CN118051543A - Battery data query method, system, electronic device and storage medium - Google Patents
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Abstract
The application provides a battery data query method, a system, electronic equipment and a storage medium, and relates to the technical field of batteries, wherein the method comprises the following steps: establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, and each data set comprises battery data of at least one dimension; responding to a data query request, and querying in the multidimensional database to obtain a query result corresponding to the data query request; analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements. The embodiment of the application can realize one-stop integration of battery research and development data and improve the data query efficiency and flexibility.
Description
Technical Field
The present application relates to the field of battery technologies, and in particular, to a method and a system for querying battery data, an electronic device, and a storage medium.
Background
The battery is a main energy source of various devices and tools in the current generation by virtue of the advantages of high energy and portability, the development speed of the battery is also rapidly improved, and accordingly, a shorter development period and a large amount of historical data are obtained, and the data query methods such as retrieval analysis and the like for the historical data can be beneficial to the understanding of the current development situation and parameters of the battery by workers, so that assistance is provided for accelerating iteration of battery products.
However, at present, most of inquiry modes of battery data are investigation and data inquiry of battery data from a single dimension of a certain type of battery or a certain manufacturer, and if inquiry analysis is required for batteries with different dimensions, manual secondary analysis is required, so that the problems of large workload and incomplete and inaccurate battery data analysis exist.
It should be noted that the foregoing statements are merely to provide background information related to the present disclosure and may not necessarily constitute prior art.
Disclosure of Invention
In view of the above, the present application aims to provide a battery data query method, a system, an electronic device and a storage medium, which can solve the problems of incomplete and inaccurate analysis of battery data in the existing scheme.
Based on the above object, in a first aspect, the present application provides a battery data query method, including: establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, each data set comprises at least one dimension of battery data, and the dimension of the battery data comprises one or more of a battery process dimension, a battery test dimension and a material dimension; responding to a data query request, and querying in the multidimensional database to obtain a query result corresponding to the data query request; analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
According to the embodiment, the multi-dimensional database is built by converging battery data with different dimensions, one-stop integration of battery research and development data is achieved, the multi-dimensional database is queried in response to a data query request, a query result corresponding to the data query request is obtained, query time consumed by scattered missing of data can be reduced, data query efficiency is improved, and the rule set is preset.
In some embodiments, the battery data includes structured data and unstructured data, and the building a multi-dimensional database includes: decoding and analyzing the unstructured data to obtain key information in the unstructured data; classifying the structured data and the key information according to the dimension of the battery data to obtain a multi-class data set; and establishing the multi-dimensional database according to the multi-class data set.
According to the embodiment, the unstructured data are decoded and analyzed to extract the key information in the unstructured data, so that the data size in the database can be increased, and the integration level of the battery data and the accuracy of data query are improved.
In some embodiments, before querying the multidimensional database to obtain a query result corresponding to the data query request, the method further includes: summarizing the battery data with the query frequency greater than or equal to the preset query frequency threshold value based on the query frequency and the preset query frequency threshold value of each battery data in the multi-dimensional database to obtain an intermediate data set; wherein, in case of a query in the multi-dimensional database, the query is performed from the intermediate dataset.
According to the embodiment, according to the query frequency of the battery data, the battery data with higher heat is placed in the middle data set, and under the condition of querying in the multi-dimensional database, the query is performed from the middle data set, so that the data query speed is further improved.
In some embodiments, after building the multidimensional database, the method further comprises: establishing an association relation between different data in the multidimensional database according to preset association information, wherein the association information comprises one or more of project codes, product names and identification information; and taking the battery data with the association relation as an association set to obtain at least one association set based on the association information.
According to the embodiment, the battery data among different dimensions can be associated through the association information, and when the data query request contains the association information, the battery data related to the association information in the battery data of different dimensions can be called, so that the accuracy of the data query is improved.
In some embodiments, the responding to the data query request, querying in the multidimensional database, to obtain a query result corresponding to the data query request, includes: determining a target association set corresponding to the data query request according to the data query request; and inquiring battery data corresponding to the data inquiry request in the target association set to obtain the inquiry result.
According to the embodiment, the target association set can be quickly positioned according to the data query request, so that the battery data wanted by the user can be accurately searched in the target association set, and the data query precision is improved.
