Method, device and equipment for constructing intelligent integrated platform, and storage medium

Abstract

The application relates to the technical field of computers and discloses a construction method and device of an intelligent integrated platform, equipment and a storage medium, the method comprising the following steps: constructing an ultra-speed modeling layer, an automatic loading layer, a data simulation layer and a target integrated performance optimization layer according to attribute parameters of a target vehicle; compiling the ultra-speed modeling layer, the automatic loading layer, the data simulation layer and the target integrated performance optimization layer to obtain an application program executable script file; executing the application program executable script and a preset plug-in file according to preset configuration information through a target device to obtain a plurality of platform program blocks; and constructing a target intelligent integrated platform according to a target public interface, a target plug-in directory and the plurality of platform program blocks. The intelligent integrated platform constructed in the above manner can realize multidisciplinary collaborative balance development of vehicle performance, effectively improve production efficiency, shorten a research and development cycle and save design change cost.

Description

Technical Field

[0001] This invention relates to the field of computer control technology, and in particular to a method, apparatus, equipment, and storage medium for constructing an intelligent integrated platform. Background Technology

[0002] With the continuous development and vertical extension of vehicle technology, more and more manufacturers are constantly improving and optimizing quality and efficiency, especially for passenger car manufacturers. The advent of integrated platforms can realize optimization strategies, proxy models, data analysis visualization, integration of MDO optimization strategies, simulation model templates, parameterized template integration and other functions. However, the currently built integrated platforms can only realize a small part of the above functions, and the platform is not intelligent enough in the process of realizing functions, which requires human intervention in the analysis or production process, resulting in low production efficiency, extremely long R&D cycle and high cost. Furthermore, it cannot achieve multi-disciplinary collaborative balanced development of vehicle performance.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, device, and storage medium for constructing an intelligent integrated platform, aiming to solve the technical problems that existing integrated platforms cannot achieve multi-disciplinary collaborative and balanced development of vehicle performance, and result in low production efficiency, long R&D cycles, and high costs.

[0005] To achieve the above objectives, the present invention provides a method for constructing an intelligent integration platform, the method comprising the following steps:

[0006] Based on the target vehicle's attribute parameters, a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer are constructed.

[0007] The rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer are compiled to obtain an executable script file for the application.

[0008] The target device executes the application's executable script and preset plugin files according to preset configuration information to obtain several platform program blocks;

[0009] The target intelligent integration platform is constructed based on the target public interface, the target plugin directory, and the aforementioned platform program blocks.

[0010] Optionally, the step of constructing a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle includes:

[0011] Perform characteristic analysis on the attribute parameters of the target vehicle to obtain the corresponding parameter feature information;

[0012] The attribute parameters of the target vehicle are classified according to the parameter feature information to obtain different data categories;

[0013] Create corresponding data directories based on the different data categories;

[0014] The attribute parameters of the target vehicle are stored in the corresponding data directory according to the data category. The data directory includes a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory.

[0015] By using a preset layered template, the modeling parameter directory and the loading parameter directory are constructed in layers to obtain a rapid modeling layer and an automated loading layer.

[0016] The simulation parameter directory and the performance optimization parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer and the target integrated performance optimization layer.

[0017] Optionally, the step of constructing the modeling parameter directory and the loading parameter directory in layers using a preset layered template to obtain a rapid modeling layer and an automated loading layer includes:

[0018] A data integration file is generated based on the PDM integrated data, classification extraction process, and verification data in the modeling parameter catalog;

[0019] Automated modeling files are generated based on the geometry cleanup process, mid-surface extraction process, network batch processing process, standardized naming process, CFD facet wrapping process, batch drilling process, and simplified bridge creation process in the modeling parameter catalog.

[0020] Automated assembly files are generated based on the assembly process and panel connection process of the modeling parameters.

[0021] The data integration file, the automated modeling file, and the automated assembly file are loaded through target model transformation;

[0022] By using a preset layered template to construct the file loading results into layers, a rapid modeling layer is obtained.

[0023] A durability performance file is generated based on the sheet metal fatigue parameters, weld fatigue parameters, and weld point fatigue parameters in the loading parameter directory.

[0024] A target performance file is generated based on the strength performance parameters, stiffness performance parameters, collision performance parameters, and NVH performance parameters in the loading parameter directory;

[0025] The durability performance file, the target performance file, and the multibody dynamics strategy are constructed in layers using the preset layered template to obtain an automated loading layer.

[0026] Optionally, the step of constructing a data simulation layer and a target integrated performance optimization layer by constructing the simulation parameter directory and the performance optimization parameter directory in layers using the preset layered template, respectively, includes:

[0027] Obtain the index data of the durability performance file and the target performance file;

[0028] Simulation files are generated based on the data structured storage process, data attributed retrieval process, data version iteration process, and simulation process of the indicator data and the simulation parameter directory.

