Body-in-white strength simulation result post-processing method and device, electronic equipment and medium

Abstract

The application relates to the technical field of vehicles, in particular to a body-in-white strength simulation result post-processing method and device, electronic equipment and a medium, which comprises the following steps: constructing a finite element model of a body-in-white based on geometric data of the body-in-white, making a load file based on a load decomposition table of a plurality of preset working conditions which are constructed in advance, inputting the load file into the finite element model, and obtaining a strength simulation result of the body-in-white; generating a post-processing analysis reference table based on the properties of components in the finite element model, inputting the strength simulation result and the post-processing analysis reference table into a preset post-processing software, traversing each component of the body-in-white under each preset working condition in the strength simulation result, and obtaining a post-processing result of the body-in-white. Therefore, the technical problems of low efficiency, errors and long iteration period in manual data extraction, manual qualification determination and result recording during the post-processing of the body-in-white strength simulation are solved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a method, device, electronic device and medium for post-processing of body-in-white strength simulation results. Background Technology

[0002] In the process of vehicle development, the body-in-white, as the core load-bearing skeleton of the automobile, is a key structure that supports all vehicle components, transmits loads, and ensures the safety of passengers. Its structural strength directly determines the safety, reliability, handling stability, and ride comfort of the vehicle under various driving scenarios. The body-in-white strength test conditions are the most common steady-state or quasi-static load scenarios that automobiles face in daily use. These mainly include vertical impact conditions, braking conditions, and cornering conditions. Although these conditions do not reach extreme load strengths such as collisions, the loads are applied frequently and the conditions are diverse. Moreover, there is a coupling effect between different load types under different conditions. Under long-term action, stress concentration, plastic deformation, and even fatigue failure can easily occur in local structures of the body-in-white, seriously affecting the service life of the entire vehicle and driving safety.

[0003] In related technologies, post-processing mainly relies on manual operation. Engineers need to manually extract the stress values ​​of each part under different working conditions in software such as HyperView, compare them with the material yield strength, and record the parts that exceed the tolerance.

[0004] However, the above methods suffer from problems such as inefficiency, error-proneness, and lack of standardization, which urgently need to be addressed. Summary of the Invention

[0005] This application provides a method, device, electronic device, and medium for post-processing the simulation results of body-in-white strength, in order to solve the technical problems of low efficiency, error-proneness, and long iteration cycle in the post-processing of body-in-white strength simulation results due to the large number of parts and various working conditions.

[0006] The first aspect of this application provides a post-processing method for simulation results of body-in-white strength, including the following steps: Obtain the geometric data of the body-in-white, and construct the finite element model of the body-in-white after the geometric data passes the inspection; A load file is created based on a pre-constructed load decomposition table of multiple preset working conditions, and the load file is input into the finite element model to obtain the strength simulation results of the body-in-white. A post-processing analysis reference table is generated based on the component properties in the finite element model. The strength simulation results and the post-processing analysis reference table are input into a preset post-processing software. The preset post-processing software is then used to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

[0007] Furthermore, in some embodiments, the step of using the preset post-processing software to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white includes: Based on multiple preset working conditions of the body-in-white and each component under each preset working condition, the maximum equivalent stress of each component under the current preset working condition is extracted; The maximum equivalent stress is compared with the strength target value corresponding to each part in the post-processing analysis reference table, and the target part to be optimized is determined.

[0008] Furthermore, in some embodiments, determining the target part to be optimized includes: Determine whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value; If the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, then the target component whose maximum equivalent stress is greater than the corresponding strength target value is determined to be unqualified. The unqualified target component is then used as the target component to be optimized, and the unqualified information of the target component to be optimized is recorded. Optimize the target part to be optimized, and continue to traverse the optimized target parts until all target parts are qualified.

[0009] Furthermore, in some embodiments, the step of inputting the load file into the finite element model to obtain the strength simulation results of the body-in-white includes: Based on the analysis type and parameter settings of the finite element model, calculate the load file; Based on the calculation results of the load file, the stress distribution and displacement deformation results of the body-in-white under each preset working condition are obtained, and the model file and calculation result file of the body-in-white are generated.

[0010] Furthermore, in some embodiments, before constructing the finite element model of the body-in-white, the following steps are also included: The geometric data of the body-in-white are checked using preprocessing software, and when the check results meet the preset check conditions, the target surface of the body-in-white is selected for mesh generation. Based on the mesh generation results and the material property information of the body-in-white, the component name of each component is modified according to the component list table to obtain the material property information of each component, and the connection relationship between the body-in-white and each component is constructed based on the material property information of each component.