In some embodiments, the analyzing the query result based on the preset rule set to obtain target data includes: taking the query result as input data of a rule engine, and performing data conversion and calculation on the query result by using the rule engine and the preset rule set to obtain a calculation result; and carrying out format conversion on the calculation result to obtain a calculation result in a chart format as the target data.
The embodiment can provide a channel for the user to interact with the battery data query system, improves the interaction capability of the system, can facilitate the user to set the rule set according to the self requirement, and improves the flexibility of data query.
In some embodiments, the battery data of different dimensions has different query rights, the method further comprising: determining the queriable battery data of a user according to authority information of the user; responding to a data query request of a user, and querying in the queriable battery data to obtain a query result corresponding to the data query request.
The embodiment can improve the safety of the battery data of enterprises and reduce the risk of data leakage.
In a second aspect, there is also provided a battery data query system, the system comprising: the data aggregation module is used for establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, each data set comprises at least one dimension of battery data, and the dimension of the battery data comprises one or more of a battery process dimension, a battery test dimension and a material dimension; the data query module is used for responding to a data query request, querying in the multidimensional database and obtaining a query result corresponding to the data query request; the data analysis module is used for analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
In a third aspect, there is also provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor running the computer program to implement the method for querying battery data according to the first aspect.
In a fourth aspect, there is also provided a computer-readable storage medium having stored thereon a computer program for execution by a processor to implement the method of querying battery data according to any of the first aspects.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
In the drawings, the same reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily drawn to scale. It is appreciated that these drawings depict only some embodiments according to the disclosure and are not therefore to be considered limiting of its scope. Also, like reference numerals are used to designate like parts throughout the accompanying drawings.
Fig. 1 shows a step flowchart of a battery data query method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a battery data query system according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an electronic device according to an embodiment of the present application;
fig. 4 is a schematic diagram of a storage medium according to an embodiment of the present application.
Detailed Description
Embodiments of the technical scheme of the present application will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present application, and thus are merely examples, and are not intended to limit the scope of the present application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion.
In the description of embodiments of the present application, the technical terms "first," "second," and the like are used merely to distinguish between different objects and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated, a particular order or a primary or secondary relationship. In the description of the embodiments of the present application, the meaning of "plurality" is two or more unless explicitly defined otherwise.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
In the description of the embodiments of the present application, the term "and/or" is merely an association relationship describing an association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
Batteries are becoming a major energy source for various devices and tools of the current generation by virtue of their high energy and portability, such as power batteries, are becoming more widely used. The power battery is not only applied to energy storage power supply systems such as hydraulic power, firepower, wind power and solar power stations, but also widely applied to electric vehicles such as electric bicycles, electric motorcycles, electric automobiles, and the like, and a plurality of fields such as military equipment, aerospace, and the like. With the continuous expansion of the application field of the power battery, the market demand of the power battery is also continuously expanding. Along with the shorter development period and a large amount of historical data, the data query methods such as retrieval analysis and the like for the historical data can be helpful for staff to know the current development situation and parameters of the battery, and assist is provided for acceleration iteration of the battery product.
However, at present, most of inquiry modes of battery data are investigation and data inquiry of battery data from a single dimension of a certain type of battery or a certain manufacturer, and if inquiry analysis is required for batteries with different dimensions, manual secondary analysis is required, so that the problems of large workload and incomplete and inaccurate battery data analysis exist.
Based on the above, the embodiment of the application provides a query method for battery data, which is characterized in that a multi-dimensional database is built by converging battery data with different dimensions, one-stop integration of battery research and development data is realized, a query result corresponding to the data query request is obtained by querying the multi-dimensional database in response to the data query request, the query time consumption caused by scattered omission of the data can be reduced, the data query efficiency is improved, and a rule set is preset.
The battery data in this embodiment may be data of various stages of development, production, manufacturing, maintenance, etc. of the battery, and of course, this embodiment may also be applied to other data query scenarios, and for convenience of explanation, the following embodiment will take the battery data as an example, where the battery may be a battery product such as a battery module, a battery pack, or a battery cell, and the battery data may be data related to any one or more battery products such as a battery module, a battery pack, or a battery cell.
Fig. 1 shows a flowchart of steps of a battery data query method according to an embodiment of the present application. Referring to fig. 1, in an embodiment of the present application, a method for querying battery data includes the following steps S101 to S103:
S101, establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, and each data set comprises at least one dimension of battery data.
S102, responding to the data query request, and querying in a multidimensional database to obtain a query result corresponding to the data query request.