[0029] Set the simulation output directory and simulation interface header file directory according to the simulation file;

[0030] The simulation output directory, simulation interface header file directory, and simulation parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer.

[0031] Based on the structural stiffness MDO process, NVH MDO process, and collision MDO process in the performance optimization parameter catalog, generate MDO process files;

[0032] Based on the simulation performance optimization parameters, MDO calculation submission strategy, MDO automated processing strategy, and target joint optimization strategy in the performance optimization parameter catalog, a target optimization file is generated.

[0033] Set the performance output directory and performance interface header file directory according to the MDO process file and the target optimization file;

[0034] The target integrated performance optimization layer is obtained by constructing the performance output directory, the performance interface header file directory, and the performance optimization parameter directory in layers using the preset layered template.

[0035] Optionally, the step of constructing the target intelligent integration platform based on the target public interface, the target plugin directory, and the several platform program blocks includes:

[0036] Set the corresponding plugin classes and plugin functions according to the target plugin directory, and set the corresponding public interface classes according to the target public structure;

[0037] Set the plugin class and the public interface class to have an inheritance relationship;

[0038] The platform program blocks are connected according to the inheritance relationship and the target public interface to obtain the target intelligent integration platform.

[0039] Optionally, after constructing the target intelligent integration platform based on the target public interface, the target plugin directory, and the several platform program blocks, the method further includes:

[0040] Obtain preset vehicle body weld point data, and extract the weld point names from the preset vehicle body weld point data;

[0041] The target intelligent integration platform identifies the name of the weld point to obtain the part number;

[0042] The number of solder joint layers and the location of the solder joints are determined based on the part number;

[0043] The target solder joint is generated based on the target intelligent integration platform, the number of solder joint layers, and the position of the solder joint.

[0044] Optionally, after constructing the target intelligent integration platform based on the target public interface, the target plugin directory, and the several platform program blocks, the method further includes:

[0045] Obtain the body data of the part to be named;

[0046] The corresponding assembly hierarchy is obtained based on the body data of the part to be named;

[0047] The assembly hierarchy is adjusted using the target intelligent integration platform to obtain the current hierarchy.

[0048] The position of the part body data to be named is moved according to the current hierarchical relationship;

[0049] Rename the original data of the part to be named after it has been moved.

[0050] Furthermore, to achieve the above objectives, the present invention also proposes a construction apparatus for an intelligent integration platform, the construction apparatus comprising:

[0051] The acquisition module is used to construct a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle.

[0052] The compilation module is used to compile the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer to obtain an executable script file for the application.

[0053] The execution module is used to execute the application executable script and preset plugin files on the target device according to preset configuration information to obtain several platform program blocks;

[0054] The building module is used to construct the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks.

[0055] Furthermore, to achieve the above objectives, the present invention also proposes an intelligent integration platform construction device, which includes: a memory, a processor, and an intelligent integration platform construction program stored in the memory and executable on the processor. The intelligent integration platform construction program is configured to implement the intelligent integration platform construction method described above.

[0056] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a construction program for an intelligent integration platform, wherein when the construction program for the intelligent integration platform is executed by a processor, the construction method for the intelligent integration platform as described above is implemented.

[0057] The intelligent integration platform construction method proposed in this invention constructs a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integration performance optimization layer based on the attribute parameters of the target vehicle; compiles the high-speed modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer to obtain an application executable script file; executes the application executable script and preset plugin files on the target device according to preset configuration information to obtain several platform program blocks; constructs the target intelligent integration platform based on the target common interface, the target plugin directory, and the several platform program blocks; the intelligent integration platform constructed in the above manner can realize multi-disciplinary collaborative balanced development of vehicle performance, and effectively improve production efficiency, shorten the R&D cycle, and save design change costs. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of the structure of the intelligent integration platform for the hardware operating environment involved in the embodiments of the present invention.

[0059] Figure 2 This is a flowchart illustrating the first embodiment of the construction method for the intelligent integration platform of the present invention;

[0060] Figure 3 This is a flowchart illustrating the second embodiment of the construction method for the intelligent integration platform of the present invention;

[0061] Figure 4 This is a schematic diagram of the functional modules of the first embodiment of the intelligent integration platform construction device of the present invention.

[0062] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0063] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0064] Reference Figure 1 , Figure 1 This is a schematic diagram of the construction device structure of the intelligent integration platform for the hardware operating environment involved in the embodiments of the present invention.