[0011] According to the post-processing method for body-in-white strength simulation results in this application embodiment, a finite element model of the body-in-white is constructed based on the geometric data of the body-in-white. A load file is created based on a pre-constructed load decomposition table of multiple preset working conditions and input into the finite element model to obtain the strength simulation results of the body-in-white. A post-processing analysis reference table is generated based on the component attributes in the finite element model. The strength simulation results and the post-processing analysis reference table are input into a preset post-processing software. The software iterates through each component under each preset working condition of the body-in-white in the strength simulation results to obtain the post-processing results of the body-in-white. This solves the technical problems of low efficiency, error-proneness, and long iteration cycles in the post-processing of body-in-white strength simulation due to the large number of components and working conditions, which often result in manual data extraction, manual qualification judgment, and result recording. By pre-generating a post-processing analysis reference table containing the strength target values ​​of each component based on the component attributes in the finite element model, and then using CAE post-processing software to automatically traverse all working conditions and all components, the maximum equivalent stress of each component is extracted and compared with the strength target values ​​in the reference table. Finally, unqualified components are automatically identified and recorded, thus achieving fully automated post-processing of the body-in-white strength simulation results.

[0012] A second aspect of this application provides a post-processing device for body-in-white strength simulation results, comprising: The acquisition module is used to acquire the geometric data of the body-in-white and construct the finite element model of the body-in-white after the geometric data has passed the inspection. The transmission module is used to generate a load file based on a pre-built load decomposition table of multiple preset working conditions, and input the load file into the finite element model to obtain the strength simulation results of the body-in-white. The traversal module is used to generate a post-processing analysis reference table based on the component properties in the finite element model, input the strength simulation results and the post-processing analysis reference table into the preset post-processing software, and use the preset post-processing software to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

[0013] Furthermore, in some embodiments, the traversal module includes: The extraction unit is used to extract the maximum equivalent stress of each component under the current preset working condition based on multiple preset working conditions of the body-in-white and each component under each preset working condition; The comparison unit is used to compare the maximum equivalent stress with the strength target value corresponding to each part in the post-processing analysis reference table, and to determine the target part to be optimized.

[0014] Furthermore, in some embodiments, the comparison unit includes: The judgment subunit is used to determine whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value. The recording subunit is used to determine that if the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, the target component with the maximum equivalent stress greater than the corresponding strength target value is unqualified, and the unqualified target component is used as the target component to be optimized, and the unqualified information of the target component to be optimized is recorded. An optimization subunit is used to optimize the target part to be optimized and continue to traverse the optimized target parts until all target parts are qualified.

[0015] Furthermore, in some embodiments, the transmission module includes: A calculation unit is used to calculate the load file based on the analysis type and parameter settings of the finite element model; The generation unit is used to obtain the stress distribution and displacement deformation results of the body-in-white under each preset working condition based on the calculation results of the load file, and generate the model file and calculation result file of the body-in-white.

[0016] Furthermore, in some embodiments, before constructing the finite element model of the body-in-white, the acquisition module further includes: The partitioning unit is used to check the geometric data of the body-in-white using preprocessing software, and when the check results meet the preset check conditions, select the target surface of the body-in-white for mesh partitioning. The construction unit is used to modify the component name of each component according to the component list table based on the mesh division result and the material property information of the body-in-white, obtain the material property information of each component, construct the connection relationship between the body-in-white and each component based on the material property information of each component, and construct the connection relationship based on the connection relationship.

[0017] According to the post-processing device for body-in-white strength simulation results according to the embodiments of this application, a finite element model of the body-in-white is constructed based on the geometric data of the body-in-white, and a load file is created based on a pre-constructed load decomposition table of multiple preset working conditions, and input into the finite element model to obtain the strength simulation results of the body-in-white; a post-processing analysis reference table is generated based on the component properties in the finite element model, and the strength simulation results and the post-processing analysis reference table are input into a preset post-processing software, and each component of the body-in-white under each preset working condition in the strength simulation results is traversed to obtain the post-processing results of the body-in-white. This solves the technical problems of low efficiency, error-proneness, and long iteration cycles in the post-processing of body-in-white strength simulation, which is caused by the large number of parts and multiple working conditions. By generating a post-processing analysis reference table containing the strength target values ​​of each part in advance based on the part attributes in the finite element model, and then using CAE (Computer-Aided Engineering) post-processing software to automatically traverse all working conditions and all parts, extract the maximum equivalent stress of each part and compare it with the strength target value in the reference table, and finally automatically identify and record unqualified parts, thus realizing fully automated post-processing of body-in-white strength simulation results.

[0018] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the post-processing method for body-in-white strength simulation results as described in the above embodiments.

[0019] A fourth aspect of this application provides a computer-readable storage medium storing computer instructions for causing the computer to execute the post-processing method for body-in-white strength simulation results as described in the above embodiments.

[0020] A fifth aspect of this application provides a computer program product, including a computer program that is executed to implement the post-processing method for body-in-white strength simulation results described in the above embodiments.