S103, analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
The execution body of the embodiment of the application may be an electronic device capable of executing the query method of the battery data, and the electronic device may include, but is not limited to, a terminal, a server, or the like.
The battery data in this embodiment may include one or more of design information of the battery, such as chemical composition of the battery, voltage and capacity of the battery, external dimensions of the battery, charge and discharge characteristics of the battery, operating temperature range of the battery, safety performance of the battery, cycle life of the battery, application field of the battery, and the like. The process data of the battery comprises production parameters of the battery, detection data of the battery, equipment states of the battery, process parameters of the battery, quality control data of the battery, on-line monitoring data of the battery, production records of the battery and the like. The test data of the battery comprises battery capacity of the battery, charge and discharge performance of the battery, cold and hot environment test data of the battery, safety performance test data of the battery, cycle life test data of the battery, impact and vibration test data of the battery, internal resistance test data of the battery, X-ray detection data of the battery and the like. The material data of the battery includes a positive electrode material of the battery, a negative electrode material of the battery, an electrolyte of the battery, a separator of the battery, an additive of the battery, a nanomaterial of the battery, and the like.
The dimension of the battery data refers to the type of the battery data, and the dimension of the battery data includes one or more of a battery process dimension, a battery test dimension and a material dimension, for example, the design information of the battery is taken as the battery data of one dimension, the process data of the battery is taken as the battery data of the other dimension, and the test data of the battery is taken as the battery data of the other dimension. Thus, battery data in multiple dimensions, namely multiple data sets, can be obtained, and the multi-dimensional database is built according to the multiple data sets.
The multi-dimensional database can be established by identifying battery data with different dimensions, designing a dimension table according to the dimensions, wherein one dimension table corresponds to one data set, identifying the relationship among the data in each dimension table by an identification model, and establishing the association relationship among the associated data to obtain the dimension with a hierarchical structure, such as the sequential relationship among the battery data with the process steps of mixing, forming, drying, assembling and the like by taking the dimension of the battery process data as an example.
The data query request in this embodiment refers to a data query request input by a user through an operation page, and when the terminal or the server receives the data query request, the terminal or the server queries in the multidimensional database in response to the data query request, so as to obtain a query result corresponding to the data query request, so as to meet the data query requirement of the user.
For example, if the data query request is "what the positive electrode material of the battery includes", the query result obtained by querying in the multidimensional database is "the positive electrode material of the battery generally includes lithium cobaltate, ternary material, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate, and the like".
In one example, the data query request may be of a different type, such as a literal class, a numeric class, a comparison class, a symbolic class, a temporal class, a fuzzy query class, etc.
It can be understood that the data volume of the battery data is huge, and the possible content of the obtained query result is also very large, so that the embodiment analyzes the query result based on the preset rule set to obtain the target data, so that further analysis according to the requirement of the user can be realized, self-service analysis of the battery data by the user is realized, and the data query precision and flexibility are further improved.
The preset rule set in this embodiment is a set of data analysis logic set according to a user requirement, and the data analysis logic set according to the user requirement may include preset calculation logic, logic triggering conditions, a desired target data form, and the like.
Continuing the above example, in the case where the query result is "the positive electrode material of the battery generally includes lithium cobaltate, ternary material, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate, or the like". The user preset rule set is "output the query result in order of importance of the components" or "output the query result in form of table", or "output the query result in order of importance of the components and in form of table".
According to the embodiment, the battery data in different dimensions are aggregated, the multidimensional database is built according to the dimensions of the battery data, one-stop integration of battery research and development data is realized, the multidimensional database is queried in response to a data query request, a query result corresponding to the data query request is obtained, query time consumption caused by scattered omission of the data can be reduced, data query efficiency is improved, and the preset rule set is a set of data analysis logic set according to user requirements, so that the query result is analyzed based on the preset rule set, the obtained target data more accords with the user requirements, self-service analysis of the battery data by a user can be realized, and data query precision and flexibility are further improved.
In some embodiments of the application, the battery data includes structured data and unstructured data, and building the multi-dimensional database includes: decoding and analyzing the unstructured data to obtain key information in the unstructured data; classifying the structured data and the key information according to the battery data to obtain a multi-class data set; a multi-dimensional database is established according to the multi-class data set.
Structured data refers to data that is organized and stored in a fixed format and structure. Structured data typically exists in the form of tables, tables in databases, spreadsheets, etc., each data item having well-defined fields that can be accessed and processed using rows and columns. When the battery data is acquired, the structured battery data can be directly called through a calling interface.