[0065] like Figure 1 As shown, the construction equipment for this intelligent integrated platform may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0066] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the construction equipment of the intelligent integration platform, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0067] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a program for building an intelligent integrated platform.

[0068] exist Figure 1In the intelligent integrated platform construction device shown, the network interface 1004 is mainly used for data communication with the network integrated platform workstation; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and memory 1005 in the intelligent integrated platform construction device of the present invention can be set in the intelligent integrated platform construction device, and the intelligent integrated platform construction device calls the intelligent integrated platform construction program stored in the memory 1005 through the processor 1001 and executes the intelligent integrated platform construction method provided in the embodiment of the present invention.

[0069] Based on the above hardware structure, an embodiment of the construction method of the intelligent integration platform of the present invention is proposed.

[0070] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the construction method for the intelligent integration platform of the present invention.

[0071] In the first embodiment, the method for constructing the intelligent integration platform includes the following steps:

[0072] Step S10: Construct a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle.

[0073] It should be noted that the execution subject of this embodiment is the intelligent integration platform construction device, but it can also be other devices that can achieve the same or similar functions, such as platform construction controllers, etc. This embodiment does not limit this, and in this embodiment, the platform construction controller is used as an example for explanation.

[0074] It should be understood that attribute parameters refer to the parameters of the target vehicle's own attributes. These attribute parameters include, but are not limited to, performance parameters, processing parameters, simulation parameters, etc. After obtaining the attribute parameters of the target vehicle, a rapid modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer are constructed based on the attribute parameters. The rapid modeling layer refers to the data layer used to quickly model based on the input vehicle data. The automated loading layer refers to the data layer that performs automated loading calculations and automated post-processing of the input data. The data simulation layer refers to the data layer that performs simulation management or simulation data management of the model, indicators, or reports. The rapid modeling layer, automated loading layer, data simulation layer, and target integrated performance optimization layer are all constructed layer by layer using a preset layer template.

[0075] Step S20: Compile the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer to obtain an executable script file for the application.

[0076] It is understandable that an application executable script file refers to a script file that can be executed within an application. After obtaining the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer, the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer are automatically compiled in sequence according to the script file editing rules. Then, the compiled script files are packaged to obtain the application executable script file, which exists in the form of a data package.

[0077] Step S30: The target device executes the application executable script and preset plugin file according to the preset configuration information to obtain several platform program blocks.

[0078] It should be understood that the "several platform program blocks" refer to the various program blocks used to build the target intelligent integrated platform. These platform program blocks include CAE secondary development programs, simulation management programs, and target PBS calculation programs. The "preset plug-in files" refer to the files that help the application executable scripts generate the corresponding program blocks. The format of the preset plug-in files can be DLLs. The "preset configuration information" refers to the configuration information configured on the target device. That is, through the settings of the preset configuration information, the target device can execute the application executable scripts and preset plug-in files normally and successfully. The target device can be a compiler or a virtual machine.

[0079] Step S40: Construct the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks.

[0080] Understandably, the target plugin directory refers to the directory that stores the plugin files loaded and generated during application runtime. This target plugin directory includes the output directory of the specified plugin and the directory of public interface header files. After obtaining several platform program blocks, these platform program blocks are aggregated and connected according to the target plugin directory through the target public interface to construct the target intelligent integration platform. Optionally, this target intelligent integration platform also includes other integration software, a functional layer, a client, and a server. Other integration software connects to the client via TCP protocol, the server connects to the client via TCP protocol, and the client accesses MySQL through a web data access structure. Access to the SDM database is supported, and the functional layers include, but are not limited to, model building, automated constraint loading, automated report generation, and data storage and archiving. Model building includes streamlined modeling workflow design, CAD data import, mesh generation and optimization, connection creation and debugging, BlueBook attribute generation, TrimMass application, model quality checking, model library and model conversion, etc. Automated constraint loading includes MDOelParams preparation, analysis constraint loading design, analysis workflow construction, automatic generation of analysis header files, and automatic queuing calculations, etc. Automated reporting includes report template design, report table creation, automated report workflow design, and automatic report generation. Data storage and archiving includes data archiving design, automatic data upload and archiving, input data, process data, analysis-required parameters and indicators, file management, data comparison and analysis, and compatibility with the SDM system.

[0081] Further, step S40 includes: setting corresponding plugin classes and plugin functions according to the target plugin directory, and setting corresponding public interface classes according to the target public structure; setting the plugin classes and the public interface classes to have an inheritance relationship; and connecting the plurality of platform program blocks according to the inheritance relationship and the target public interface to obtain the target intelligent integration platform.

