Whole vehicle performance analysis optimization method, device and equipment and storage medium

Abstract

The application belongs to the technical field of automobile manufacturing, and discloses a whole vehicle performance analysis optimization method, device, equipment and storage medium. The method comprises the following steps: constructing a whole vehicle finite element model; loading the whole vehicle finite element model, performing finite element simulation analysis, screening important index items as sub-targets of target optimization, and determining corresponding target values; screening parts and components strongly related to the performance of the whole vehicle from the whole vehicle model; taking the minimum total weight of the parts and components as the final target of target optimization; constructing a target simulation approximate model based on the parts and components; constructing a target optimization process according to the target values corresponding to the sub-targets and the final target corresponding to the parts and components; performing simulation calculation according to the target simulation approximate model, determining the optimal solution of the target optimization process, and obtaining an optimization result. In the optimization stage, the performance and the quality are considered comprehensively to optimize the performance and the quality of the performance sub-targets, so that the whole vehicle performance and the quality reach an optimal balanced relationship.

Description

Technical Field

[0001] This invention relates to the field of automobile manufacturing technology, and in particular to a method, apparatus, equipment, and storage medium for whole vehicle performance analysis and optimization. Background Technology

[0002] In the CAE analysis system for vehicle development, the performance of the entire vehicle is constrained and evaluated from multiple disciplines closely related to the vehicle body structure, such as safety crash testing, NVH (noise, vibration, and harshness), structural stiffness and strength, and fatigue durability. Currently, each discipline has its own set of objectives and evaluation systems, but for the entire vehicle, there may be excessive overlap in the evaluation of performance across different disciplines.

[0003] Lightweighting is a major challenge for vehicle manufacturers. In terms of overall vehicle performance, there are conflicts between optimizing the performance of various disciplines and between optimizing the performance of various disciplines and lightweighting. How to balance the relationship between the performance of various disciplines and the relationship between overall vehicle performance and weight, and ultimately achieve a balance between "performance-weight-cost", is a common focus of attention in the industry.

[0004] 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

[0005] The main objective of this invention is to provide a method, apparatus, device, and storage medium for analyzing and optimizing vehicle performance, aiming to solve the technical problem of how to balance the relationship between the performance of various disciplines and the relationship between the overall vehicle performance and weight.

[0006] To achieve the above objectives, the present invention provides a method for analyzing and optimizing vehicle performance, the method comprising the following steps:

[0007] Construct a finite element model of the entire vehicle;

[0008] The finite element model of the whole vehicle is subjected to constraint loading, and finite element simulation analysis is performed to screen out important indicators that are strongly related to the overall structure of the vehicle body;

[0009] The aforementioned key indicators are used as sub-objectives for target optimization, and the target values ​​corresponding to the sub-objectives are determined.

[0010] Select components that are highly relevant to the overall vehicle performance from the vehicle model;

[0011] The minimum total weight of the components is taken as the final target for optimization.

[0012] A target simulation approximation model is constructed based on the aforementioned components;

[0013] A target optimization process is constructed based on the target values ​​corresponding to the sub-project targets and the final targets corresponding to the components.

[0014] Simulation calculations are performed based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result.

[0015] Optionally, the constraints are applied to the whole vehicle finite element model, and finite element simulation analysis is performed to screen out important indicators that are strongly related to the overall vehicle structure, including:

[0016] The finite element model of the whole vehicle is subjected to constraint loading, and finite element simulation analysis is performed to obtain the simulation analysis results;

[0017] The simulation analysis results are post-processed to obtain the benchmark analysis results;

[0018] Based on the benchmark analysis results and the corresponding vehicle technical specifications, a preliminary evaluation was conducted, and key performance indicators that are strongly correlated with the overall vehicle structure were selected from the various performance indicators.

[0019] Optionally, the benchmark analysis results include safety collision benchmark analysis results, NVH benchmark analysis results, structural stiffness benchmark analysis results, structural strength benchmark analysis results, and fatigue durability benchmark analysis results;

[0020] The post-processing of the simulation analysis results to obtain the benchmark analysis results includes:

[0021] Determine the performance items to be examined for the preset target decomposition and the examination points corresponding to the performance items, extract the intrusion amount and acceleration corresponding to the examination points, and record the intrusion amount and acceleration corresponding to the examination points as the safety collision benchmark analysis results;

[0022] Create dynamic stiffness response point acceleration curves and convert them into dynamic stiffness values; read the X-direction displacement of NTF response points and convert it into noise values; create VTF response point acceleration curves and read the peak values ​​of the curves; record the dynamic stiffness values, the noise values, and the peak values ​​of the curves as NVH benchmark analysis results.