Unstructured data refers to data without fixed format and structure, which usually exists in the form of free text, images, audio, video, log files, etc., and has no explicit fields and relationships inside, which is difficult to directly understand and process by a machine. The unstructured data cannot be directly called, so that the key information in the unstructured data is obtained by decoding and analyzing the unstructured data, so that the key information in the unstructured battery data is conveniently obtained.
The method comprises the steps of decoding and analyzing unstructured data, such as extracting text data, decoding images or audio files, and the like, cleaning the extracted data, including punctuation marks of texts, removing stop words, denoising the images, and the like, and removing irrelevant information, noise and portions with nonstandard formats, so that the cleaned data are subjected to feature extraction to obtain key information in the unstructured data. The key information may be one or more of the above-described design information, process data, test data, and material data of the battery. That is, whether the structured data or the unstructured data corresponds to a dimension, the embodiment classifies the structured data and the key information according to the dimensions of the structured data and the unstructured data to obtain a multi-class data set.
The dimensions of the battery data in this embodiment include one or more of a battery process dimension, a battery test dimension, and a material dimension, so that a multi-class data set with dimensions as units can be obtained, and then the multi-class data sets are aggregated to establish the multi-dimensional database.
According to the embodiment, the unstructured data are decoded and analyzed to extract the key information in the unstructured data, so that the data size in the database can be increased, and the integration level of the battery data and the accuracy of data query are improved.
In some embodiments of the present application, before performing a query in the multidimensional database to obtain a query result corresponding to the data query request, the method of this embodiment further includes: summarizing the battery data with the query frequency greater than or equal to the preset query frequency threshold value based on the query frequency of each battery data in the multi-dimensional database and the preset query frequency threshold value to obtain an intermediate data set; wherein, in the case of querying in a multidimensional database, queries are performed from an intermediate dataset.
It can be understood that the amount of data in the battery database is very large, and when data is queried, the time for querying one by one is very long, so in this embodiment, by acquiring the data query frequency, data with high query frequency is put into a new data set, that is, data with high query frequency is concentrated in an intermediate data set, and when data query is performed, query can be performed in the intermediate data set, so as to improve the data query speed.
The preset query frequency threshold can be set in a self-defined mode according to the actual query quantity, and can also be set in a self-defined mode according to the data storage quantity of the intermediate data set.
In order to control the data storage amount of the intermediate data set, in one example, sub-data such as a key list, a sub-item list, a common search key item, a data trace chain and the like in the battery data may be extracted, and these sub-data are extracted into the intermediate data set in a sorted manner, that is, it is not necessary to extract all battery data corresponding to one item or one product into the intermediate data set, but key information in battery data corresponding to one item or one product is extracted into the intermediate data set.
According to the embodiment, according to the query frequency of the battery data, the battery data with high query frequency is placed in the middle data set, and under the condition of querying in the multi-dimensional database, the query is performed from the middle data set, so that the data query speed is further improved.
In some embodiments of the application, after building the multi-dimensional database, the method further comprises: establishing an association relation between different data in a multidimensional database according to preset association information, wherein the association information comprises one or more of item codes, product names and identification information; and taking the battery data with the association relation as an association set to obtain at least one association set based on the association information.
In this embodiment, the association information includes one or more of item codes, product names, and identification information, so that an association relationship between battery data in different dimensions can be established, and then the battery data with the association relationship is used as an association set, and the association information may include one or more association sets, so that at least one association set based on the association information can be obtained. Therefore, the battery data with the association relationship can be gathered, the correlation degree between query result data can be improved when the data query is carried out, the user can query the required battery data more conveniently, and the accuracy of the data query is improved.
The item code refers to the name of a battery item, the product name refers to the name of a battery or a battery pack or a battery core, the identification information refers to the uniform identification of a certain type of product, and the identification information can be a coded identifier such as a bar code or a two-dimensional code.
In one example, the battery project may include data of multiple dimensions of battery design information, process data, test data and material data, so that the battery data of different dimensions are associated according to project codes, for example, the associated information includes project codes a and product names B, and the obtained associated set includes an associated set of project codes a and an associated set of product names B. Therefore, when the user queries according to the project code, all battery data associated with the project code can be uniformly displayed to the user, and the accuracy of data query is improved.
According to the embodiment, the battery data among different dimensions can be associated through the association information, and when the data query request contains the association information, the battery data related to the association information in the battery data of different dimensions can be called, so that the accuracy of the data query is improved.
