CN111581730A - Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform - Google Patents
Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform Download PDFInfo
- Publication number
- CN111581730A CN111581730A CN202010417186.6A CN202010417186A CN111581730A CN 111581730 A CN111581730 A CN 111581730A CN 202010417186 A CN202010417186 A CN 202010417186A CN 111581730 A CN111581730 A CN 111581730A
- Authority
- CN
- China
- Prior art keywords
- analysis
- frame
- design
- model
- constraining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000005457 optimization Methods 0.000 title claims abstract description 29
- 230000010354 integration Effects 0.000 title claims abstract description 9
- 238000004458 analytical method Methods 0.000 claims abstract description 55
- 238000013461 design Methods 0.000 claims abstract description 35
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 11
- 238000005516 engineering process Methods 0.000 claims abstract description 11
- 238000005452 bending Methods 0.000 claims abstract description 10
- 238000013401 experimental design Methods 0.000 claims abstract description 8
- 230000003068 static effect Effects 0.000 claims description 6
- 230000009191 jumping Effects 0.000 claims description 4
- 238000005316 response function Methods 0.000 claims description 4
- 230000035945 sensitivity Effects 0.000 claims description 4
- 230000002068 genetic effect Effects 0.000 claims description 3
- 238000013433 optimization analysis Methods 0.000 claims description 3
- 238000010206 sensitivity analysis Methods 0.000 claims description 2
- 238000012356 Product development Methods 0.000 abstract description 3
- 230000004044 response Effects 0.000 abstract description 3
- 238000004364 calculation method Methods 0.000 description 7
- 238000011161 development Methods 0.000 description 6
- 238000011160 research Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Automation & Control Theory (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Body Structure For Vehicles (AREA)
Abstract
The invention relates to the technical field of Computer Aided Engineering (CAE) technology and finite element method, in particular to an automobile frame multidisciplinary optimization method based on a Hyperstudy integration platform, which determines that fatigue analysis, bending rigidity analysis, torsional rigidity analysis, strength analysis and fatigue analysis are carried out on an automobile frame based on the CAE technology and the finite element method, the main section size and the plate thickness of the automobile frame are taken as design variables, modal frequency value, rigidity value and maximum principal stress are taken as constraint responses, and the whole automobile frame quality is taken as a target for corresponding. The optimal Latin hypercube method is adopted to carry out experimental design on each design variable based on the Hyperstudy integration platform, an approximate model is established, then a multidisciplinary optimization algorithm is adopted to optimize the main section size and the plate thickness of the frame, and finally optimal design parameters are obtained, so that a reliable analysis method is provided for the comprehensive performance and the light weight design of the frame, and the product development efficiency is effectively improved.
Description
Technical Field
The invention relates to the technical field of Computer Aided Engineering (CAE) technology and finite element method, in particular to a multidisciplinary optimization method of an automobile frame based on a Hyperstudy integration platform.
Background
Among the factors that improve the research and development ability of automobiles, Computer Aided Engineering (CAE) is the most important technical means in the development process of digital products. With the development of computer technology and the continuous development and perfection of technologies such as numerical analysis theory, optimization design and the like, a more advanced, accurate and efficient method appears in the design of a frame system, and the design enters a multi-disciplinary field which takes a CAE technology as a tool and takes static and dynamic analysis, modal and response analysis, fatigue analysis and structure optimization design of finite element rigidity and strength as main contents from the past experience, analogy, static analysis and the like.
As the automobile frame system is more and more complex, the interaction of various performances required by the automobile frame system is more and more obvious, and the design of the frame system relates to the field of multidisciplinary, so that the overall design process of the frame system is very complex. In order to excavate the design potential and improve the design quality, the multidisciplinary optimization technology is introduced into the frame design by taking the design as a starting point, the comprehensive optimization design theory and method of the frame complex system are analyzed and researched, and the comprehensive optimization design theory and method are effectively applied to the actual engineering. The method has important academic value and wide application prospect for the design of the frame system.
However, how to select design variables, analysis methods and technical routes is always a difficult problem which puzzles technicians, limits multidisciplinary optimization research of the automobile frame to a certain extent, and after single performance and requirements are met, whether other various performances of the automobile frame can meet the design requirements or not, and which parts still have potential optimization spaces are also problems which need to be considered by the designers. Moreover, in the current research on the performance of the automobile frame, a single subject (an investigation target) analysis method is usually adopted, and all subjects are mutually connected and influenced, so that the analysis by the single subject analysis method is incomplete, and an optimal scheme cannot be found among the performances on the basis of meeting multiple subjects and multiple targets.
Based on the situation, the invention provides a multidisciplinary optimization method applied to a frame system. The method comprehensively considers each performance index required to be met by the frame system by utilizing a multidisciplinary optimization principle, and finally realizes multidisciplinary optimization of the frame system through an established optimization program and a determined calculation scheme, thereby achieving the purpose of meeting individual performance requirements.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides an automobile frame multidisciplinary optimization method based on a Hyperstudy integration platform, determines fatigue analysis, bending rigidity analysis, torsional rigidity analysis, strength analysis and fatigue analysis of an automobile frame based on a CAE technology and a finite element method, takes the main section size and the plate thickness of the automobile frame as design variables, takes modal frequency values, rigidity values and maximum main stress as constraint response, and takes the mass of the whole automobile frame as a target for corresponding. The optimal Latin hypercube method is adopted to carry out experimental design on each design variable based on the Hyperstudy integration platform, an approximate model is established, then a multidisciplinary optimization algorithm is adopted to optimize the main section size and the plate thickness of the frame, and finally optimal design parameters are obtained, so that a reliable analysis method is provided for the comprehensive performance and the light weight design of the frame, and the product development efficiency is effectively improved.
