New energy automobile structured table collaborative management and integration method

Abstract

The invention discloses a new energy automobile structured table collaborative management and integration method. The method comprises the following steps: constructing a semantic mapping rule of a new energy automobile system structured table based on an OSLC specification; according to the semantic mapping rule, distributing a unique URI (Uniform Resource Identifier) for each table unit, and constructing a parameter access interface based on a RESTful architecture; constructing a table tool adapter based on the parameter access interface, wherein the adapter is used for converting a data format between data of a structured table and OSLC resources; a multi-source table version management module is integrated in the table tool adapter, and bidirectional synchronous conversion of heterogeneous data sources, historical tracking of parameter modification and version comparison are executed; according to the method, unified standardized expression of cross-format and cross-source table data is realized, and the efficiency of heterogeneous data integration is improved.

Description

Technical Field

[0001] The present invention belongs to the field of MBSE, and particularly relates to a collaborative management and integration method for structured tables of new energy vehicles. Background Art

[0002] In recent years, the new energy vehicle industry has shown a rapid development trend, with significantly improved technical complexity and system integration. The design and optimization of core subsystems such as power batteries, electric drive systems, and energy management require multi-disciplinary collaboration, involving dynamic adjustment and sharing of a large number of technical parameters. During the R & D process, parameter data is usually stored in the form of structured tables, covering key information such as battery performance, motor specifications, and control strategies. With the increasing demand for cross-departmental and cross-enterprise collaboration, the generation, management, and exchange of parameter tables have become important links in the design of new energy vehicle systems. At the same time, there are many participants in the industry ecosystem, including vehicle manufacturers, component suppliers, simulation tool developers, etc. There are differences in the definition, storage, and transmission methods of technical parameters among all parties, resulting in challenges in data interaction.

[0003] Currently, the management of tabular data in the R & D of new energy vehicles mainly relies on general collaboration platforms (such as Microsoft 365), which provide basic table editing and sharing functions and support multi-user online collaboration. For example, Microsoft 365 allows teams to simultaneously edit the same Excel file in the cloud and avoid conflicts through file-level or worksheet-level locking mechanisms.

[0004] However, the existing technologies mainly focus on the centralized editing of a single table file, do not support the automatic conversion and integration of heterogeneous tables, the table formats lack standardization, and the data structures generated by different tools vary greatly, resulting in low cross-platform data integration efficiency. Summary of the Invention

[0005] Object of the Invention: The object of the present invention is to provide a collaborative management and integration method for structured tables of new energy vehicles that can achieve collaborative management and data integration of structured tables of new energy vehicle systems.

[0006] Technical Solution: The collaborative management and integration method described in the present invention includes the following steps:

[0007] (1) Construct semantic mapping rules for structured tables of new energy vehicle systems based on the OSLC specification, enabling table data from different sources to be mapped and interoperated based on a common semantic framework, and solving the problem of format heterogeneity;

[0008] (2) According to the semantic mapping rules, assign a unique URI identifier to each table cell to make it an independently addressable resource, and build a parameter access interface based on the RESTful architecture to support programmatic access and modification of parameter data, improving data accessibility and integration capabilities;

[0009] (3) Build a table tool adapter based on the parameter access interface. The adapter is used to convert the data format between structured table data and OSLC resources, realizing seamless integration of heterogeneous table data and reducing manual conversion costs;

[0010] (4) Integrate a multi-source table version management module in the table tool adapter to perform two-way synchronous conversion of heterogeneous data sources, historical tracking of parameter modifications, and version comparison to ensure data consistency and optimize the multi-team collaborative design process.

[0011] Preferably, the construction of the semantic mapping rules in step 1 includes:

[0012] Parse the structured table file of the new energy vehicle system to obtain the header structure, cell data, and worksheet relationships, and convert the table content in different formats into a standardized data structure that conforms to the OSLC specification; establish a table data tree based on the standardized data structure, where the root node corresponds to the table file, and the child nodes correspond to the parameter worksheet, data area, and cell in sequence; attach attribute information to each node of the table data tree, including data type, valid value range, measurement unit, update time, and person in charge, realizing semantic alignment and structured organization of table data in different formats, and laying a standardized foundation for subsequent fine-grained data access, version management, and system integration.