In some embodiments of the present application, in response to a data query request, a query is performed in a multidimensional database to obtain a query result corresponding to the data query request, including: determining a target association set corresponding to the data query request according to the data query request; and inquiring battery data corresponding to the data inquiry request in the target association set to obtain an inquiry result.
Continuing the above example, the association set includes "item code a association set", "product name B association set", and the data query request is "core material composition data related to item code a", and then the target association set is "item code a association set", and further "item code a association set" is queried for core material composition data related to item code a.
According to the embodiment, the target association set can be quickly positioned according to the data query request, so that the battery data wanted by the user can be accurately searched in the target association set, and the data query precision is improved.
In some embodiments of the present application, analyzing the query result based on a preset rule set to obtain target data includes: taking the query result as input data of a rule engine, and performing data conversion and calculation on the query result by using the rule engine and a preset rule set to obtain a calculation result; and converting the calculation result into a format to obtain a calculation result in a chart format as target data.
Among them, a Rule Engine (Rule Engine) is a software system for managing and executing rules or conditions and making decisions or inferences based on the rules. Rule engines are typically used to automate the processing of a large number of business rules, conditions, or logic so that the system may operate autonomously or provide suggestions based on these rules.
The preset rule set in this embodiment is a set of data analysis logic set according to a user requirement, and the data analysis logic set according to the user requirement may include preset calculation logic, logic triggering conditions, a desired target data form, and the like.
The preset rule set can be written into the rule engine through the rule engine editor, namely, a user can write the rule set through the rule engine editor, and then the rule set is embedded into the rule engine. The algorithm rule can be edited by a user conveniently, and data calculation, inspection and analysis can be performed.
In this embodiment, the query result is used as input data of the rule engine, the rule engine may perform data conversion and calculation on the query result by using a preset rule set to obtain a calculation result, where the calculation result is a data type supporting output of a chart, and then the calculation result may be used as input of drawing software, and the drawing software may perform format conversion on the calculation result to obtain a calculation result in a chart format as target data.
For example, in the case where the query result is "the positive electrode material of the battery generally includes lithium cobaltate, ternary material, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate, or the like". The rule set preset by the user is "the query results are ordered according to the importance degree of the components and output according to the form of the table". The "positive electrode material of the battery typically includes lithium cobaltate, ternary material, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate, etc." is converted into a table form as target data.
The embodiment can provide a channel for the user to interact with the battery data query system, improves the interaction capability of the system, can facilitate the user to set the rule set according to the self requirement, and improves the flexibility of data query.
In some embodiments of the present application, battery data of different dimensions have different query rights, and the method of the present embodiment further includes: determining the queriable battery data of the user according to the authority information of the user; responding to the data query request of the user, and querying in the queriable battery data to obtain a query result corresponding to the data query request.
It can be understood that the battery data is important data for each enterprise, especially the confidentiality of the battery research and development data is important for the battery enterprise, so that the battery data with different confidentiality degrees needs to be provided with certain query authorities, correspondingly, users with different levels also need to be provided with authorities, and the users are allowed to query only if the users have the authorities for querying certain battery data, thereby improving the safety of the battery data and reducing the risk of data leakage.
When receiving a data query request of a user, the embodiment can acquire the authority information of the user, so as to determine the queriable battery data of the user, further determine the queriable battery data range corresponding to the authority information of the user, and query in the queriable battery data range, further improve the safety of the battery data of enterprises.
In the embodiment of the application, one-stop integration of battery research and development data is realized, the time consumption for inquiring caused by scattered omission of data can be reduced, the data inquiring efficiency is improved, the target data which meets the requirements of users can be obtained, the self-service analysis of the battery data by the users is realized, and the data inquiring precision and flexibility are further improved.
The foregoing description of various embodiments is intended to highlight differences between the various embodiments, which may be the same or similar to each other by reference, and is not repeated herein for the sake of brevity.
The following describes a battery data query method according to some embodiments of the present application in a specific example. The method is described by taking cell research and development data as an example.
In the specific example, the processing data, the test data, the material data and the like included in the battery cell research and development data are gathered and integrated together from storage addresses such as a cloud end, a server and an off-line memory, a multidimensional database is established according to different types of data, and one-stop integration of all battery cell research and development data is realized. When unstructured data exists in the data, transcoding and analyzing the unstructured data to obtain key information, and then converging the key information.