[0082] It should be understood that a plugin class refers to a class used to input plugin code, and a plugin function refers to a function used to generate plugin files. After obtaining the target plugin directory, the corresponding plugin class and plugin function are set according to the target plugin directory. Then, the plugin class and the public interface class are set to an inheritance relationship, that is, the plugin class inherits all the attributes of the public interface class. After the setting is completed, several platform program blocks are connected through the target public interface according to the inheritance relationship to obtain the target intelligent integration platform.

[0083] Furthermore, after step S40, the method further includes: acquiring preset body weld point data, extracting weld point names from the preset body weld point data; identifying the weld point names through the target intelligent integration platform to obtain a part number; determining the weld point layer number and weld point position based on the part number; and generating a target weld point based on the target intelligent integration platform, the weld point layer number, and the weld point position.

[0084] It should be understood that the preset body weld point data refers to the data of each weld point inside the assembly, including the number of weld points, their positions, and the connection relationships between them. The weld point name refers to the name of the weld point in the body weld point data. Since body weld points have a naming standard in the Catia model, starting with "WP+" followed by the part number of the connected object, for example, WP-M6-2801035+M6-2801171, after obtaining the weld point name, the target intelligent integration platform identifies the weld point name to obtain the part number, and then uses regular expressions to identify the part connected object corresponding to the part number to determine the weld point layer and weld point position. Finally, in HyperMesh, target weld points are generated in batches based on the weld point layer and weld point position.

[0085] Further, step S40 includes: acquiring the body data of the part to be named; obtaining the corresponding assembly hierarchy relationship based on the body data of the part to be named; adjusting the assembly hierarchy relationship through the target intelligent integration platform to obtain the current hierarchy relationship; moving the position of the body data of the part to be named according to the current hierarchy relationship; and renaming the moved body data of the part to be named.

[0086] Understandably, the part body data to be named refers to the attribute data of the part itself that needs to be renamed. This part body data is obtained by analyzing the imported assembly set file through the Catia model. The comp name of the part body to be named is usually "PartBody" with a numerical suffix. The assembly hierarchy refers to the hierarchical relationship of the part number corresponding to the part body data in the part body. This assembly hierarchy can be a two-level upper-level assembly relationship, and sheet metal parts, weld points, weld seams, and fasteners all belong to the same parent assembly. After obtaining the assembly hierarchy, the assembly hierarchy is first adjusted, then the part body data to be named is moved to the correct assembly position, then the comp name is modified according to different part contents, and redundant information is removed. Finally, the compID is modified to be consistent with the part number. The comp name is modified according to the parent assembly name (for parts to be meshed), and the comp name is modified according to the parent assembly name (for fasteners) to achieve the renaming of the part body data to be named.

[0087] This embodiment constructs a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle. The high-speed modeling layer, the automated loading layer, the data simulation layer, and the target integrated performance optimization layer are compiled to obtain an executable script file for the application. The target device executes the executable script and preset plugin files according to preset configuration information to obtain several platform program blocks. A target intelligent integration platform is constructed based on the target common interface, the target plugin directory, and the several platform program blocks. The intelligent integration platform constructed in the above manner can achieve multi-disciplinary collaborative balanced development of vehicle performance, and effectively improve production efficiency, shorten the R&D cycle, and save design change costs.

[0088] In one embodiment, such as Figure 3 The second embodiment of the construction method for the intelligent integration platform of the present invention, based on the first embodiment, includes step S10, which includes:

[0089] Step S101: Perform characteristic analysis on the attribute parameters of the target vehicle to obtain the corresponding parameter feature information.

[0090] It should be understood that parameter feature information refers to information that can uniquely identify different attribute parameters. This parameter feature information can be the name or number of the attribute parameter. Specifically, the corresponding parameter feature information is obtained by analyzing the attribute parameters of the target vehicle.

[0091] Step S102: Classify the attribute parameters of the target vehicle according to the parameter feature information to obtain different data categories.

[0092] It is understandable that data category refers to the category of attribute parameters of different target vehicles. After obtaining the parameter feature information, the attribute parameters are classified according to the parameter feature information to obtain the corresponding data category. For example, the attribute parameters of the target vehicle include a1, b1, a2, b2, and c1. Therefore, the different data categories after classification are: category a: a1 and a2, category b: b1 and b2, and category c.

[0093] Step S103: Create corresponding data directories according to the different data categories.

[0094] It should be understood that a data directory refers to a directory that stores various attribute parameters. There can be multiple data directories. After obtaining different data categories, corresponding data directories are created according to the different data categories.

[0095] Step S104: Store the attribute parameters of the target vehicle into the corresponding data directory according to the data category. The data directory includes a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory.