[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for post-processing simulation results of body-in-white strength according to an embodiment of this application; Figure 2 This is a flowchart illustrating the overall solution according to one embodiment of this application; Figure 3 This is a schematic diagram of a finite element model of a body-in-white according to an embodiment of this application; Figure 4 A flowchart illustrating the post-processing reference table editing process according to one embodiment of this application; Figure 5 This is a flowchart of the post-processing traversal according to one embodiment of the present application; Figure 6 This is an example diagram of a post-processing device for body-in-white strength simulation results according to an embodiment of this application; Figure 7 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The following describes a method, apparatus, electronic device, and medium for post-processing body-in-white strength simulation results according to embodiments of this application, with reference to the accompanying drawings. Addressing the technical problems mentioned in the background art regarding the inefficiency, error-proneness, and long iteration cycles in manual data extraction, qualification assessment, and result recording during body-in-white strength simulation post-processing due to the large number of parts and various working conditions, this application provides a method for post-processing body-in-white strength simulation results. In this method, a finite element model of the body-in-white is constructed based on its geometric data. A load file is created based on a pre-constructed load decomposition table of multiple preset working conditions and input into the finite element model to obtain the body-in-white strength simulation results. A post-processing analysis reference table is generated based on the component attributes in the finite element model. The strength simulation results and the post-processing analysis reference table are input into preset post-processing software. The software iterates through each component under each preset working condition of the body-in-white in the strength simulation results to obtain the post-processed results of the body-in-white. This solves the technical problems of low efficiency, error-proneness, and long iteration cycles in the post-processing of body-in-white strength simulation, which is caused by the large number of parts and multiple working conditions. By generating a post-processing analysis reference table containing the strength target values ​​of each part in advance based on the part attributes in the finite element model, and then using CAE post-processing software to automatically traverse all working conditions and all parts, extract the maximum equivalent stress of each part and compare it with the strength target value in the reference table, and finally automatically identify and record unqualified parts, thus realizing fully automated post-processing of body-in-white strength simulation results.

[0025] Specifically, before introducing the embodiments of this application, we will first introduce the background technology and corresponding technical issues related to this application.

[0026] In the process of vehicle development, the body-in-white, as the core load-bearing skeleton of the automobile, is a key structure that supports all vehicle components, transmits loads, and ensures the safety of passengers. Its structural strength directly determines the safety, reliability, handling stability, and ride comfort of the vehicle under various driving scenarios. The body-in-white strength test is the most common steady-state or quasi-static load scenario that automobiles face in daily use. It mainly includes vertical impact conditions, braking conditions, and cornering conditions. Although these conditions do not reach extreme load strengths such as collisions, the loads are applied frequently and the conditions are diverse. Moreover, there is a coupling effect between different load types (vertical, longitudinal, and lateral) under different conditions. Under long-term action, stress concentration, plastic deformation, and even fatigue failure can easily occur in local structures of the body-in-white, seriously affecting the service life of the entire vehicle and driving safety.

[0027] The number of structural components in a body-in-white is generally around 300 to 400. A single analysis requires stress assessment and optimization for each component. The CAE analysis process requires approximately 4-5 rounds of analysis iterations and optimizations. When performing finite element analysis of body-in-white strength, a large number of repetitive post-processing operations on the model need to be performed manually, and the analysis results need to be recorded manually. This results in low work efficiency, a high impact on design cycle costs, and a high risk of human error, leading to distortion of simulation analysis results.

[0028] In the relevant technologies, there are two major problems in the post-processing of body-in-white strength simulation, which seriously restrict the efficiency of product development and the quality control effect: (1) Data processing is difficult. After the body-in-white is finely modeled, the simulation calculation will generate a large amount of data, involving about 300 to 400 parts of the body. When processing manually, it is necessary to extract and organize the data one by one, and repeatedly check the accuracy of the data. It is easy to have problems such as data omission, calculation error, and parameter confusion. Once an error occurs, the simulation calculation needs to be restarted and the processing process repeated, which greatly increases the workload; (2) The optimization process is cumbersome and inefficient. The optimization of the body-in-white structure needs to be based on the results of multiple rounds of simulation. Manually, it is necessary to repeatedly record the simulation data of different optimization schemes, compare the performance differences of each scheme, and statistically analyze the changing trends of key indicators. This is not only time-consuming and labor-intensive, but also difficult to quickly locate the optimal optimization direction, resulting in an excessively long optimization cycle and the inability to solve potential structural problems in the design stage in a timely manner.

[0029] Therefore, based on the aforementioned technical problems, this application embodiment implements an automatic post-processing analysis method for rapidly extracting body-in-white strength simulation results using the pre-processing software HYPERMESH in Hyperworks and the Python language. This effectively solves the core problems of large data volume, error-proneness, repetitive work, and low efficiency in the post-processing methods of related technologies, providing efficient, accurate, and convenient technical support for body-in-white product design and optimization.