[0023] Read the Z-direction displacement corresponding to each of the aforementioned examination points, calculate the corresponding stiffness value based on the Z-direction displacement, and record the stiffness value as the structural stiffness benchmark analysis result;

[0024] The maximum stress value of each component is read according to the preset yield strength of each component, and the maximum stress value of each component is recorded as the structural strength benchmark analysis result.

[0025] Read the damage value of the connection location that is greater than a preset threshold, and record the damage value of the connection location as the fatigue durability benchmark analysis result.

[0026] Optionally, the preliminary evaluation based on the benchmark analysis results and the corresponding vehicle technical specifications, and the selection of key indicators with strong correlation to the overall vehicle structure from various performance indicators, includes:

[0027] Based on the benchmark analysis results and the corresponding vehicle technical specifications, a preliminary evaluation is conducted to determine the compliant and non-compliant items, and the compliant and non-compliant items are used as initial key indicators.

[0028] By excluding the preset vehicle fatigue durability dimension and preset vehicle strength related indicators from the initial important indicators, important indicators with strong correlation to the overall vehicle structure are obtained.

[0029] Optionally, the step of performing simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result includes:

[0030] Simulation calculations are performed based on the target simulation approximation model to minimize the final target and maximize the target values ​​corresponding to the sub-targets, thereby determining the optimal solution of the target optimization process and obtaining the optimization results.

[0031] Optionally, after performing simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result, the method further includes:

[0032] Assign the thickness variable value corresponding to the optimal solution to the variable components in the benchmark analysis model of each discipline dimension to obtain the verification model;

[0033] Based on the verification model, analysis is performed to determine performance target achievement information and quality change information;

[0034] A comprehensive evaluation is conducted based on the performance target achievement information and the quality change information to obtain a comprehensive evaluation result.

[0035] Optionally, after analyzing the verification model to determine performance target achievement information and quality change information, the method further includes:

[0036] If the performance target achievement information does not meet the preset performance requirements, and the quality change information does not meet the preset quality requirements, then the target optimization process is adjusted.

[0037] Simulation calculations are performed based on the target simulation approximation model to determine the optimal solution corresponding to the adjusted target optimization process, and the adjusted optimization result is obtained.

[0038] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle performance analysis and optimization device, the vehicle performance analysis and optimization device comprising:

[0039] The building module is used to construct the finite element model of the entire vehicle;

[0040] The finite element simulation analysis module is used to constrain and load the whole vehicle finite element model, perform finite element simulation analysis, and screen out important indicators that are strongly related to the overall structure of the vehicle body.

[0041] The optimization item determination module is used to take the important indicator items as sub-objectives for target optimization and determine the target values ​​corresponding to the sub-objectives;

[0042] The filtering module is used to filter out components that are highly relevant to the overall vehicle performance from the vehicle model;

[0043] The optimization term determination module is further configured to take the minimum total weight of the components as the final target of the optimization.

[0044] An approximate model construction module is used to construct an approximate model of the target simulation based on the components;

[0045] The optimization item determination module is also used to construct a target optimization process based on the target value corresponding to the sub-item target and the final target corresponding to the component;

[0046] The optimization module is used to perform simulation calculations based on the target simulation approximation model, determine the optimal solution of the target optimization process, and obtain the optimization result.

[0047] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle performance analysis and optimization device, which includes: a memory, a processor, and a vehicle performance analysis and optimization program stored in the memory and executable on the processor. The vehicle performance analysis and optimization program is configured to implement the vehicle performance analysis and optimization method described above.

[0048] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a vehicle performance analysis and optimization program, wherein the vehicle performance analysis and optimization program, when executed by a processor, implements the vehicle performance analysis and optimization method as described above.

[0049] This invention constructs a finite element model of the entire vehicle; applies constraints to the finite element model and performs finite element simulation analysis to identify key indicators strongly correlated with the overall vehicle structure; uses these key indicators as sub-objectives for optimization and determines their corresponding target values; selects components strongly related to overall vehicle performance from the vehicle model; uses the minimum total weight of these components as the final objective for optimization; constructs an approximate simulation model based on the components; constructs an optimization process based on the target values ​​of the sub-objectives and the final objective of the components; and performs simulation calculations based on the approximate simulation model to determine the optimal solution for the optimization process, thus obtaining the optimization result. Through this approach, in the optimization phase, performance and quality are considered holistically to optimize performance-deficient items and quality, optimizing both overall vehicle performance and quality while also addressing design conflicts between different disciplines, achieving an optimal balance between overall vehicle performance and quality. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the structure of the vehicle performance analysis and optimization device for the hardware operating environment involved in the embodiments of the present invention;

[0051] Figure 2 This is a flowchart illustrating the first embodiment of the vehicle performance analysis and optimization method of the present invention;

[0052] Figure 3 This is a flowchart illustrating the second embodiment of the vehicle performance analysis and optimization method of the present invention;

[0053] Figure 4 This is a structural block diagram of the first embodiment of the vehicle performance analysis and optimization device of the present invention.