[0013] Preferably, the conversion of the table content in different formats into a standardized data structure that conforms to the OSLC specification includes:

[0014] Map the OSLC service provider directory to the central repository of all parameter tables of new energy vehicles;

[0015] Map the OSLC service provider to the worksheet of the structured table of the new energy vehicle system;

[0016] Map the OSLC service to the query, addition, deletion, modification, and merging operations of internal cells, rows, columns, and region blocks in the structured table of the new energy vehicle system;

[0017] Map the OSLC resource to the cell value and header definition in the structured table of the new energy vehicle system.

[0018] This mapping mechanism realizes the complete digital expression from the system architecture to specific parameters, bridges the semantic gap between traditional tabular data and the MBSE tool chain, enabling each tabular element to be accurately accessed and manipulated in the form of a standardized service; through this deep integration, it not only retains the tabular operation paradigm familiar to engineers but also endows the parameter data with semantic interaction capabilities for systems engineering, providing native support for the full lifecycle management of design data.

[0019] Preferably, the association relationships between the nodes of the tabular data tree include: the design dependency relationship between the vehicle power performance table and the electric drive system selection table; the spatial constraint relationship between the body layout parameter table and the battery pack structure table.

[0020] By intelligently identifying and explicitly establishing the engineering semantic associations between different tables, the originally isolated parameter tables form a data network with engineering logic. This structured expression of the association relationships enables automatic impact domain analysis of parameter changes, significantly enhancing the coordination of multi-system parallel development and the scientific nature of design decisions, providing intelligent associated data support for complex system parameter optimization.

[0021] Preferably, the parameter access interface described in step 2 includes:

[0022] The data layer, which is used to interact with the structured tabular file of the new energy vehicle system and perform format conversion and content extraction;

[0023] The service layer, which is used to implement the service functions defined by the OSLC specification and handle resource mapping and relationship management;

[0024] The interface layer, which provides a standardized RESTful API to achieve external system integration;

[0025] The service layer also includes a concurrency control mechanism to manage the parallel access of multiple users to the parameter units in the structured table.

[0026] By constructing a well-structured parameter access interface system, external systems can accurately access specific parameter units through standardized interfaces, while ensuring data consistency during parallel modification by multiple users. This not only meets the real-time call requirements of the MBSE tool chain for parameter data but also solves the resource competition problem existing in traditional tabular collaboration, providing high-reliability and high-concurrency data service support for the collaborative R & D of new energy vehicles.

[0027] Preferably, the interface layer is also used to provide operations on the structured table:

[0028] Obtain cell values, table structure information, cell formats, and merged region definitions through the GET method;

[0029] Add new parameter entries, create new worksheets, insert new rows or columns at specified positions via the POST method;

[0030] Modify cell values and update cell formats via the PUT method;

[0031] Delete parameter entries, remove entire rows or columns, and split merged cells via the DELETE method.

[0032] Such operations on structured tables not only achieve remote operations on fine-grained elements such as cell values, formats, and merged regions, but also innovatively transform table editing actions into traceable API call sequences, enabling the parameter modification process to maintain both the user-friendly operation logic of Excel and the version control and automated integration capabilities at the software development level, providing a technical foundation for cross-platform data collaboration and CI / CD process integration.

[0033] Preferably, the table tool adapter described in step 3 can achieve the following functions:

[0034] Convert structured table files including Excel workbooks, relational database tables, and proprietary format data files into standardized OSLC resources;

[0035] Synchronize changes in the standardized OSLC resources back to the original table files;

[0036] Support parallel collaborative editing of multidisciplinary parameters such as battery systems, motor drives, thermal management, and control algorithms.