[0030] Specifically, Figure 1 This is a flowchart illustrating a method for post-processing simulation results of body-in-white strength provided in an embodiment of this application.

[0031] like Figure 1 As shown, the post-processing method for the body-in-white strength simulation results includes the following steps: In step S101, the geometric data of the body-in-white is obtained, and a finite element model of the body-in-white is constructed after the geometric data is checked and approved.

[0032] Furthermore, in some embodiments, before constructing the finite element model of the body-in-white, the method further includes: using preprocessing software to check the geometric data of the body-in-white, and when the check results meet the preset check conditions, selecting the target surface of the body-in-white for mesh generation; based on the mesh generation results and the material property information of the body-in-white, modifying the component name of each component according to the component list table to obtain the material property information of each component, and constructing the connection relationship between the body-in-white and each component based on the material property information of each component.

[0033] The preset inspection conditions can be set by those skilled in the art based on the post-processing requirements of the body-in-white simulation results, and are not specifically limited here.

[0034] Specifically, such as Figure 2 As shown, firstly, the geometric data of the body-in-white is acquired, such as the external contour dimensions, wheelbase and track width, and key positions of the body. The geometric data of the body-in-white is then imported into the pre-processing software HYPERMESH, and the geometric data of the body-in-white is checked. The check results must meet the preset check conditions, that is, the positional relationship between the data must be correct, there must be no penetration, the geometry must not have broken surfaces or free edges, and the assembly relationship of each component must be correct. When the above conditions are met, the check results are determined to meet the preset check conditions.

[0035] Secondly, in this embodiment, shell meshes are used for both sheet metal and plastic parts. When the inspection results meet the preset inspection conditions, the target surface of the body-in-white (i.e., the neutral surface of each component extracted from the sheet metal parts of the body-in-white) is selected for meshing. The mesh size is 8mm, and areas of different thicknesses are placed in different layers. The reinforcing ribs of the plastic parts are also extracted from the neutral surface and connected to the body using node coupling. At the same time, first-order tetrahedral solid elements with a unit size of 3mm are used for the cast aluminum parts. Then, the quality of the mesh is checked, and the elements that do not meet the mesh quality requirements are adjusted. The mesh quality parameters are shown in Table 1. Table 1

[0036] Next, based on the mesh generation results and the material property information of the body-in-white, the part name of each component is modified according to the bill of parts (BOM) table to obtain the material property information of each component. The connection relationship between the body-in-white and each component is constructed, connecting components such as the battery, subframe, front frame, and four doors and two hoods. Then, based on the connection relationship, the finite element model of the body-in-white is constructed.

[0037] Specifically, such as Figure 2 and Figure 3 As shown, based on the material parameters used in the BOM (Bill of Materials), the shell element is assigned a thickness attribute according to the actual thickness of the parts. The parts are named "Part Number (7 digits)_Material_XXX", for example: "5101021_St280D+Z-60 / 60_T80". After the parts are assigned material attributes, it is confirmed that the weight information of the model is consistent with the weight provided by the design. If there is a large deviation, it is necessary to further check whether the material and attribute parameters are correct. Then, according to the actual vehicle connection relationship, the connection of the four doors and two hoods, as well as the front frame, subframe and other accessories is completed. The mass of the four doors and two hoods is assigned using mass points. Flexible elements are used to connect them to the body. Rigid elements are used for the bolted parts. First-order hexahedral elements are used for the weld points with a diameter of 6mm. First-order pentahedral elements are used for the welds. First-order hexahedral elements are also selected for the adhesives, thus constructing the finite element model of the body-in-white.

[0038] In step S102, a load file is created based on a pre-constructed load decomposition table of multiple preset working conditions, and the load file is input into the finite element model to obtain the strength simulation results of the body-in-white.

[0039] Furthermore, in some embodiments, the load file is input into the finite element model to obtain the strength simulation results of the body-in-white, including: calculating the load file based on the analysis type and parameter settings of the finite element model; obtaining the stress distribution and displacement deformation results of the body-in-white under each preset working condition based on the calculation results of the load file, and generating the model file and calculation result file of the body-in-white.

[0040] The preset working conditions can be set by those skilled in the art based on the post-processing requirements of the body-in-white simulation results, and are not specifically limited here.

[0041] Specifically, such as Figure 2 As shown, in this embodiment of the application, the load decomposition table is first read and a load file is created based on a number of pre-built preset working conditions, such as emergency braking, extreme turning, and vertical impact. For example, the theoretical load data in the decomposition table is converted into a format that can be recognized by the finite element solver, and an independent load sub-working condition definition is generated for each preset working condition. This ensures that the load set corresponding to each preset working condition corresponds one-to-one with the preset working condition name, forming a comprehensive load file that includes all extreme working conditions.