[0054] 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

[0055] 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.

[0056] Reference Figure 1 , Figure 1 This is a schematic diagram of the vehicle performance analysis and optimization equipment structure for the hardware operating environment involved in the embodiments of the present invention.

[0057] like Figure 1As shown, the vehicle performance analysis and optimization device 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 high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0058] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the vehicle performance analysis and optimization equipment, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0059] 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 vehicle performance analysis and optimization program.

[0060] exist Figure 1 In the vehicle performance analysis and optimization device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the vehicle performance analysis and optimization device of the present invention can be set in the vehicle performance analysis and optimization device. The vehicle performance analysis and optimization device calls the vehicle performance analysis and optimization program stored in the memory 1005 through the processor 1001 and executes the vehicle performance analysis and optimization method provided in the embodiment of the present invention.

[0061] This invention provides a method for analyzing and optimizing vehicle performance, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the vehicle performance analysis and optimization method of the present invention.

[0062] In this embodiment, the vehicle performance analysis and optimization method includes the following steps:

[0063] Step S10: Construct the finite element model of the whole vehicle.

[0064] It is understood that the execution subject of this embodiment is a vehicle performance analysis and optimization device. The vehicle performance analysis and optimization device can be a computer, processor, server, or other devices with the same or similar functions. This embodiment does not limit this.

[0065] It should be noted that the process involves obtaining the complete vehicle CAD model and then building a finite element model of the vehicle according to the model requirements. Optionally, different CAE disciplines have different modeling requirements for the complete vehicle model, and the model should be built differently based on the specific requirements of each discipline. Specifically, the constructed complete vehicle finite element model is a loadable and computationally achievable model with assigned material thicknesses and established connection relationships.

[0066] Step S20: Apply constraints to the whole vehicle finite element model and perform finite element simulation analysis to screen out important indicators that are strongly related to the overall structure of the vehicle body.

[0067] It should be understood that the loading conditions and software operating environment requirements differ across different disciplines. Therefore, constraint loading and analysis calculations should be differentiated according to the specific requirements of each discipline. Specifically, safety collision calculations are performed using the Lsdyna environment; NVH performance calculations are performed using the Nastran or OptiSticCUT environments; structural stiffness and strength calculations are performed using the Nastran or Abaqus environments; and fatigue durability calculations are performed using the Nastran / Ncode environment.

[0068] Further, step S20 includes: constraining and loading the whole vehicle finite element model, and performing finite element simulation analysis to obtain simulation analysis results; post-processing the simulation analysis results to obtain benchmark analysis results; and conducting a preliminary evaluation based on the benchmark analysis results and the corresponding whole vehicle technical specifications to select important indicators that are strongly related to the overall structure of the vehicle body from various performance indicators.

[0069] It should be noted that a model with pre-assigned material thickness and established connection relationships under constraint loading is used for simulation analysis. The simulation analysis results are then post-processed and recorded as the baseline analysis results. Based on the baseline analysis results and the corresponding Vehicle Technical Specifications (VTS), a preliminary evaluation is conducted, and key performance indicators with strong correlation to the overall vehicle body structure are selected from various performance indicators.

[0070] Furthermore, the benchmark analysis results include safety collision benchmark analysis results, NVH benchmark analysis results, structural stiffness benchmark analysis results, structural strength benchmark analysis results, and fatigue durability benchmark analysis results;

[0071] The post-processing of the simulation analysis results to obtain benchmark analysis results includes: determining the performance items to be examined by the preset target decomposition and the examination points corresponding to the performance items; extracting the intrusion amount and acceleration corresponding to the examination points; recording the intrusion amount and acceleration corresponding to the examination points as safety collision benchmark analysis results; creating dynamic stiffness response point acceleration curves and converting them into dynamic stiffness values; reading the X-direction displacement of the NTF response points and converting it into noise values; creating VTF response point acceleration curves and reading the peak values ​​of the curves; recording the dynamic stiffness values, the noise values, and the peak values ​​of the curves as NVH benchmark analysis results; reading the Z-direction displacement corresponding to each examination point; calculating the corresponding stiffness values ​​based on the Z-direction displacements; recording the stiffness values ​​as structural stiffness benchmark analysis results; reading the maximum stress values ​​of each component according to the preset yield strength corresponding to each component; recording the maximum stress values ​​corresponding to each component as structural strength benchmark analysis results; and reading the damage values ​​of connection locations where the damage values ​​are greater than a preset threshold; recording the damage values ​​of the connection locations as fatigue durability benchmark analysis results.

