets the user's selection requirements, the server can also generate a selection report in combination with the target model that meets the user's selection requirements. Here, the selection report can be generated according to the user's preferences. Here, the preferences may include information type and report style. As an example, the selection report may include information such as the cooling capacity and power of the target model that meets the user's selection requirements under different load conditions. Furthermore, the server can push the selection report to the user. In this way, it is convenient for the user to promptly learn the target model that meets the user's selection requirements based on the selection report.
[0080] Figure 8 is a schematic diagram of a device for screening air conditioner models provided by an embodiment of the present disclosure; Figure 8 As shown, the embodiment of the present disclosure provides a device for screening air conditioner models, including an acquisition module 81, a generation module 82 and a screening module 83. The acquisition module 81 is configured to acquire the selection parameters and current working condition information input by the user; the generation module 82 is configured to generate a target model list according to the selection parameters and current working condition information input by the user; the screening module 83 is configured to screen the model data in the target model list according to the user's selection requirements, so as to obtain the target model that meets the user's selection requirements.
[0081] The device for screening air conditioner models provided by the embodiment of the present disclosure is used to obtain the selection parameters and current working condition information input by the user; and generate a target model list according to the selection parameters and current working condition information input by the user; thereby screening the data of each model in the target model list according to the selection requirements of the user to obtain the target model that meets the selection requirements of the user. With this scheme, the air conditioner models can be preliminarily screened in combination with the selection parameters and current working condition information input by the user to generate a target model list, and then the data of each model in the target model list can be secondary screened in combination with the selection requirements of the user to ensure the accuracy of the air conditioner model screening results, effectively improving the selection efficiency of the air conditioner.
[0082] Fig. 9 is another schematic diagram of a device for screening air conditioner models provided by an embodiment of the present disclosure; Fig. 9 As shown, an embodiment of the present disclosure provides a device 200 for screening air conditioner models, including a processor 201 and a memory 202. Optionally, the device may also include a communication interface 203 and a bus 204. The processor 201, the communication interface 203, and the memory 202 may communicate with each other through the bus 204. The communication interface 203 may be used for information transmission. The processor 201 may call the logic instructions in the memory 202 to execute the method for screening air conditioner models of the above embodiment.
[0083] In addition, the logic instructions in the memory 202 described above may be implemented in the form of software functional units and when sold or used as independent products, may be stored in a computer-readable storage medium.
[0084] The memory 202 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor 201 executes the function application and data processing by running the program instructions / modules stored in the memory 202, that is, the method for screening air conditioner models in the above embodiment is implemented.
[0085] The memory 202 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 202 may include a high-speed random access memory and may also include a non-volatile memory.
[0086] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned method for screening air conditioner models.
[0087] The computer-readable storage medium mentioned above may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.
[0088] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes, or a transient storage medium.
[0089] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.
[0090] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.
[0091] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.
[0092] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.
Claims
1. A method for screening air conditioner models, characterized in that: include: Obtain the selection parameters and current working condition information input by the user; Generate a target model list according to the selection parameters input by the user and the current operating condition information; The data of each model in the target model list is filtered according to the user's selection requirements to obtain a target model that meets the user's selection requirements.
2. The method according to claim 1, characterized in that: According to the selection parameters input by the user and the current working condition information, a target model list is generated, including: Filtering out a set of target models that meet the selection parameters in the model information database; Determine the cooling capacity of each target model in the target model set under a full load state according to the current operating condition information; Generate a list of target models based on the cooling capacity of each target model under full load and the target required cooling capacity.
3. The method according to claim 2, characterized in that According to the current operating condition information, determining the cooling capacity of each target model in the target model set under a full load state includes: Obtaining a machine model database, wherein the machine model database stores associations between different operating conditions, machine models, and refrigeration capacities under full load; The cooling capacities of different target models under the current working conditions and under full load are matched in the model database to be determined as the cooling capacities of each target model in the target model set under full load.
4. The method according to claim 2, characterized in that: According to the cooling capacity of each target model under full load and the target required cooling capacity, a list of target models is generated, including: Obtain the cooling capacity error of the required cooling capacity input by the user; Calculate the absolute value of the difference between the cooling capacity of each target model under full load and the target required cooling capacity in turn; The target machine model whose absolute value of the difference between the cooling capacity under full load and the target required cooling capacity is lower than the cooling capacity error is added to the target machine model list.
5. The method according to claim 2, characterized in that: The target cooling capacity requirement is determined by: Selecting a first model with the largest cooling capacity under standard working conditions and a second model with the smallest cooling capacity under standard working conditions from the target model set; Determine, according to the current operating condition information, the cooling capacity of the first model under full load and the cooling capacity of the second model under full load; The target required cooling capacity is determined according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load.
6. The method according to claim 5, characterized in that Determining a target required cooling capacity according to the cooling capacity of the first model under a full load state and the cooling capacity of the second model under a full load state includes: Determine an upper limit value and a lower limit value of the required cooling capacity according to the cooling capacity of the first model under full load and the cooling capacity of the second model under full load; The target cooling capacity requirement is determined according to the upper limit value of the cooling capacity requirement and the lower limit value of the cooling capacity requirement.
7. The method according to claim 1, characterized in that After obtaining the target model that meets the user's selection requirements, the method further includes: Generate a selection report based on the target model that meets the user's selection requirements; The selection report is pushed to the user so that the user can promptly know the target model that meets the user's selection requirements.
8. A device for screening air conditioner models, characterized in that: include: An acquisition module is configured to acquire selection parameters input by a user and current working condition information; A generating module is configured to generate a target model list according to the selection parameters input by the user and the current working condition information; The screening module is configured to screen the model data in the target model list according to the user's selection requirements to obtain the target model that meets the user's selection requirements.
9. A device for screening air conditioner models, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the method for screening air conditioner models according to any one of claims 1 to 7 when running the program instructions.
10. A storage medium storing program instructions, characterized in that: When the program instructions are executed, the method for screening air conditioner models according to any one of claims 1 to 7 is executed.