[0042] Secondly, the completed load file is imported into the finite element model. Since the actual load usually acts on the suspension mounting point, powertrain mounting point, etc., and these locations may correspond to holes or specific connection areas in the finite element model, it is necessary to process the loading point. This mainly includes: determining the target node or geometric center of the load application, and using rigid elements to couple the load application point with the actual connection area of ​​the vehicle body or subframe, so as to uniformly and realistically transfer the concentrated force or torque to the vehicle body structure, simulate the force flow transmission path in the actual physical connection, and avoid calculation distortion caused by local stress concentration.

[0043] Next, based on the analysis type (such as linear static analysis) and parameter settings of the finite element model, the imported load file is submitted to NASTRAN for solution calculation. This mainly includes: analysis type settings, loading method settings, output card settings, and model file export.

[0044] Among them, the analysis type is selected as static analysis, and the corresponding solution sequence keyword is sol101. Static analysis is used to calculate the response of the structure under static load, including physical quantities such as stress, strain and displacement. It is suitable for strength assessment of the body-in-white under quasi-static conditions such as vertical impact, braking and turning.

[0045] The loading method adopted is the inertial release loading method, with the corresponding keyword INREL,-2. Inertial release is a calculation method for handling unbalanced load systems. It balances the external load by applying inertial force, so that the entire system is in a self-balancing state and can be solved without the need for additional constraints. This loading method is particularly suitable for the strength analysis of free-free structures such as body-in-white, and can effectively avoid additional stress introduced by improper constraints.

[0046] The output card options include two parts: nodal displacement and element stress. For nodal displacement, select all nodes of the overall finite element model and output the displacement values ​​of each node in the three translational degrees of freedom in the global coordinate system. This data is used to evaluate the overall deformation mode and local deformation of the body-in-white under various working conditions. For element stress, only the equivalent stress of the sheet metal elements is output, and the elements connected to the rigid elements are removed. The purpose of this setting is that the elements directly connected to the rigid elements often have stress concentration in the stress calculation results. These values ​​cannot truly reflect the actual stress state of the structure. Excluding them can avoid interference with the analysis results.

[0047] The model file is exported in BDF format. BDF files are the standard input files for the NASTRAN solver and contain complete model data, including node coordinates, element connections, material properties, boundary conditions, load information, and solver control cards.

[0048] Finally, the exported BDF format model file is submitted to NASTRAN for calculation. After reading the BDF file, the NASTRAN solver assembles the overall stiffness matrix and load vectors according to the SOL101 static analysis workflow, and uses a sparse matrix solver to solve the linear equations to obtain the displacement response of each node under various load conditions. Then, the element stress is calculated through the strain-displacement relationship, and the result is generated in op2 format (NASTRAN Output File Version). 2) The calculation result file, op2 file, is a NASTRAN binary calculation result file. This calculation result file contains the complete strength simulation results of the body-in-white under all preset working conditions. It mainly includes displacement results: the displacement value of each node under each working condition, used to evaluate the overall stiffness of the body-in-white and check key mounting points, etc.; stress results: the equivalent stress of each element under each working condition. For sheet metal parts, the output is the mid-surface stress of the shell element, including the upper surface stress, lower surface stress and mid-surface stress. These data are the core basis for subsequent strength qualification judgment; working condition labels: each result data is associated with the corresponding working condition label (such as vertical impact, turning, maximum braking, etc.), which facilitates the extraction of data by working condition in the post-processing stage.

[0049] In step S103, a post-processing analysis reference table is generated based on the component properties in the finite element model. The strength simulation results and the post-processing analysis reference table are input into the preset post-processing software. The preset post-processing software is then used to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

[0050] Furthermore, in some embodiments, the preset post-processing software is used to traverse multiple preset working conditions of the body-in-white and each component under each preset working condition in the strength simulation results to obtain the post-processing results of the body-in-white, including: extracting the maximum equivalent stress of each component under the current preset working condition based on multiple preset working conditions of the body-in-white and each component under each preset working condition; comparing the maximum equivalent stress with the strength target value corresponding to each part in the post-processing analysis reference table, and determining the target part to be optimized.

[0051] Furthermore, in some embodiments, determining the target part to be optimized includes: determining whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value; if the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, then the target part with the maximum equivalent stress greater than the corresponding strength target value is determined to be unqualified, and the unqualified target part is taken as the target part to be optimized, and the unqualified information of the target part to be optimized is recorded; the target part to be optimized is optimized, and the optimized target parts are traversed until all target parts are qualified.

[0052] The preset post-processing software can be selected based on a comprehensive consideration of four core dimensions: solver compatibility, analysis type requirements, automation scalability, and industry standards. No specific limitations are made here.