[0072] It should be understood that in the safety collision simulation analysis of this embodiment, based on the performance items decomposed from the preset target, the intrusion amount and acceleration of the test points are extracted and recorded as the base analysis results of the safety collision; in the NVH simulation analysis, the acceleration curve of the dynamic stiffness response point is generated and converted into a dynamic stiffness value, the X-direction displacement of the NTF response point is read and converted into a dB value, the VTF response point acceleration curve is generated and the peak value of the curve is read, and the above are summarized into the NVH result summary table and recorded as the base analysis results of NVH; in the structural stiffness simulation analysis, the Z-direction displacement of each test point is read and converted into the corresponding stiffness value through the calculation formula; in the structural strength simulation analysis, the maximum stress value of the component is read according to the yield strength defined for each component and recorded as the base analysis results of the structural strength; in the fatigue durability simulation analysis, the sheet metal and weld damage values ​​with damage values ​​> 1 are read and recorded as the base analysis results of the fatigue durability.

[0073] Furthermore, the preliminary evaluation based on the benchmark analysis results and the corresponding vehicle technical specifications, and the selection of important indicators with strong correlation to the overall vehicle structure from various performance indicators, includes: conducting a preliminary evaluation based on the benchmark analysis results and the corresponding vehicle technical specifications to determine the qualified and unqualified items, and using the qualified and unqualified items as initial important indicators; excluding indicators related to the preset vehicle fatigue durability dimension and preset vehicle strength from the initial important indicators to obtain important indicators with strong correlation to the overall vehicle structure.

[0074] It should be noted that the key indicators that are closely related to the overall structure of the vehicle body include the qualified and unqualified items in the Base analysis results. Since the two performance dimensions of vehicle fatigue durability and vehicle strength focus on unqualified parts, which can be solved through local structural optimization, this embodiment excludes all indicators of vehicle fatigue durability and vehicle strength from the initial key indicators and determines the key indicators that are closely related to the overall structure of the vehicle body.

[0075] Step S30: Take the important indicator items as sub-objectives for target optimization, and determine the target values ​​corresponding to the sub-objectives.

[0076] In the specific implementation, important indicators are selected as sub-objectives for multi-disciplinary and multi-objective optimization, and the minimum target value to be achieved for each sub-objective is set according to the preset objectives.

[0077] Step S40: Select components that are highly relevant to the overall vehicle performance from the vehicle model.

[0078] It should be understood that, optionally, sensitivity analysis can be used to screen out components that are strongly correlated with the overall vehicle performance. The thickness of these components may vary slightly from the thickness in the finite element model of the vehicle.

[0079] Step S50: Take the minimum total weight of the components as the final target of the target optimization.

[0080] It should be noted that the total base mass of the selected body parts is statistically analyzed, and the minimum total weight of the overall variable parts is set as the final objective of the multidisciplinary multi-objective optimization. However, the base mass of the selected body parts is not the minimum mass that is expected to be achieved.

[0081] Step S60: Construct an approximate simulation model of the target based on the components.

[0082] It should be understood that by treating components as variables, the basic sampling models for various disciplines in CAE are built through parameterization, and a sample model is obtained by combining statistical sampling methods. The sample model is then submitted for calculation, and an approximate model for multi-disciplinary and multi-objective simulation is constructed. The construction of the basic sampling model utilizes component variables for parameterization, and the parameterization method is not limited; the sample model is obtained using statistical sampling methods, and the statistical sampling method itself is not limited.

[0083] Step S70: Construct a target optimization process based on the target value corresponding to the sub-project target and the final target corresponding to the component.

[0084] Step S80: Perform simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result.

[0085] It should be noted that the design and construction of a multidisciplinary, multi-objective optimization process involves performing optimization simulation calculations, balancing the various sub-objectives with the final objective, and finding the optimal solution. The optimization method for the multidisciplinary, multi-objective approach is not limited; different optimization algorithms such as polynomial, Kriging, and RBF can be selected. In the multidisciplinary, multi-objective optimization simulation analysis results, all solution sets should converge.

[0086] Specifically, step S80 includes: performing simulation calculations based on the target simulation approximation model, minimizing the final target and maximizing the target value corresponding to the sub-target, determining the optimal solution of the target optimization process, and obtaining the optimization result.