[0096] Understandably, after obtaining different data categories, the attribute parameters of the target vehicle are stored in the corresponding data directory according to the data category. This data directory includes a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory. Specifically, the attribute parameters belonging to modeling are stored in the modeling parameter directory, the attribute parameters belonging to loading are stored in the loading parameter directory, the attribute parameters belonging to simulation are stored in the simulation parameter directory, and the attribute parameters belonging to performance optimization are stored in the performance optimization parameter directory.

[0097] Step S105: The modeling parameter directory and the loading parameter directory are constructed in layers using a preset layered template to obtain the rapid modeling layer and the automated loading layer.

[0098] It should be understood that the preset layered template refers to a template that builds the parameter directory into corresponding data layers. First, the modeling parameter directory is built into layers using the preset layered template to obtain the rapid modeling layer. Then, the loading parameter directory is built into layers using the preset layered template to obtain the automated loading layer.

[0099] Further, step S105 includes: generating a data integration file based on the PDM integrated data, classification extraction process, and verification data in the modeling parameter catalog; generating an automated modeling file based on the geometry cleanup process, mid-surface extraction process, network batch processing process, standardized naming process, CFD cladding process, batch drilling process, and simplified bridge establishment process in the modeling parameter catalog; generating an automated assembly file based on the assembly process and plate connection process of the modeling parameters; loading the data integration file, the automated modeling file, and the automated assembly file through target model conversion; constructing the file loading results in layers using a preset layer template to obtain a rapid modeling layer; generating a durability performance file based on the sheet metal fatigue parameters, weld fatigue parameters, and weld point fatigue parameters in the loading parameter catalog; generating a target performance file based on the strength performance parameters, stiffness performance parameters, collision performance parameters, and NVH performance parameters in the loading parameter catalog; and constructing the durability performance file, the target performance file, and the multibody dynamics strategy in layers using the preset layer template to obtain an automated loading layer.

[0100] Understandably, the data integration file is generated from PDM integrated data, classification and extraction processes, and verification data. The automated modeling file is generated from geometry cleanup processes, mid-surface extraction processes, mesh batch processing processes, standardized naming processes, CFD faceting, batch drilling processes, and simplified bridge creation processes. This geometry processing process can import Catia geometry models into HyperMesh, automatically standardize the assembly levels and naming of sheet metal and injection molded parts, automatically standardize the assembly levels and naming of weld points, weld seams, and fasteners, delete duplicate geometry, automatically extract mid-surfaces, assign attributes, specify thickness information, check the geometry model, and export STP geometry files. The mesh processing process can automatically import STP geometry models into HyperMesh. The process involves converting p-geometry files to ANSA, automatically cleaning the geometry, optimizing the 2D mesh, normalizing the assembly hierarchy, naming parts, and automatically exporting NAS mesh files. The connection process then automatically imports STP and NAS mesh files, automatically creates weld points and weld point elements based on weld point geometry and component names, and automatically creates bolts (RBE2 elements) based on fastener geometry and component names. Finally, through target model conversion, the loading structure of the data integration file, automated modeling file, and automated assembly file is layered to create a rapid modeling layer. An automated loading layer is then constructed using preset layering templates based on durability performance files, standard performance files, and multibody dynamics strategies.

[0101] Step S106: The simulation parameter directory and the performance optimization parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer and the target integrated performance optimization layer.

[0102] It should be understood that after obtaining the simulation parameter directory and the performance optimization parameter directory, firstly, the simulation parameter directory is constructed in layers using a preset layered template to obtain the data simulation layer. Then, the performance optimization parameter directory is created in layers using a preset layered template to obtain the target integration performance optimization layer.

[0103] Further, step S106 includes: acquiring the index data of the durability performance file and the target performance file; generating a simulation file based on the data structured storage process, data attribute retrieval process, data version iteration process, and simulation process of the index data and the simulation parameter directory; setting the simulation output directory and simulation interface header file directory based on the simulation file; constructing the simulation output directory, simulation interface header file directory, and simulation parameter directory in layers using the preset layered template to obtain a data simulation layer; generating an MDO process file based on the structural stiffness MDO process, NVH MDO process, and collision MDO process of the performance optimization parameter directory; generating a target optimization file based on the simulation performance optimization parameters, MDO calculation submission strategy, MDO automated processing strategy, and target joint optimization strategy of the performance optimization parameter directory; setting the performance output directory and performance interface header file directory based on the MDO process file and the target optimization file; and constructing the performance output directory, performance interface header file directory, and performance optimization parameter directory in layers using the preset layered template to obtain a target integrated performance optimization layer.