[0053] Specifically, such as Figure 4As shown, firstly, the completed finite element model is opened in the HyperMesh preprocessing software. An interactive plugin developed using XML and Python is then used and called within the Hyperworks extension plugin. After encapsulation, a one-click call is implemented in the custom tool, automatically filtering out the sheet metal parts to be examined in the finite element model based on their properties. Secondly, after exporting the component data, a strength target value is set for each component based on the material used. The strength target value is set based on the yield strength of the material used in the component, meaning the maximum equivalent stress the component can withstand during service should not exceed the yield strength of its material. In other words, the strength target is ≤ the yield strength of the material used. For example, the material used in "5401151_FC330 / 590DH_T200" is FC33. The strength target is ≤330MPa for 0 / 590DH. After setting, a post-processing analysis reference table is generated, as shown in Table 2. This post-processing analysis reference table provides the basis for subsequent automated judgment, that is, the upper limit of stress that each component should meet under different working conditions. Next, the model file and calculation result file in the strength simulation results, as well as the post-processing analysis reference table, are input into the preset post-processing software, such as Hyperview. After importing, click the automated processing plug-in button integrated in the Hyperview toolbar, select the above post-processing analysis reference table file, and specify the save location of the result report. The plug-in then starts to automatically perform post-processing analysis and uses the preset post-processing software to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition.

[0054] Table 2

[0055] Specifically, in the process of using the preset post-processing software to traverse multiple preset working conditions of the body-in-white and each component under each preset working condition in the strength simulation results, the plug-in adopts a double-layer loop traversal logic structure to fully automate the body-in-white strength simulation results. First, the plug-in automatically reads all the calculation working condition identifiers in the op2 calculation result file and traverses each preset working condition in turn, as shown in Table 3, including but not limited to vertical impact, turning, maximum braking, maximum acceleration, lateral impact, reversing braking, etc.

[0056] Table 3

[0057] Secondly, such as Figure 5As shown, under the current traversal condition, the plugin automatically identifies all components in the BDF model file and sequentially traverses each component that needs to be examined. The traversal range covers all sheet metal parts of the body-in-white, typically around 300 to 400. It also extracts the maximum equivalent stress of each component under the current preset traversal condition and the components being traversed. Furthermore, it traverses the equivalent stress values ​​of all units of the component and extracts the maximum value as the maximum equivalent stress of the component under the current preset traversal condition.

[0058] Finally, the extracted maximum equivalent stress is compared with the strength target value corresponding to each part in the post-processing analysis reference table. If the maximum equivalent stress is less than or equal to the strength target value, the part is determined to meet the strength requirements under the current preset working condition. If the maximum equivalent stress is greater than the strength target value, the part is determined to not meet the strength requirements under the current preset working condition. When the determination result is unqualified, the plugin identifies the part as the target part to be optimized and records the unqualified information of the target part to be optimized, such as the part name, the unqualified working condition, the material grade, the strength target value, and the maximum equivalent stress. Then, for the unqualified working condition results, the target part to be optimized is optimized. The optimization methods include adjusting the number and height of the reinforcing ribs, replacing the material grade, and adjusting the local thickness. The optimized target parts are then traversed until all target parts are qualified, as shown in Table 4.

[0059] Table 4

[0060] Furthermore, after the plugin completes the traversal of all preset working conditions and all components, it automatically generates an Excel-formatted results report. This report lists detailed information on all target parts to be optimized (i.e., non-conforming parts) in a checklist format, making it easier for designers to quickly locate problem areas and carry out targeted structural optimization.

[0061] It should be noted that the finite element modeling process in the embodiments of this application can be replaced by other pre-processing software, for example, the Python language can be replaced by the Tcl language.

[0062] In summary, this application, through automated post-processing, can quickly and accurately extract simulation data and precisely identify dangerous areas of the body-in-white under various working conditions (such as stress concentration points and structural weak points). Based on this accurate data, those skilled in the art can optimize the body structure in a targeted manner during the product design stage, avoid product problems such as body deformation and cracking that may occur during actual vehicle operation, improve the strength, reliability and service life of the body-in-white, and ensure vehicle driving safety.

[0063] The use of embodiments of this application can shorten the product development cycle, improve development efficiency, and further realize full automation of post-processing. Data sorting, statistics, and comparison can be completed without manual intervention, which greatly reduces the workload and time consumption of post-processing. At the same time, it accelerates the iteration speed of structural optimization, allowing those skilled in the art to devote more energy to structural innovation and optimization design, effectively shortening the product development cycle of body-in-white and even the whole vehicle, helping products to be launched to the market quickly, and enhancing the market competitiveness of enterprises.