[0037] These functions not only break down the data barriers between traditional engineering tables and the MBSE tool chain, but also enable parallel collaborative editing of cross-disciplinary parameters such as batteries, electric drives, and thermal management. This adaptation mechanism not only retains the original tool usage habits of each professional team but also ensures the automatic synchronization and consistency maintenance of parameter changes, significantly improving the efficiency and data reliability of multidisciplinary collaborative design.

[0038] Preferably, the table tool adapter described in step 3 can also provide the following integration capabilities:

[0039] Directly access parameter constraints through system architecture design tools for architecture optimization;

[0040] Obtain material parameters and boundary conditions through multi-physics field simulation tools;

[0041] Access control parameters through control system development tools for algorithm verification;

[0042] Perform fault prediction based on component parameters through reliability analysis tools.

[0043] This all-round toolchain integration not only breaks through the information silos in traditional parameter management, but also constructs a collaborative design environment linked by parameter data, enabling all aspects from conceptual design to simulation verification to work based on a unified and real-time parameter benchmark, improving the overall efficiency and design quality of new energy vehicle development.

[0044] Preferably, the multi-source table version management mechanism described in step 4 can achieve the following functions:

[0045] Assign a unique version identifier to the change of each parameter cell;

[0046] Record the values before and after modification and describe the modification information;

[0047] Construct a parameter change chain to track the complete evolution process of multidisciplinary parameters from the initial design to the finalization.

[0048] These functions realize the full life cycle tracking of each parameter unit by establishing a fine-grained parameter version management system. This atomic-level version control mechanism enables designers to trace back the iteration process of any parameter, analyze the formation path of key design decisions, and at the same time support the difference comparison based on historical versions and the selective rollback of parameters, providing a data basis for the impact assessment of design changes and the precipitation of design experience, significantly improving the traceability of parameter management and the repeatability of the design process.

[0049] Preferably, the multi-source table version management mechanism described in step 4 includes the following modules:

[0050] Version branch control module, creating independent parameter branches for different team design directions;

[0051] Version comparison module: Provide a comparison view to highlight the parameter differences between different versions;

[0052] Version merging module: Provide a parameter-level merging tool to integrate the optimal results.

[0053] These modules realize the design paradigm of multi-team parallel exploration in the new energy vehicle R & D process, retaining design diversity while ensuring system compatibility. This version management mechanism not only solves the version conflict problem in traditional serial development, but also forms a closed-loop design process of "exploration - comparison - optimization", greatly improving the innovation efficiency of complex system design and the robustness of technical solutions.

[0054] Beneficial effects: Compared with the prior art, the present invention has the following remarkable advantages: 1. It realizes the unified and standardized expression of cross-format and cross-source tabular data, improving the efficiency of heterogeneous data integration; 2. Through the URI resource identifier and RESTful service interface, it breaks through the limitations of traditional file-level locking and realizes the parallel editing ability of different parameter units in the same table by multi-disciplinary teams; 3. Through the table tool adapter, on the premise of keeping the original tool chain unchanged, it realizes the automatic alignment and consistency maintenance of design parameters; 4. It supports the full-process parameter change tracking from requirement definition to detailed design, and can quickly locate the historical version, modification reason and associated impact of any parameter, making the design decision-making process completely transparent. Description of the Drawings

[0055] Figure 1 is a flowchart of the present invention;

[0056] Figure 2 is a schematic diagram of the structured table and semantic mapping rules of the present invention;

[0057] Figure 3 is a schematic diagram of the resource identifier and service interface of the present invention. Detailed Embodiments

[0058] The technical solution of the present invention will be further described below with reference to the drawings.

[0059] The structured table collaborative management and integration method described in the present invention uses the OSLC specification to parse and construct a standardized expression and service-oriented access framework for parameter tables, realizing the unified management and efficient integration of tabular data from different sources. By establishing semantic mapping rules and a resource identifier system for parameter resources, static table units are transformed into accessible network resources, realizing collaborative editing of parameters, providing a basis for seamless integration of configuration parameter data and the MBSE tool chain, and also providing a parameter configuration management mechanism throughout the entire design process for the new energy vehicle system R & D process.