[0087] In practice, the ultimate goal of multidisciplinary and multi-objective optimization is to achieve a balance between vehicle performance and quality, with optimization of each sub-objective coordinated to minimize quality and maximize vehicle performance.

[0088] Furthermore, a set of solutions that satisfy all sub-objectives and the final objective is selected, and the solution with the lowest quality among the solutions that satisfy the objective is selected as the optimal solution.

[0089] This embodiment constructs a finite element model of the entire vehicle; constrains and loads the finite element model, performs finite element simulation analysis, and selects important indicators that are strongly related to the overall vehicle structure; uses these important indicators as sub-objectives for target optimization and determines the target values ​​corresponding to these sub-objectives; selects components that are strongly related to the overall vehicle performance from the vehicle model; uses the minimum total weight of the components as the final target for target optimization; constructs a target simulation approximation model based on the components; constructs a target optimization process based on the target values ​​corresponding to the sub-objectives and the final target corresponding to the components; performs simulation calculations based on the target simulation approximation model, determines the optimal solution of the target optimization process, and obtains the optimization results. Through the above method, in the optimization stage, performance and quality are considered holistically to optimize performance-deficient items and quality, optimizing both overall vehicle performance and quality while also taking into account design conflicts between different disciplines, thus achieving an optimal balance between overall vehicle performance and quality.

[0090] refer to Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the vehicle performance analysis and optimization method of the present invention.

[0091] Based on the first embodiment described above, the vehicle performance analysis and optimization method of this embodiment further includes, after step S80:

[0092] Step S801: Assign the thickness variable value corresponding to the optimal solution to the variable components in the benchmark analysis model of each discipline dimension to obtain the verification model.

[0093] Step S802: Analyze the verification model to determine the performance target achievement information and quality change information.

[0094] Step S803: Perform a comprehensive evaluation based on the performance target achievement information and the quality change information to obtain a comprehensive evaluation result.

[0095] It should be understood that the thickness variable of the optimal solution is assigned to the variable components in the Base analysis model of each discipline dimension of CAE to obtain the validation model, which is then submitted for verification. The verification results are post-processed and evaluated according to the original target value. The total mass of the overall variable components in the validation model is statistically analyzed and compared with the total mass of the Base analysis model. The difference between the two is determined as the weight reduction or the weight increase required for performance optimization. The achievement of the performance target and the change in mass are comprehensively evaluated to assess whether the overall vehicle performance and mass have reached the optimal balance.

[0096] It should be noted that the standard for passing the verification result is that the difference between the verification result of the model and the multidisciplinary multi-objective optimization result is less than a certain value. Optionally, the performance targets of the sub-items in the verification result are compared and evaluated based on the set minimum target values ​​to be achieved.

[0097] Furthermore, after analyzing the verification model to determine the performance target achievement information and quality change information, the method further includes: if the performance target achievement information does not meet the preset performance requirements and the quality change information does not meet the preset quality requirements, then adjusting the target optimization process; performing simulation calculations according to the target simulation approximation model to determine the optimal solution corresponding to the adjusted target optimization process, and obtaining the adjusted optimization result.

[0098] It should be understood that all performance targets in the verification results are compared with the corresponding Base analysis results to determine whether the verification performance results are better than the Base results. If the verification performance results are better than the Base results, it indicates that the corresponding performance has been optimized; if the verification performance results are worse than the Base results, it indicates that the corresponding performance has been relatively weakened. Then, the corresponding VTS (Vehicle Performance Target) is used for comparison and evaluation to determine whether the degree of weakening is consistent with the original Base result level or meets the VTS performance target requirements. If the degree of weakening is consistent with the original Base result level or still meets the target requirements, the optimization scheme is fully accepted; if the degree of weakening differs significantly, or does not meet the target requirements, or the quality change does not meet the quality requirements, the target optimization process is partially modified. Since the variables set in this embodiment are not all components of the vehicle, the verification results, except for the performance items as sub-targets, may fluctuate slightly compared to the Base analysis results, but this does not affect the overall performance. The performance compliance situations described above can all be used to evaluate that the overall performance and quality of this vehicle have reached an optimal balance.

[0099] It should be noted that if there are no unmet targets or only a few unmet targets in a sub-project, the optimized quality will be lower than the base quality, which is considered forward lightweight development and indicates that the overall vehicle performance and quality have achieved an optimal balance. If there are multiple unmet targets in a sub-project, the optimized quality will be higher than the base quality, which is also considered reverse development and indicates that the overall vehicle performance and quality have achieved an optimal balance.