When a user inputs a data query request through a software operation page, authority information of the user is detected, if the user has authority to query all data in a multidimensional database, a query result corresponding to the data query request is queried in the multidimensional database, for example, the data query request is "what positive electrode materials of a battery include", and the query result obtained by querying in the multidimensional database is "the positive electrode materials of the battery generally include lithium cobaltate, ternary materials, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate and the like".
If the user only has the right to query a part of the battery data, the user only searches in the part of the battery data.
Because the data volume of the battery data is huge, the possible content of the obtained query result may be too large, the user can further analyze the query result through a preset rule set, and the above example is continued, where the query result is "the positive electrode material of the battery generally includes lithium cobaltate, ternary material, lithium iron phosphate, lithium nickel manganese cobalt oxide, sodium phosphate, and the like". The rule set preset by the user may be "output the query result in order according to the importance degree of the component". The embodiment outputs the target data matched with the user requirement according to the preset rule set.
In addition, in an example, the embodiment may also support statistics on the access amount of the user, share the queried battery data to others, and link the system of the embodiment with other platforms to realize functions such as data sharing, problem feedback, and the like.
The foregoing description of various embodiments is intended to highlight differences between the various embodiments, which may be the same or similar to each other by reference, and is not repeated herein for the sake of brevity.
Some embodiments of the present application further provide a battery data query system, fig. 2 shows a schematic structural diagram of the battery data query system provided in the embodiment of the present application, and referring to fig. 2, the battery data query system 400 includes:
The data aggregation module 401 is configured to build a multidimensional database, where the multidimensional database includes a plurality of data sets, each data set includes at least one dimension of battery data, and the dimension of the battery data includes one or more of a battery process dimension, a battery test dimension, and a material dimension.
The data query module 402 is configured to perform a query in the multidimensional database in response to a data query request, and obtain a query result corresponding to the data query request.
The data analysis module 403 is configured to analyze the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
In one example, the battery data includes structured data and unstructured data, and the data aggregation module 401 is configured to decode and analyze the unstructured data to obtain key information in the unstructured data; and classifying the structured data and the key information according to the dimension of the battery data to obtain a multi-class data set.
In one example, the data query module 402 is configured to, before querying the multidimensional database to obtain a query result corresponding to the data query request, summarize, based on a query frequency of each battery data in the multidimensional database and a preset query frequency threshold, battery data with a query frequency greater than or equal to the preset query frequency threshold to obtain an intermediate data set; wherein, in case of a query in the multi-dimensional database, the query is performed from the intermediate dataset.
In one example, the data aggregation module 401 is configured to, after establishing a multidimensional database, establish an association relationship between different data in the multidimensional database according to preset association information, where the association information includes one or more of item codes, product names, and identification information; and taking the battery data with the association relation as an association set to obtain at least one association set based on the association information.
In one example, the data query module 402 is configured to determine, according to the data query request, a target association set corresponding to the data query request; and inquiring battery data corresponding to the data inquiry request in the target association set to obtain the inquiry result.
In one example, the data analysis module 403 is configured to use the query result as input data of a rule engine, and perform data conversion and calculation on the query result by using the rule engine and the preset rule set to obtain a calculation result; and carrying out format conversion on the calculation result to obtain a calculation result in a chart format as the target data.
In one example, the battery data with different dimensions have different query rights, and the data query module 402 is further configured to determine the queriable battery data of the user according to the rights information of the user; responding to a data query request of a user, and querying in the queriable battery data to obtain a query result corresponding to the data query request.
The battery data query system provided by the above embodiment of the present application and the battery data query method provided by the embodiment of the present application have the same beneficial effects as the method adopted, operated or implemented by the application program stored therein, because of the same application conception.
The embodiment of the application also provides an electronic device corresponding to the battery data query method provided by the embodiment, so as to execute the battery data query method. The embodiment of the application is not limited.
Referring to fig. 3, a schematic diagram of an electronic device according to some embodiments of the present application is shown. As shown in fig. 3, the electronic device 20 includes: a processor 200, a memory 201, a bus 202 and a communication interface 203, the processor 200, the communication interface 203 and the memory 201 being connected by the bus 202; the memory 201 stores a computer program executable on the processor 200, and the processor 200 executes the method according to any of the foregoing embodiments of the present application when the computer program is executed.