[0060] As Figure 1 shown, the method includes the following steps:

[0061] Step 1, parsing the structured table of the new energy vehicle system based on the OSLC specification and constructing semantic mapping rules to realize the standardized expression of table data.

[0062] OSLC is a technical specification proposed by IBM for tool integration and collaboration within the MBSE lifecycle, which can provide a unified method to manage and operate various models and their data in lifecycle management tools. The OSLC specification consists of a core specification and domain specifications. The core specification standardizes and describes the most core integration concepts of the OSLC specification and the general features supported by OSLC services. The OSLC core model includes a service provider catalog, service providers, services, and resources.

[0063] As Figure 2 shown, through the OSLC specification, the structured tabular data resources of new energy vehicle systems are uniformly described. Based on an in-depth analysis of the design information and parameter tables of new energy vehicle systems, key information such as the header structure, cell data, and worksheet relationships in the tables are obtained, and a complete set of mapping rules is constructed to convert the table contents in different formats (such as the basic information table, charging management table, and battery parameter table in Excel; the motor parameter table and thermal management parameter table in the export format of a proprietary database; the energy consumption analysis table, driver assistance system table, and vehicle maintenance and repair table in other format tables, etc.) into a standardized data structure expression that conforms to the OSLC specification.

[0064] Based on the Open Services Lifecycle Collaboration (OSLC) specification, semantic mapping rules between the OSLC core model and the structured tables of new energy vehicle systems are established, the object element mapping relationship between the two is clarified, and the standardized expression of the tabular data of new energy vehicle systems is realized. The semantic mapping rules between the OSLC core model and the structured tables of new energy vehicle systems are shown in Table 1:

[0065] Table 1 OSLC Core Specification and Structured Table Mapping Objects

[0066] OSLC framework Structured table Service provider directory New energy vehicle parameter table file Service provider Worksheet Service Table operation set (table query, addition, deletion, modification, merging, etc.) Resource Cell value (battery capacity, motor power, etc.)

[0067] According to this mapping structure, the service provider catalog in the OSLC specification is the top-level concept in OSLC, responsible for managing and organizing multiple service providers, providing a unified access entry, corresponding to the table file in the structured table of the new energy vehicle system, that is, the central repository of all parameter tables; the service provider representatives in the OSLC specification provide containers or partitions for specific services, corresponding to multiple worksheets in the structured table of the new energy vehicle system, providing a standardized access mechanism; the operation methods such as creation, reading, update, and deletion of service definition resources in the OSLC specification ensure the consistency of data operations, thus realizing consistent interaction with parameter units, corresponding to operations such as query, addition, deletion, modification, and merging of internal cells, rows, columns, and region blocks in the structured table of the new energy vehicle system; the resources in the OSLC specification are the specific data units processed in the OSLC service, uniquely identified by a URI, and can be accessed and operated independently, corresponding to basic elements such as cell values and header definitions in the structured table of the new energy vehicle system.

[0068] Furthermore, data parsing is performed on the table file to obtain key information such as the structural hierarchy of the table, cell values, and relationships between tables, as well as different interfaces (query, addition, deletion, modification, etc.) of the table operation set, ensuring the smooth integration of table data. When parsing the structured table of the new energy vehicle system, three types of key information need to be processed: table structure information, cell content information, and cross-table relationship information. Table structure information includes worksheet names, header definitions, merged cell regions, etc.; cell content information includes different types of data such as numerical values, text, and dates; cross-table relationship information records the overall information association relationships between tables, and this association reflects the dependencies and constraints between parameter sets in different domains during the design process. For example, the configuration selection of the electric drive system parameter table must be based on the acceleration requirements and maximum speed targets defined in the vehicle power performance index table; similarly, the battery pack structure design parameter table needs to comply with the size limit conditions in the vehicle layout space parameter table. These table-level association relationships constitute the information network framework for the design of the new energy vehicle system, ensuring that different professional design teams can carry out collaborative development based on unified design constraints. The associations between tables not only affect parameter selection but also determine the feasibility boundaries and optimization directions of the design scheme, and are the basis for achieving system-level performance goals. Based on the judgment of the key information of the table, it is decided that the parsing process adopts a recursive method: first, identify all table files and their worksheets in the table library; then parse the structural information of each worksheet, including the number of rows and columns, header definitions, data types, etc.; finally, extract the content and attributes of specific cells. The parsing result forms a structured table data tree, retaining the hierarchical structure and technical content of the original table, while adding standardized identifiers and semantic information.