[0100] This embodiment constructs a whole vehicle finite element model; constrains and loads the whole vehicle finite element model, performs finite element simulation analysis, and selects important indicators that are strongly related to the overall vehicle structure; uses these important indicators as sub-objectives for target optimization and determines the target values ​​corresponding to the sub-objectives; selects components that are strongly related to the overall vehicle performance from the whole vehicle model; uses the minimum total weight of the components as the final target for target optimization; constructs a target simulation approximation model based on the components; constructs a target optimization process based on the target values ​​corresponding to the sub-objectives and the final targets corresponding to the components; performs simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization results; assigns thickness variable values ​​corresponding to the optimal solutions to the variable components in the benchmark analysis models of each discipline dimension, obtaining a verification model; analyzes based on the verification model to determine performance target achievement information and quality change information; and performs a comprehensive evaluation based on the performance target achievement information and quality change information to obtain a comprehensive evaluation result. Through the above methods, in the optimization phase, performance and quality are considered holistically to optimize performance-deficient items and quality. While optimizing the overall vehicle performance and quality, the design contradictions between various disciplines are also taken into account, so that the overall vehicle performance and quality achieve the optimal balance. A verification and evaluation method is provided to monitor the optimization effect in the optimization phase and provide data support for the optimization process adjustment.

[0101] Furthermore, this embodiment of the invention also proposes a storage medium storing a vehicle performance analysis and optimization program, which, when executed by a processor, implements the vehicle performance analysis and optimization method described above.

[0102] 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.

[0103] Reference Figure 4 , Figure 4 This is a structural block diagram of the first embodiment of the vehicle performance analysis and optimization device of the present invention.

[0104] like Figure 4 As shown, the vehicle performance analysis and optimization device proposed in this embodiment of the invention includes:

[0105] Module 10 is used to build the finite element model of the whole vehicle.

[0106] The finite element simulation analysis module 20 is used to constrain and load the whole vehicle finite element model, and perform finite element simulation analysis to screen out important indicators that are strongly related to the overall structure of the vehicle body.

[0107] The optimization item determination module 30 is used to take the important indicator items as sub-objectives for target optimization and determine the target values ​​corresponding to the sub-objectives.

[0108] The filtering module 40 is used to filter out components that are strongly related to the performance of the whole vehicle from the whole vehicle model.

[0109] The optimization term determination module 30 is also used to take the minimum total weight of the components as the final target of the target optimization.

[0110] The approximate model construction module 50 is used to construct a target simulation approximate model based on the components.

[0111] The optimization item determination module 30 is also used to construct a target optimization process based on the target value corresponding to the sub-item target and the final target corresponding to the component.

[0112] The optimization module 60 is used to perform simulation calculations based on the target simulation approximation model, determine the optimal solution of the target optimization process, and obtain the optimization result.

[0113] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0114] This embodiment constructs a finite element model of the entire vehicle; constrains and loads the finite element model, performs finite element simulation analysis, and selects important indicators that are strongly related to the overall vehicle structure; uses these important indicators as sub-objectives for target optimization and determines the target values ​​corresponding to these sub-objectives; selects components that are strongly related to the overall vehicle performance from the vehicle model; uses the minimum total weight of the components as the final target for target optimization; constructs a target simulation approximation model based on the components; constructs a target optimization process based on the target values ​​corresponding to the sub-objectives and the final target corresponding to the components; performs simulation calculations based on the target simulation approximation model, determines the optimal solution of the target optimization process, and obtains the optimization results. Through the above method, in the optimization stage, performance and quality are considered holistically to optimize performance-deficient items and quality, optimizing both overall vehicle performance and quality while also taking into account design conflicts between different disciplines, thus achieving an optimal balance between overall vehicle performance and quality.

[0115] 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.

[0116] In addition, for technical details not described in detail in this embodiment, please refer to the vehicle performance analysis and optimization method provided in any embodiment of the present invention, which will not be repeated here.

[0117] In one embodiment, the finite element simulation analysis module 20 is further used to constrain and load the whole vehicle finite element model, and perform finite element simulation analysis to obtain simulation analysis results; to post-process the simulation analysis results to obtain benchmark analysis results; and to perform a preliminary evaluation based on the benchmark analysis results and the corresponding whole vehicle technical specifications, and to select important indicators that are strongly related to the overall structure of the vehicle body from various performance indicators.