[0104] It is understood that the indicator data refers to the unique indicator data of the durability performance file and the target performance file. This indicator data includes, but is not limited to, model indicator data and report indicator data. Then, based on the indicator data, a basic data management process is obtained. Simulation files are generated based on the basic data management process, data structured storage process, data attribute retrieval process, data version iteration process, and simulation process. Optionally, the data process includes, but is not limited to, a simulation task completion statistics process, a simulation task progress visualization process, and a simulation task creation and allocation process. The data attribute retrieval process includes, but is not limited to, a model retrieval process, a report retrieval process, and an indicator retrieval process. A data simulation layer is constructed layer by layer according to the simulation output directory, simulation interface header file directory, and simulation parameter directory using a preset layered template. The MDO process file refers to the workflow of MDO. The MDO calculation submission strategy refers to the strategy for automatically submitting calculations to the MDO calculation model. The MDO automated processing strategy refers to the strategy for automated processing after the MDO calculation structure. The target joint optimization strategy refers to the multi-disciplinary and multi-objective joint optimization strategy. Then, a target integrated performance optimization layer is constructed layer by layer according to the performance output directory, performance interface header file directory, and performance optimization parameter directory using a preset layered template.

[0105] This embodiment analyzes the attribute parameters of the target vehicle to obtain corresponding parameter feature information; classifies the attribute parameters of the target vehicle according to the parameter feature information to obtain different data categories; creates corresponding data directories according to the different data categories; and stores the attribute parameters of the target vehicle according to the data categories into the corresponding data directories, which include a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory. The modeling parameter directory and the loading parameter directory are constructed layer by layer using a preset layering template to obtain a rapid modeling layer and an automated loading layer; the simulation parameter directory and the performance optimization parameter directory are also constructed layer by layer using the preset layering template to obtain a data simulation layer and a target integration performance optimization layer. Through the above method, the corresponding parameter feature information is analyzed based on the attribute parameters of the target vehicle, then corresponding data directories are created according to different data categories, and finally, the data in the data directories are constructed layer by layer using a preset layering template to obtain a data simulation layer, a target integration performance optimization layer, and so on, thereby effectively improving the accuracy of the layered construction of each data layer.

[0106] Furthermore, this embodiment of the invention also proposes a storage medium storing a construction program for an intelligent integration platform. When the construction program for the intelligent integration platform is executed by a processor, it implements the steps of the construction method for the intelligent integration platform as described above.

[0107] Since this storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0108] In addition, refer to Figure 4 This invention also proposes a construction apparatus for an intelligent integration platform, the construction apparatus comprising:

[0109] The acquisition module 10 is used to construct a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle.

[0110] The compilation module 20 is used to compile the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer to obtain an executable script file for the application.

[0111] The execution module 30 is used to execute the application executable script and preset plugin files through the target device according to preset configuration information to obtain several platform program blocks.

[0112] Module 40 is used to construct the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks.

[0113] This embodiment constructs a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle. The high-speed modeling layer, the automated loading layer, the data simulation layer, and the target integrated performance optimization layer are compiled to obtain an executable script file for the application. The target device executes the executable script and preset plugin files according to preset configuration information to obtain several platform program blocks. A target intelligent integration platform is constructed based on the target common interface, the target plugin directory, and the several platform program blocks. The intelligent integration platform constructed in the above manner can achieve multi-disciplinary collaborative balanced development of vehicle performance, and effectively improve production efficiency, shorten the R&D cycle, and save design change costs.

[0114] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0115] In addition, for technical details not described in detail in this embodiment, please refer to the construction method of the intelligent integration platform provided in any embodiment of the present invention, which will not be repeated here.

[0116] In one embodiment, the acquisition module 10 is further configured to perform characteristic analysis on the attribute parameters of the target vehicle to obtain corresponding parameter feature information; classify the attribute parameters of the target vehicle according to the parameter feature information to obtain different data categories; create corresponding data directories according to the different data categories; store the attribute parameters of the target vehicle according to the data categories in the corresponding data directories, the data directories including modeling parameter directories, loading parameter directories, simulation parameter directories, and performance optimization parameter directories; construct the modeling parameter directory and the loading parameter directory in layers using a preset layered template to obtain a rapid modeling layer and an automated loading layer; construct the simulation parameter directory and the performance optimization parameter directory in layers using the preset layered template to obtain a data simulation layer and a target integrated performance optimization layer.