[0069] The structure of the tabular data tree usually adopts a multi-level design: the root node represents the entire new energy vehicle system parameter tabular file; the second-level nodes represent parameter worksheets in different fields, such as the battery parameter table, the motor parameter table, the thermal management parameter table, etc.; the third level is the data area in the worksheet, such as the "performance indicators" area and the "temperature characteristics" area in the battery parameter table; the bottom layer is the specific cell. Each node contains its specific attributes, such as the data type, valid value range, measurement unit, update time, person in charge, etc. of the cell. The association relationships between nodes reflect the overall design dependencies and constraint relationships between different tables. For example, there is an upstream and downstream design dependency between the vehicle power performance table and the electric drive system selection table, and the performance indicators in the power performance table directly constrain the parameter selection of the electric drive system; there is a spatial constraint relationship between the body layout parameter table and the battery pack structure table, and the available space defined by the former directly limits the design scheme of the latter. These table-level association relationships are identified by the system to ensure that when the upstream design table changes, the relevant downstream tables can receive notifications and make corresponding adjustments to maintain the consistency and feasibility of the overall design.

[0070] The above mapping and parsing mechanism effectively solves the problems of unified expression of new energy vehicle structured tables and standardization of data formats. By establishing a unified mapping mechanism and performing table parsing, it is ensured that the table information provided by teams in different disciplinary fields can be standardized and integrated while maintaining the original semantics, providing a basis for subsequent table cells to be accessed as independent resources.

[0071] Step 2, implement fine-grained access control for table cells through resource identification and service interface technologies, and build a standardized access mechanism at the parameter level.

[0072] Based on the constructed parsing and mapping framework, each table cell is transformed into an independently accessible network resource, and a standardized interaction interface system is built. This transformation makes the table cell change from a static data entry to a dynamically operable data resource, realizing precise management and access control at the cell level.

[0073] As Figure 3 shown, first, for each cell in the structured table, such as the "rated capacity" cell in the battery configuration table and the "peak power" cell in the motor parameter table, a unique URI that conforms to the specification is assigned. The URI design adopts a hierarchical path structure, including the category and hierarchical relationship of the table, ensuring that it can be accurately located and accessed. Taking the new energy vehicle system parameter table as an example, the energy density cell in the battery parameter table is mapped to the resource concept in OSLC, through semantic tags <oslc>Describe, and represent the energy density parameter by the URI value "http: / / ev-parameters.com / battery / energy-density", and "XXX / motor / power / peak" represents the motor peak power parameter. This resource-based identification makes each table cell an independently addressable entity, providing a basis for fine-grained access.