[0064] According to the post-processing method for body-in-white strength simulation results in this application embodiment, a finite element model of the body-in-white is constructed based on the geometric data of the body-in-white. A load file is created based on a pre-constructed load decomposition table of multiple preset working conditions and input into the finite element model to obtain the strength simulation results of the body-in-white. A post-processing analysis reference table is generated based on the component attributes in the finite element model. The strength simulation results and the post-processing analysis reference table are input into a preset post-processing software. The software iterates through each component under each preset working condition of the body-in-white in the strength simulation results to obtain the post-processing results of the body-in-white. This solves the technical problems of low efficiency, error-proneness, and long iteration cycles in the post-processing of body-in-white strength simulation due to the large number of components and working conditions, which often result in manual data extraction, manual qualification judgment, and result recording. By pre-generating a post-processing analysis reference table containing the strength target values ​​of each component based on the component attributes in the finite element model, and then using CAE post-processing software to automatically traverse all working conditions and all components, the maximum equivalent stress of each component is extracted and compared with the strength target values ​​in the reference table. Finally, unqualified components are automatically identified and recorded, thus achieving fully automated post-processing of the body-in-white strength simulation results.

[0065] Next, referring to the accompanying drawings, a post-processing device for the simulation results of the body-in-white strength proposed according to an embodiment of this application is described.

[0066] Figure 6 This is a block diagram of the post-processing device for the body-in-white strength simulation results according to an embodiment of this application.

[0067] like Figure 6 As shown, the post-processing device 10 for the simulation results of the body-in-white strength includes: an acquisition module 100, a transmission module 200, and a traversal module 300.

[0068] Among them, the acquisition module 100 is used to acquire the geometric data of the body-in-white and construct the finite element model of the body-in-white after the geometric data has passed the check. The transmission module 200 is used to create load files based on a pre-built load decomposition table of multiple preset working conditions, and input the load files into the finite element model to obtain the strength simulation results of the body-in-white. The traversal module 300 is used to generate a post-processing analysis reference table based on the component properties in the finite element model. The strength simulation results and the post-processing analysis reference table are input into the preset post-processing software. The preset post-processing software is used to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

[0069] Furthermore, in some embodiments, the traversal module 300 includes: The extraction unit is used to extract the maximum equivalent stress of each component under the current preset working condition based on multiple preset working conditions of the body-in-white and each component under each preset working condition. The comparison unit is used to compare the maximum equivalent stress with the strength target value corresponding to each part in the post-processing analysis reference table, and to determine the target part to be optimized.

[0070] Furthermore, in some embodiments, the comparison unit includes: The judgment sub-unit is used to determine whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value. The recording subunit is used to determine that if the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, the target component with the maximum equivalent stress greater than the corresponding strength target value is unqualified, and the unqualified target component is used as the target component to be optimized, and the unqualified information of the target component to be optimized is recorded. The optimization sub-unit is used to optimize the target part to be optimized, and continues to traverse the optimized target parts until all target parts are qualified.

[0071] Furthermore, in some embodiments, the transmission module 200 includes: The calculation unit is used to calculate the load file based on the analysis type and parameter settings of the finite element model; The generation unit is used to obtain the stress distribution and displacement deformation results of the body-in-white under each preset working condition based on the calculation results of the load file, and to generate the model file and calculation result file of the body-in-white.

[0072] Furthermore, in some embodiments, before constructing the finite element model of the body-in-white, the acquisition module 100 further includes: The meshing unit is used to check the geometric data of the body-in-white using preprocessing software, and selects the target surface of the body-in-white for meshing when the check results meet the preset check conditions. The building unit is used to modify the part name of each component according to the part list table based on the mesh generation results and the material property information of the body-in-white, obtain the material property information of each component, and build the connection relationship between the body-in-white and each component based on the material property information of each component.

[0073] According to the post-processing device for body-in-white strength simulation results according to the embodiments of this application, a finite element model of the body-in-white is constructed based on the geometric data of the body-in-white, and a load file is created based on a pre-constructed load decomposition table of multiple preset working conditions. This load file is then input into the finite element model to obtain the strength simulation results of the body-in-white. A post-processing analysis reference table is generated based on the component attributes in the finite element model. The strength simulation results and the post-processing analysis reference table are then input into a preset post-processing software. The software iterates through each component under each preset working condition of the body-in-white in the strength simulation results to obtain the post-processing results of the body-in-white. This solves the technical problems of low efficiency, error-proneness, and long iteration cycles in the post-processing of body-in-white strength simulation, which are caused by the large number of components and working conditions. By pre-generating a post-processing analysis reference table containing the strength target values ​​of each component based on the component attributes in the finite element model, and then using CAE post-processing software to automatically traverse all working conditions and all components, the maximum equivalent stress of each component is extracted and compared with the strength target value in the reference table. Finally, unqualified components are automatically identified and recorded, thereby realizing fully automated post-processing of body-in-white strength simulation results.