[0117] In one embodiment, the acquisition module 10 is further configured to: generate a data integration file based on the PDM integrated data, classification extraction process, and verification data in the modeling parameter catalog; generate an automated modeling file based on the geometry cleanup process, mid-surface extraction process, network batch processing process, standardized naming process, CFD cladding process, batch drilling process, and simplified bridge establishment process in the modeling parameter catalog; generate an automated assembly file based on the assembly process and plate connection process of the modeling parameters; load the data integration file, the automated modeling file, and the automated assembly file through target model conversion; construct the file loading results in layers using a preset layered template to obtain a rapid modeling layer; generate a durability performance file based on the sheet metal fatigue parameters, weld fatigue parameters, and weld point fatigue parameters in the loading parameter catalog; generate a target performance file based on the strength performance parameters, stiffness performance parameters, collision performance parameters, and NVH performance parameters in the loading parameter catalog; and construct the durability performance file, the target performance file, and the multibody dynamics strategy in layers using the preset layered template to obtain an automated loading layer.

[0118] In one embodiment, the acquisition module 10 is further configured to acquire the indicator data of the durability performance file and the target performance file; generate a simulation file based on the indicator data and the data structured storage process, data attribute retrieval process, data version iteration process, and simulation process of the simulation parameter directory; set a simulation output directory and a simulation interface header file directory based on the simulation file; construct the simulation output directory, simulation interface header file directory, and simulation parameter directory in layers using the preset layered template to obtain a data simulation layer; generate an MDO process file based on the structural stiffness MDO process, NVH MDO process, and collision MDO process of the performance optimization parameter directory; generate a target optimization file based on the simulation performance optimization parameters, MDO calculation submission strategy, MDO automated processing strategy, and target joint optimization strategy of the performance optimization parameter directory; set a performance output directory and a performance interface header file directory based on the MDO process file and the target optimization file; and construct the performance output directory, performance interface header file directory, and performance optimization parameter directory in layers using the preset layered template to obtain a target integrated performance optimization layer.

[0119] In one embodiment, the construction module 40 is further configured to set corresponding plugin classes and plugin functions according to the target plugin directory, and set corresponding public interface classes according to the target public structure; set the plugin classes and the public interface classes to have an inheritance relationship; and connect the plurality of platform program blocks according to the inheritance relationship and the target public interface to obtain the target intelligent integration platform.

[0120] In one embodiment, the construction module 40 is further configured to acquire preset body weld point data, extract the weld point names from the preset body weld point data; identify the weld point names through the target intelligent integration platform to obtain a part number; determine the weld point layer number and weld point position based on the part number; and generate a target weld point based on the target intelligent integration platform, the weld point layer number, and the weld point position.

[0121] In one embodiment, the construction module 40 is further configured to acquire the body data of the part to be named; obtain the corresponding assembly hierarchy relationship based on the body data of the part to be named; adjust the assembly hierarchy relationship through the target intelligent integration platform to obtain the current hierarchy relationship; move the position of the body data of the part to be named according to the current hierarchy relationship; and rename the moved body data of the part to be named.

[0122] Other embodiments or implementation methods of the intelligent integration platform construction device described in this invention can be found in the above-described method embodiments, and will not be repeated here.

[0123] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0124] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0125] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, all-in-one platform workstation, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0126] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for constructing an intelligent integration platform, characterized in that, The method for constructing the intelligent integration platform includes the following steps: Based on the target vehicle's attribute parameters, a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer are constructed. The rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer are compiled to obtain an executable script file for the application. The target device executes the application's executable script and preset plugin files according to preset configuration information to obtain several platform program blocks; The target intelligent integration platform is constructed based on the target public interface, the target plugin directory, and the aforementioned platform program blocks; The construction of a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the target vehicle's attribute parameters includes: Perform characteristic analysis on the attribute parameters of the target vehicle to obtain the corresponding parameter feature information; The attribute parameters of the target vehicle are classified according to the parameter feature information to obtain different data categories; Create corresponding data directories based on the different data categories; The attribute parameters of the target vehicle are stored in the corresponding data directory according to the data category. The data directory includes a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory. By using a preset layered template, the modeling parameter directory and the loading parameter directory are constructed in layers to obtain a rapid modeling layer and an automated loading layer. The simulation parameter directory and the performance optimization parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer and the target integrated performance optimization layer.

2. The method for constructing the intelligent integration platform as described in claim 1, characterized in that, The process involves constructing the modeling parameter directory and the loading parameter directory into layers using a preset layered template, resulting in a rapid modeling layer and an automated loading layer. A data integration file is generated based on the PDM integrated data, classification extraction process, and verification data in the modeling parameter catalog; Automated modeling files are generated based on the geometry cleanup process, mid-surface extraction process, network batch processing process, standardized naming process, CFD facet wrapping process, batch drilling process, and simplified bridge creation process in the modeling parameter catalog. Automated assembly files are generated based on the assembly process and panel connection process of the modeling parameters. The data integration file, the automated modeling file, and the automated assembly file are loaded through target model transformation; By using a preset layered template to construct the file loading results into layers, a rapid modeling layer is obtained. A durability performance file is generated based on the sheet metal fatigue parameters, weld fatigue parameters, and weld point fatigue parameters in the loading parameter directory. A target performance file is generated based on the strength performance parameters, stiffness performance parameters, collision performance parameters, and NVH performance parameters in the loading parameter directory; The durability performance file, the target performance file, and the multibody dynamics strategy are constructed in layers using the preset layered template to obtain an automated loading layer.