[0074] Based on the resource-based identification, build a service interface based on the RESTful architecture to achieve standardized operations on parameter resources. Through methods such as GET, POST, PUT, and DELETE of the HTTP protocol, achieve detailed management of the structured table of the new energy vehicle system. Specifically, the GET method can be used to obtain cell values, and also supports obtaining metadata such as table structure information, cell format, and merged area definition. For example, accessing the resource with the URI "http: / / ev-parameters.com / battery / B001 / properties" using the GET method can obtain all property information of the battery specification numbered B001, and all merged cell range definitions can be obtained through "XXX / structure / merged-cells"; the POST method can be used to create new resources, including adding new parameter entries, creating new worksheets, inserting new rows or columns at specific positions, etc. For example, using the POST method to add new thermal management parameters to "XXX / thermal", inserting a new row at the 5th row position of the motor parameter table through "XXX / motor-table / row?position=5", and inserting a new column before column C of the battery parameter table through "XXX / battery-table / column?position=C"; the PUT method can be used to update existing resources, including modifying cell values, updating cell formats, etc. For example, using the PUT method to update the corresponding resource of "XXX / battery / B001 / energy-density" can modify its energy density value, and merging the cells in the area from A1 to B5 into a single cell area through "XXX / cells / A1 / merge"; the DELETE method can be used to delete resources, including deleting parameter entries, removing entire rows or columns, splitting merged cells, etc. For example, using the DELETE method to delete the deprecated control parameters corresponding to "XXX / controller / deprecated-params", deleting the 8th row of the motor parameter table through "XXX / motor-table / row / 8", deleting column F of the battery parameter table through "XXX / battery-table / column / F", and splitting the merged cell area back into independent cells through "XXX / cells / A1 / unmerge".

[0075] To support the implementation of these service interfaces, a dedicated table data service layer is developed in this step. This service layer adopts a three-layer structure: the data layer is responsible for interacting with the original table files to implement format conversion and content extraction; the service layer implements the service functions defined by the OSLC specification to handle resource mapping and relationship management; the interface layer provides standardized RESTful APIs to support external system integration. The service layer particularly implements a concurrency control mechanism at the parameter level, allowing multiple users to edit different parameter units simultaneously without interfering with each other. For example, when the battery team modifies the energy density parameter, the motor team can update the power parameter at the same time, and the control team can adjust the relevant algorithm parameters to achieve true parallel collaborative work.

[0076] This table management mode based on resource identification and service interfaces also lays a foundation for the subsequent integration of the MBSE toolchain and parameter data. Through standardized RESTful interfaces, system architecture design tools can directly query key performance parameters (such as battery energy density, motor maximum power, etc.), and simulation verification tools can automatically obtain the parameter values required for calculations without manual transcription, thus eliminating human errors in the data transfer process. For example, the vehicle performance simulation tool can directly call "http: / / ev-parameters.com / battery / energy-density" through the API to obtain the latest battery energy density value and apply it to the calculation of the driving range. This forward-looking technical framework provides a new approach for the digital collaborative design of new energy vehicle systems throughout their life cycle.

[0077] Step 3: Build a table tool adapter to enable collaborative editing of multidisciplinary design parameters in the new energy vehicle system design process, providing a basis for seamless integration of configuration parameter data and the MBSE toolchain.

[0078] After completing the service construction of the table data, build a table tool adapter to achieve two-way data exchange between mainstream table tools and OSLC services. As an intermediate layer, the adapter, on the one hand, reads and parses the original data from different table tools and converts it into standardized OSLC resources; on the other hand, it synchronizes the changes of the standardized resources back to the original table files to maintain data consistency.

[0079] Based on the table tool adapter, collaborative editing of multidisciplinary design parameters for new energy vehicle systems can be achieved. The design of new energy vehicles involves close collaboration among multiple professional fields such as battery systems, motor drives, thermal management, and control algorithms. Through the parameter-level access control provided by the adapter, different teams can operate on their respective parameter sets in parallel. For example, during the vehicle parameter optimization phase, the battery team can update parameters such as the energy density and cycle life of battery cells in real time; the drive system team can synchronously adjust indicators such as the power density and efficiency curve of the motor; the thermal management team can optimize the heat transfer coefficient and fluid parameters of the cooling system; and the control algorithm team can adjust control strategies and parameters based on the latest hardware parameters. These teams access and update their respective parameters through standardized service interfaces. Through this fine-grained parallel collaboration mechanism, the iteration cycle of new energy vehicle system design can be significantly shortened, transforming from the traditional serial collaboration method to an efficient parallel collaboration mode.