[0074] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 701, the processor 702, and the computer program stored on the memory 701 and executable on the processor 702.

[0075] When the processor 702 executes the program, it implements the post-processing method for the body-in-white strength simulation results provided in the above embodiments.

[0076] Furthermore, electronic devices also include: Communication interface 703 is used for communication between memory 701 and processor 702.

[0077] The memory 701 is used to store computer programs that can run on the processor 702.

[0078] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0079] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0080] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0081] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0082] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described post-processing method for the simulation results of the body-in-white strength.

[0083] This embodiment also provides a computer program product, including a computer program that is executed to implement the post-processing method for the body-in-white strength simulation results of the above embodiment.

[0084] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0085] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0086] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0087] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0088] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0089] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0090] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0091] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A post-processing method for simulation results of body-in-white strength, characterized in that, Includes the following steps: Obtain the geometric data of the body-in-white, and construct the finite element model of the body-in-white after the geometric data passes the inspection; A load file is created based on a pre-constructed load decomposition table of multiple preset working conditions, and the load file is input into the finite element model to obtain the strength simulation results of the body-in-white. A post-processing analysis reference table is generated based on the component properties in the finite element model. The strength simulation results and the post-processing analysis reference table are input into a preset post-processing software. The preset post-processing software is then used to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

2. The method according to claim 1, characterized in that, The step of using the preset post-processing software to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white includes: Based on multiple preset working conditions of the body-in-white and each component under each preset working condition, the maximum equivalent stress of each component under the current preset working condition is extracted; The maximum equivalent stress is compared with the strength target value corresponding to each part in the post-processing analysis reference table, and the target part to be optimized is determined.

3. The method according to claim 2, characterized in that, The process of determining the target part to be optimized includes: Determine whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value; If the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, then the target component whose maximum equivalent stress is greater than the corresponding strength target value is determined to be unqualified. The unqualified target component is then used as the target component to be optimized, and the unqualified information of the target component to be optimized is recorded. Optimize the target part to be optimized, and continue to traverse the optimized target parts until all target parts are qualified.

4. The method according to claim 1, characterized in that, The step of inputting the load file into the finite element model to obtain the strength simulation results of the body-in-white includes: Based on the analysis type and parameter settings of the finite element model, calculate the load file; Based on the calculation results of the load file, the stress distribution and displacement deformation results of the body-in-white under each preset working condition are obtained, and the model file and calculation result file of the body-in-white are generated.

5. The method according to claim 1, characterized in that, Before constructing the finite element model of the body-in-white, the following steps are also included: The geometric data of the body-in-white are checked using preprocessing software, and when the check results meet the preset check conditions, the target surface of the body-in-white is selected for mesh generation. Based on the mesh generation results and the material property information of the body-in-white, the component name of each component is modified according to the component list table to obtain the material property information of each component, and the connection relationship between the body-in-white and each component is constructed based on the material property information of each component.

6. A post-processing device for simulation results of body-in-white strength, characterized in that, include: The acquisition module is used to acquire the geometric data of the body-in-white and construct the finite element model of the body-in-white after the geometric data has passed the inspection. The transmission module is used to generate a load file based on a pre-built load decomposition table of multiple preset working conditions, and input the load file into the finite element model to obtain the strength simulation results of the body-in-white. The traversal module is used to generate a post-processing analysis reference table based on the component properties in the finite element model, input the strength simulation results and the post-processing analysis reference table into the preset post-processing software, and use the preset post-processing software to traverse multiple preset working conditions of the body-in-white in the strength simulation results and each component under each preset working condition to obtain the post-processing results of the body-in-white.

7. The apparatus according to claim 6, characterized in that, The traversal module includes: The extraction unit is used to extract the maximum equivalent stress of each component under the current preset working condition based on multiple preset working conditions of the body-in-white and each component under each preset working condition; The comparison unit is used to compare the maximum equivalent stress with the strength target value corresponding to each part in the post-processing analysis reference table, and to determine the target part to be optimized.

8. The apparatus according to claim 7, characterized in that, The comparison unit includes: The judgment subunit is used to determine whether the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value. The recording subunit is used to determine that if the maximum equivalent stress of each component under the current preset working condition is greater than the corresponding strength target value, the target component with the maximum equivalent stress greater than the corresponding strength target value is unqualified, and the unqualified target component is used as the target component to be optimized, and the unqualified information of the target component to be optimized is recorded. An optimization subunit is used to optimize the target part to be optimized and continue to traverse the optimized target parts until all target parts are qualified.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the post-processing method for body-in-white strength simulation results as described in any one of claims 1-5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the post-processing method for the simulation results of the body-in-white strength as described in any one of claims 1-5.

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