3. The method for constructing the intelligent integration platform as described in claim 2, characterized in that, The process involves constructing a data simulation layer and a target integrated performance optimization layer by using the preset layered template to create layers for the simulation parameter directory and the performance optimization parameter directory, respectively. Obtain the index data of the durability performance file and the target performance file; Simulation files are generated based on the data structured storage process, data attributed retrieval process, data version iteration process, and simulation process of the indicator data and the simulation parameter directory. Set the simulation output directory and simulation interface header file directory according to the simulation file; The simulation output directory, simulation interface header file directory, and simulation parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer. Based on the structural stiffness MDO process, NVH MDO process, and collision MDO process in the performance optimization parameter catalog, generate MDO process files; Based on the simulation performance optimization parameters, MDO calculation submission strategy, MDO automated processing strategy, and target joint optimization strategy in the performance optimization parameter catalog, a target optimization file is generated. Set the performance output directory and performance interface header file directory according to the MDO process file and the target optimization file; The target integrated performance optimization layer is obtained by constructing the performance output directory, the performance interface header file directory, and the performance optimization parameter directory in layers using the preset layered template.

4. The method for constructing the intelligent integration platform as described in claim 3, characterized in that, The construction of the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks includes: Set the corresponding plugin classes and plugin functions according to the target plugin directory, and set the corresponding public interface classes according to the target public structure; Set the plugin class and the public interface class to have an inheritance relationship; The platform program blocks are connected according to the inheritance relationship and the target public interface to obtain the target intelligent integration platform.

5. The method for constructing an intelligent integration platform as described in any one of claims 1 to 4, characterized in that, After constructing the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks, the method further includes: Obtain preset vehicle body weld point data, and extract the weld point names from the preset vehicle body weld point data; The target intelligent integration platform identifies the name of the weld point to obtain the part number; The number of solder joint layers and the location of the solder joints are determined based on the part number; The target solder joint is generated based on the target intelligent integration platform, the number of solder joint layers, and the position of the solder joint.

6. The method for constructing an intelligent integration platform as described in any one of claims 1 to 4, characterized in that, After constructing the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks, the method further includes: Obtain the body data of the part to be named; The corresponding assembly hierarchy is obtained based on the body data of the part to be named; The assembly hierarchy is adjusted using the target intelligent integration platform to obtain the current hierarchy. The position of the part body data to be named is moved according to the current hierarchical relationship; Rename the original data of the part to be named after it has been moved.

7. A device for constructing an intelligent integrated platform, characterized in that, The apparatus for constructing the intelligent integration platform includes: The acquisition module is used to construct a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the attribute parameters of the target vehicle. The compilation module is used to compile the rapid modeling layer, the automated loading layer, the data simulation layer, and the target integration performance optimization layer to obtain an executable script file for the application. The execution module is used to execute the application executable script and preset plugin files on the target device according to preset configuration information to obtain several platform program blocks; The building module is used to construct the target intelligent integration platform based on the target public interface, the target plugin directory, and the aforementioned platform program blocks; The construction of a high-speed modeling layer, an automated loading layer, a data simulation layer, and a target integrated performance optimization layer based on the target vehicle's attribute parameters includes: Perform characteristic analysis on the attribute parameters of the target vehicle to obtain the corresponding parameter feature information; The attribute parameters of the target vehicle are classified according to the parameter feature information to obtain different data categories; Create corresponding data directories based on the different data categories; The attribute parameters of the target vehicle are stored in the corresponding data directory according to the data category. The data directory includes a modeling parameter directory, a loading parameter directory, a simulation parameter directory, and a performance optimization parameter directory. By using a preset layered template, the modeling parameter directory and the loading parameter directory are constructed in layers to obtain a rapid modeling layer and an automated loading layer. The simulation parameter directory and the performance optimization parameter directory are constructed in layers using the preset layered template to obtain the data simulation layer and the target integrated performance optimization layer.

8. A device for constructing an intelligent integrated platform, characterized in that, The intelligent integration platform construction device includes: a memory, a processor, and an intelligent integration platform construction program stored in the memory and executable on the processor. The intelligent integration platform construction program is configured to implement the intelligent integration platform construction method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a construction program for an intelligent integration platform, which, when executed by a processor, implements the construction method for the intelligent integration platform as described in any one of claims 1 to 6.

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