[0080] In addition, the table tool adapter also provides a basis for seamless integration of configuration parameter data with the MBSE tool chain. Through standardized service interfaces, various MBSE tools can directly access the latest parameter data. For example, system architecture design tools can automatically optimize the architecture based on parameter constraints; multi-physics field simulation tools can obtain accurate material parameters and boundary conditions; control system development tools can access the latest control parameters for algorithm verification; and reliability analysis tools can perform fault prediction based on component parameters. This seamless integration greatly improves data consistency and work efficiency in the design process, avoiding errors and delays caused by manual data transcription in the traditional method. At the same time, since all tools are based on the same source of parameter truth, when parameters change, all relevant analysis and design activities can be updated in a timely manner, ensuring that design decisions are based on the latest data. This intelligent parameter propagation mechanism ensures efficient collaboration among multidisciplinary teams for design changes, ultimately forming a complete and consistent set of new energy vehicle system design parameters, providing a reliable source of authoritative truth for subsequent detailed design and development.

[0081] Step 4: Build a multi-source table version management mechanism to support two-way synchronous conversion of heterogeneous data sources, while implementing historical tracking and version comparison of parameter modifications, and supporting the rollback ability at the single-parameter level

[0082] Based on the first three steps, further build a multi-source table version management mechanism. Through the complete tracking and management of parameter changes in the new energy vehicle system design process, provide historical tracking, version comparison, and selective rollback capabilities of parameter modifications to achieve version branch management in the design parallel development scenario.

[0083] First, through the table tool adapter to support the conversion of heterogeneous data sources, the system can process parameter tables from different sources such as Excel workbooks, relational database tables, and proprietary format data files, ensuring that operations can be carried out under a unified parameter management framework regardless of the data source. On this basis, the core function of the system is to introduce a version management mechanism at the parameter level, creating a detailed historical record for each parameter modification. The system assigns a unique version identifier to the change of each parameter cell, records information such as the values before and after the modification, and constructs a complete parameter change chain. Through this fine-grained version control, the system can accurately track the complete evolution process of each parameter from the initial design to the final determination.

[0084] The version management function specifically implements three core features: branch control, version comparison, and version merging. The version branch control and merging function can support parameter integration in parallel development scenarios. The version comparison function provides an intuitive comparison view, highlighting the parameter differences between different versions, which is convenient for design review and change analysis. Through the version comparison function, each team can conduct change analysis and design calibration on the existing design scheme versions during the design process to form the optimal design scheme. During the parallel development process of new energy vehicle systems, different teams may create multiple design schemes based on the same benchmark, forming different branches of parameters. For example, the thermal management team may explore both air-cooled and liquid-cooled solutions simultaneously, and the drive system team may evaluate different motor topologies. Through branch control, the system allows independent parameter branches to be created for different design directions, and each branch can evolve independently without interfering with each other. When it is necessary to compare different schemes or merge the preferred results, the system provides a parameter-level merging tool.

[0085] The parameter-level version management mechanism provides transparency and traceability for design decisions in the new energy vehicle system design process, enabling engineers to understand the evolutionary relationship between each version. At the same time, the version branch control supports the parallel exploration of design schemes, enabling the team to evaluate multiple alternative schemes simultaneously without having to lock in decisions prematurely, greatly enhancing the flexibility and reliability of the design process. These capabilities together ensure the controllability and consistency of parameter changes in the new energy vehicle system design process, prevent parameter chaos, and guarantee design quality.< / oslc>

Claims

1. A structured table collaborative management and integration method for new energy vehicles, characterized in that, Including the following steps: (1) Construct semantic mapping rules for the structured table of the new energy vehicle system based on the OSLC specification; (2) According to the semantic mapping rules, assign a unique URI identifier to each table cell and construct a parameter access interface based on the RESTful architecture; (3) Construct a table tool adapter based on the parameter access interface for converting the data format between the structured table data and the OSLC resources; (4) Integrate a multi-source table version management module in the table tool adapter to perform two-way synchronous conversion of heterogeneous data sources, historical tracking of parameter modifications, and version comparison.