The memory 201 may include a high-speed random access memory (RAM: random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 203 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
Bus 202 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. The memory 201 is configured to store a program, and the processor 200 executes the program after receiving an execution instruction, and the method for querying battery data disclosed in any of the foregoing embodiments of the present application may be applied to the processor 200 or implemented by the processor 200.
The processor 200 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 200 or by instructions in the form of software. The processor 200 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), etc.; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 201, and the processor 200 reads the information in the memory 201, and in combination with its hardware, performs the steps of the above method.
The electronic equipment provided by the embodiment of the application and the battery data query method provided by the embodiment of the application have the same application conception and the same beneficial effects as the method adopted, operated or realized by the electronic equipment.
The present application further provides a computer readable storage medium corresponding to the battery data query method provided in the foregoing embodiment, please refer to fig. 4, which illustrates a computer readable storage medium 30, the computer readable storage medium 30 may be an optical disc, the optical disc may have a program product stored thereon, the program product may be an operating system, application software, tool software, etc., and the program product includes a computer program, where the computer program usually exists in a source code or a binary form after compiling, and when the computer program is executed by a processor, the computer program performs the battery data query method provided in any of the foregoing embodiments.
It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.
The computer readable storage medium provided by the above embodiment of the present application has the same advantages as the method adopted, operated or implemented by the application program stored in the computer readable storage medium, because of the same application conception as the method for querying the battery data provided by the embodiment of the present application.
It should be noted that:
In the above text, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above embodiments, which are merely illustrative, not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
Claims (10)
1. A method for querying battery data, the method comprising:
Establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, each data set comprises at least one dimension of battery data, and the dimension of the battery data comprises one or more of a battery process dimension, a battery test dimension and a material dimension;
Responding to a data query request, and querying in the multidimensional database to obtain a query result corresponding to the data query request;
Analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
2. The method of claim 1, wherein the battery data comprises structured data and unstructured data, and wherein the creating a multi-dimensional database comprises:
decoding and analyzing the unstructured data to obtain key information in the unstructured data;
Classifying the structured data and the key information according to the dimension of the battery data to obtain a multi-class data set;
and establishing the multi-dimensional database according to the multi-class data set.
3. The method for querying battery data according to claim 1, wherein before querying in the multidimensional database to obtain a query result corresponding to the data query request, the method further comprises:
summarizing the battery data with the query frequency greater than or equal to the preset query frequency threshold value based on the query frequency and the preset query frequency threshold value of each battery data in the multi-dimensional database to obtain an intermediate data set;
Wherein, in case of a query in the multi-dimensional database, the query is performed from the intermediate dataset.
4. The method of querying battery data as claimed in claim 1 or 2, wherein after establishing the multi-dimensional database, the method further comprises:
Establishing an association relation between different data in the multidimensional database according to preset association information, wherein the association information comprises one or more of project codes, product names and identification information;
And taking the battery data with the association relation as an association set to obtain at least one association set based on the association information.
5. The method according to claim 4, wherein the querying in the multidimensional database in response to the data query request to obtain the query result corresponding to the data query request comprises:
determining a target association set corresponding to the data query request according to the data query request;
and inquiring battery data corresponding to the data inquiry request in the target association set to obtain the inquiry result.
6. The battery data query method according to claim 1, wherein the analyzing the query result based on the preset rule set to obtain the target data includes:
taking the query result as input data of a rule engine, and performing data conversion and calculation on the query result by using the rule engine and the preset rule set to obtain a calculation result;
and carrying out format conversion on the calculation result to obtain a calculation result in a chart format as the target data.
7. The method of claim 1, wherein battery data of different dimensions have different query rights, the method further comprising:
determining the queriable battery data of a user according to authority information of the user;
Responding to a data query request of a user, and querying in the queriable battery data to obtain a query result corresponding to the data query request.
8. A battery data query system, the system comprising:
the data aggregation module is used for establishing a multi-dimensional database, wherein the multi-dimensional database comprises a plurality of data sets, each data set comprises at least one dimension of battery data, and the dimension of the battery data comprises one or more of a battery process dimension, a battery test dimension and a material dimension;
The data query module is used for responding to a data query request, querying in the multidimensional database and obtaining a query result corresponding to the data query request;
the data analysis module is used for analyzing the query result based on a preset rule set to obtain target data; the preset rule set is a set of data analysis logic set according to user requirements.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor running the computer program to implement the method of querying battery data as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program is executed by a processor to implement a method of querying battery data according to any of claims 1-7.
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