[0118] In one embodiment, the benchmark analysis results include safety collision benchmark analysis results, NVH benchmark analysis results, structural stiffness benchmark analysis results, structural strength benchmark analysis results, and fatigue durability benchmark analysis results;

[0119] The finite element simulation analysis module 20 is further used to determine the performance items to be examined by the preset target decomposition and the examination points corresponding to the performance items; extract the intrusion amount and acceleration corresponding to the examination points; record the intrusion amount and acceleration corresponding to the examination points as safety collision benchmark analysis results; generate dynamic stiffness response point acceleration curves and convert them into dynamic stiffness values; read the X-direction displacement of the NTF response point and convert it into noise values; generate VTF response point acceleration curves and read the peak values ​​of the curves; record the dynamic stiffness values, the noise values, and the peak values ​​of the curves as NVH benchmark analysis results; read the Z-direction displacement corresponding to each examination point; calculate the corresponding stiffness value based on the Z-direction displacement; record the stiffness value as structural stiffness benchmark analysis results; read the maximum stress value of each component according to the preset yield strength corresponding to each component; record the maximum stress value corresponding to each component as structural strength benchmark analysis results; read the damage value of the connection position where the damage value is greater than a preset threshold; record the damage value of the connection position as fatigue durability benchmark analysis results.

[0120] In one embodiment, the finite element simulation analysis module 20 is further configured to perform a preliminary evaluation based on the benchmark analysis results and the corresponding vehicle technical specifications, determine the qualified items and the unqualified items, and use the qualified items and the unqualified items as initial important indicators; exclude the indicators related to the preset vehicle fatigue durability dimension and the preset vehicle strength from the initial important indicators to obtain important indicators that are strongly related to the overall vehicle structure.

[0121] In one embodiment, the optimization module 60 is further configured to perform simulation calculations based on the target simulation approximation model, minimize the final target and maximize the target value corresponding to the sub-target, determine the optimal solution of the target optimization process, and obtain the optimization result.

[0122] In one embodiment, the vehicle performance analysis and optimization device further includes a verification module;

[0123] The verification module is used to assign thickness variable values ​​corresponding to the optimal solution to the variable components in the benchmark analysis model of each discipline dimension, thereby obtaining a verification model; to perform analysis based on the verification model to determine performance target achievement information and quality change information; and to conduct a comprehensive evaluation based on the performance target achievement information and the quality change information to obtain a comprehensive evaluation result.

[0124] In one embodiment, the verification module is further configured to adjust the target optimization process if the performance target achievement information does not meet the preset performance requirements and the quality change information does not meet the preset quality requirements; perform simulation calculations based on the target simulation approximation model to determine the optimal solution corresponding to the adjusted target optimization process, and obtain the adjusted optimization result.

[0125] 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.

[0126] 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.

[0127] 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, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0128] 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 vehicle performance analysis optimization method, characterized by, The vehicle performance analysis and optimization method includes: Construct a finite element model of the whole vehicle. The constructed finite element model of the whole vehicle is a loadable and computationally achievable model with assigned material thickness and completed connection relationships. The finite element model of the whole vehicle is subjected to constraint loading, and finite element simulation analysis is performed to screen out important indicators that are strongly related to the overall structure of the vehicle body; The aforementioned key indicators are used as sub-objectives for target optimization, and the target values ​​corresponding to the sub-objectives are determined. Select components that are highly relevant to the overall vehicle performance from the vehicle model; The minimum total weight of the components is taken as the final target for optimization; A target simulation approximation model is constructed based on the aforementioned components; A target optimization process is constructed based on the target values ​​corresponding to the sub-project targets and the final targets corresponding to the components. Simulation calculations are performed based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization results; The constraints are applied to the finite element model of the entire vehicle, and finite element simulation analysis is performed to screen out important indicators that are strongly correlated with the overall structure of the vehicle body, including: The finite element model of the whole vehicle is subjected to constraint loading, and finite element simulation analysis is performed to obtain the simulation analysis results; The simulation analysis results are post-processed to obtain the benchmark analysis results; Based on the benchmark analysis results and the corresponding vehicle technical specifications, a preliminary evaluation is conducted, and key performance indicators that are strongly correlated with the overall vehicle structure are selected from various performance indicators. The preliminary evaluation is conducted based on the benchmark analysis results and the corresponding vehicle technical specifications. Key performance indicators with strong correlation to the overall vehicle structure are selected from various performance indicators, including: Based on the benchmark analysis results and the corresponding vehicle technical specifications, a preliminary evaluation is conducted to determine the compliant and non-compliant items, and the compliant and non-compliant items are used as initial key indicators. By excluding the preset vehicle fatigue durability dimension and preset vehicle strength related indicators from the initial important indicators, important indicators with strong correlation to the overall vehicle structure are obtained.