2. The collaborative management and integration method according to claim 1, wherein The construction of the semantic mapping rules described in step 1 includes: Parse the structured table file of the new energy vehicle system to obtain the header structure, cell data, and worksheet relationships, and convert the table content in different formats into a standardized data structure that conforms to the OSLC specification; Establish a table data tree based on the standardized data structure, where the root node corresponds to the table file, and the child nodes correspond to the parameter worksheet, data area, and cell in sequence; Attach attribute information to each node of the table data tree, including data type, valid value range, measurement unit, update time, and person in charge.

3. The collaborative management and integration method according to claim 2, wherein The conversion of the table content in different formats into a standardized data structure that conforms to the OSLC specification includes: Map the OSLC service provider directory to the central repository of all parameter tables of new energy vehicles; Map the OSLC service provider to the worksheet of the structured table of the new energy vehicle system; Map the OSLC service to the query, addition, deletion, modification, and merging operations of internal cells, rows, columns, and region blocks in the structured table of the new energy vehicle system; Map the OSLC resource to the cell value and header definition in the structured table of the new energy vehicle system.

4. The collaborative management and integration method according to claim 2, characterized in that, The association relationships between the nodes of the table data tree include: The design dependency relationship between the vehicle power performance table and the electric drive system selection table; The spatial constraint relationship between the body layout parameter table and the battery pack structure table.

5. The collaborative management and integration method according to claim 1, wherein The parameter access interface described in step 2 includes: The data layer is used to interact with the structured table file of the new energy vehicle system and perform format conversion and content extraction; The service layer is used to implement the service functions defined by the OSLC specification and handle resource mapping and relationship management; The interface layer provides a standardized RESTful API to implement external system integration; The service layer also includes a concurrency control mechanism to manage the parallel access of multiple users to the parameter cells in the structured table.

6. The collaborative management and integration method according to claim 5, wherein The interface layer is also used to provide operations on the structured table: Obtain cell values, table structure information, cell formats, and merged region definitions through the GET method; Add new parameter entries, create new worksheets, insert new rows or columns at specified positions through the POST method; Modify cell values and update cell formats through the PUT method; Delete parameter entries, remove entire rows or columns, and split merged cells through the DELETE method.

7. The collaborative management and integration method according to claim 1, wherein The table tool adapter described in step 3 can implement the following functions: Convert structured table files including Excel workbooks, relational database tables, and proprietary format data files into standardized OSLC resources; Synchronize the changes of the standardized OSLC resources back to the original spreadsheet file; Support parallel collaborative editing of multidisciplinary parameters such as battery systems, motor drives, thermal management, and control algorithms.

8. The collaborative management and integration method according to claim 1, wherein The spreadsheet tool adapter described in step 3 can also provide the following integration capabilities: Directly access parameter constraints through the system architecture design tool for architecture optimization; Obtain material parameters and boundary conditions through the multiphysics simulation tool; Access control parameters through the control system development tool for algorithm verification; Perform fault prediction based on component parameters through the reliability analysis tool.

9. The collaborative management and integration method according to claim 1, wherein The multi-source spreadsheet version management mechanism described in step 4 can achieve the following functions: Assign a unique version identifier to the change of each parameter cell; Record the values before and after the modification and describe the modification information; Build a parameter change chain to track the complete evolution process of multidisciplinary parameters from the initial design to the final determination.

10. The collaborative management and integration method according to claim 1, wherein The multi-source spreadsheet version management mechanism described in step 4 includes the following modules: Version branch control module, creating independent parameter branches for different team design directions; Version comparison module: providing a comparison view to highlight the parameter differences between different versions; Version merging module: providing a parameter-level merging tool to integrate the preferred results.

Images