2. The vehicle performance analysis optimization method of claim 1, wherein, The benchmark analysis results include safety collision benchmark analysis results, NVH benchmark analysis results, structural stiffness benchmark analysis results, structural strength benchmark analysis results, and fatigue durability benchmark analysis results; The post-processing of the simulation analysis results to obtain the benchmark analysis results includes: Determine the performance items to be examined for the preset target decomposition and the examination points corresponding to the performance items, extract the intrusion amount and acceleration corresponding to the examination points, and record the intrusion amount and acceleration corresponding to the examination points as the safety collision benchmark analysis results; Create dynamic stiffness response point acceleration curves and convert them into dynamic stiffness values; read the X-direction displacement of NTF response points and convert it into noise values; create VTF response point acceleration curves and read the peak values ​​of the curves; record the dynamic stiffness values, the noise values, and the peak values ​​of the curves as NVH benchmark analysis results. Read the Z-direction displacement corresponding to each of the aforementioned examination points, calculate the corresponding stiffness value based on the Z-direction displacement, and record the stiffness value as the structural stiffness benchmark analysis result; The maximum stress value of each component is read according to the preset yield strength of each component, and the maximum stress value of each component is recorded as the structural strength benchmark analysis result. Read the damage value of the connection location that is greater than a preset threshold, and record the damage value of the connection location as the fatigue durability benchmark analysis result.

3. The method of claim 1, wherein the vehicle performance analysis optimization method is characterized by, The step of performing simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result includes: Simulation calculations are performed based on the target simulation approximation model to minimize the final target and maximize the target values ​​corresponding to the sub-targets, thereby determining the optimal solution of the target optimization process and obtaining the optimization results.

4. The method of claim 1, wherein the vehicle performance analysis optimization method is characterized by, After performing simulation calculations based on the target simulation approximation model to determine the optimal solution of the target optimization process and obtain the optimization result, the method further includes: Assign the thickness variable value corresponding to the optimal solution to the variable components in the benchmark analysis model of each discipline dimension to obtain the verification model; Based on the verification model, analysis is performed to determine performance target achievement information and quality change information; A comprehensive evaluation is conducted based on the performance target achievement information and the quality change information to obtain a comprehensive evaluation result.

5. The vehicle performance analysis and optimization method as described in claim 4, characterized in that, After analyzing the verification model to determine the performance target achievement information and quality change information, the method further includes: If the performance target achievement information does not meet the preset performance requirements, and the quality change information does not meet the preset quality requirements, then the target optimization process is adjusted. Simulation calculations are performed based on the target simulation approximation model to determine the optimal solution corresponding to the adjusted target optimization process, and the adjusted optimization result is obtained.

6. A vehicle performance analysis and optimization device, characterized in that, The vehicle performance analysis and optimization device includes: The construction module is used to build a whole vehicle finite element model. The built whole vehicle finite element model is a loadable and compute-ready model with material thickness already assigned and the necessary connection relationships completed. The finite element simulation analysis module is used to constrain and load the whole vehicle finite element model, perform finite element simulation analysis, and screen out important indicators that are strongly related to the overall structure of the vehicle body. The optimization item determination module is used to take the important indicator items as sub-objectives for target optimization and determine the target values ​​corresponding to the sub-objectives; The filtering module is used to filter out components that are highly relevant to the overall vehicle performance from the vehicle model; The optimization term determination module is further configured to take the minimum total weight of the components as the final target of the optimization. An approximate model construction module is used to construct an approximate model of the target simulation based on the components; The optimization item determination module is also used to construct a target optimization process based on the target value corresponding to the sub-item target and the final target corresponding to the component; The optimization module is used to perform simulation calculations based on the target simulation approximation model, determine the optimal solution of the target optimization process, and obtain the optimization result; The finite element simulation analysis module is also used to constrain and load the whole vehicle finite element model, and perform finite element simulation analysis to obtain simulation analysis results; to post-process the simulation analysis results to obtain benchmark analysis results; and to conduct a preliminary evaluation based on the benchmark analysis results and the corresponding whole vehicle technical specifications, and to select important indicators that are strongly related to the overall structure of the vehicle body from various performance indicators. The finite element simulation analysis module is also used to perform a preliminary evaluation based on the benchmark analysis results and the corresponding vehicle technical specifications, determine the qualified and unqualified items, and use the qualified and unqualified items as initial important indicators; exclude the indicators related to the preset vehicle fatigue durability dimension and preset vehicle strength from the initial important indicators to obtain important indicators that are strongly related to the overall vehicle structure.

7. A vehicle performance analysis and optimization device, characterized in that, The device includes: a memory, a processor, and a vehicle performance analysis and optimization program stored in the memory and executable on the processor, the vehicle performance analysis and optimization program being configured to implement the vehicle performance analysis and optimization method as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, The storage medium stores a vehicle performance analysis and optimization program, which, when executed by a processor, implements the vehicle performance analysis and optimization method as described in any one of claims 1 to 5.

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