In order to realize the purpose of the invention, the technical scheme adopted by the invention is as follows:
s1, establishing an automobile frame finite element model for optimization analysis based on a CAE technology and a finite element method, and finishing the definition of a shape variable and a size variable on the basis of the frame finite element model;
s2, performing basic performance analysis on the finite element model of the frame, wherein the basic performance analysis comprises modal analysis, torsional rigidity analysis, bending rigidity analysis, strength analysis and fatigue analysis:
s2.1, performing modal analysis on the frame by adopting a Lanzcos method and setting a frequency range to be 0-100 Hz;
s2.2, constraining the degree of freedom 123 at the midpoint position of the left leaf spring at the rear side, constraining the degree of freedom 13 at the midpoint position of the right leaf spring at the rear side, constraining the degree of freedom in the direction of the midpoint position 3 of the first cross beam at the front end, and applying two counter forces in opposite directions at the midpoints of the left leaf spring and the right leaf spring at the front end so as to analyze the torsional rigidity of the frame and obtain the torsional rigidity value of the frame;
s2.3, constraining the degree of freedom 123 at the middle point position of the left-side plate spring at the rear part, constraining the degree of freedom 13 at the middle point position of the right-side plate spring at the rear part, constraining the degree of freedom 23 at the middle point position of the left-side plate spring at the front end, constraining the degree of freedom 3 at the middle point position of the right-side plate spring at the front end, and applying forces in the same direction at the left and right sides of the middle part of the frame so as to analyze the bending rigidity of the frame and obtain the;
s2.4, extracting the ultimate static strength load based on the established multi-physical model, calculating by adopting an inertia release method, wherein the model is free of constraint and is calculated according to eight working conditions: the maximum main stress of the eight working condition frames is respectively obtained by static state, downward jumping, upward jumping, turning braking, turning, twisting, front braking and rear braking;
s2.5, calculating the fatigue working condition by using radio software;
s3, setting a modal frequency value, a bending stiffness value, a torsion stiffness value, a maximum main stress and a fatigue life value under a strength working condition as response functions, and carrying out sensitivity analysis on the main section size and the plate thickness of the frame by adopting a Hammersley method;
s4, eliminating design variables with low sensitivity, and carrying out experimental design on each design variable by adopting an optimal Latin hypercube method to obtain Latin hypercube experimental design sample distribution;
s5, establishing a Radial Basis Function (RBF) model according to the sample distribution data, evaluating the precision of the RBF model and the RBF model, and constructing an approximate model meeting the precision requirement;
and S6, optimizing the main section size and the plate thickness of the frame by the approximate model respectively by adopting a Sequence Quadratic Programming (SQP) algorithm and a multi-objective genetic algorithm in a multidisciplinary optimization algorithm to obtain optimal design parameters.
The invention has the beneficial effects that:
1. the invention provides a reliable analysis method for the comprehensive performance and the light weight design of the frame, effectively improves the product development efficiency, reduces the development cost, shortens the development period and has very important guiding significance for the optimization application and the light weight in the automobile development.
Drawings
FIG. 1 is a multidisciplinary optimization scheme of the present invention;
FIG. 2 is a flow chart of the frame optimization of the present invention;
FIG. 3 is a finite element model of a vehicle frame according to the present invention.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings
See fig. 1-3.
The invention discloses a multidisciplinary optimization method of an automobile frame based on a Hyperstudy integration platform, which comprises the following steps:
s1, establishing an automobile frame finite element model for optimization analysis based on a CAE technology and a finite element method, and finishing the definition of a shape variable and a size variable on the basis of the frame finite element model; finite element modeling is carried out on the automobile frame by adopting finite element software optistruct, dimension variable setting is carried out on the thickness dimension of the frame by utilizing a gauge module, and forming variable setting is carried out on the main section and the shape of the frame by utilizing a morph module;
s2, performing basic performance analysis on the finite element model of the frame, wherein the basic performance analysis comprises modal analysis, torsional rigidity analysis, bending rigidity analysis, strength analysis and fatigue analysis; loading a simulation analysis load, outputting a calculation file of modal analysis, loading a strength analysis load, outputting a strength analysis calculation file, loading a rigidity analysis load, outputting a rigidity calculation file, loading a fatigue analysis load, and outputting a fatigue calculation file; setting the calculation files in the Hyperterm as corresponding analysis files, tpl files and four tpl files into the Hyperterm, and calculating each previously defined analysis working condition;
s3, setting a modal frequency value, a bending stiffness value, a torsion stiffness value and a maximum principal stress and fatigue life value under the strength working condition as response functions, and performing DOE analysis on size and shape design variables by adopting a Hammersley method;
s4, according to the analysis result of the DOE, the sensitivity of each design variable to the response function is checked, the design variable with low sensitivity is eliminated, the optimization model is simplified, and the optimization efficiency is improved;
s5, carrying out experimental design on each design variable by using an optimal Latin hypercube method to obtain Latin hypercube experimental design sample distribution;
s6, establishing a Radial Basis Function (RBF) model according to the obtained sample distribution data, and evaluating the precision of the RBF model;
s7, respectively adopting a Sequence Quadratic Programming (SQP) algorithm and a multi-objective genetic algorithm in a multidisciplinary optimization algorithm based on the established approximate model to perform multidisciplinary optimization on each design variable, wherein the minimum mass can be used as a target function according to the actual application condition, each performance of the frame can be optimized as a constraint function, some performance parameters can be used as the target function, the rest performance parameters are used as the constraint functions to perform optimization, the optimal design variable is obtained, and finally, the optimal solution is verified through simulation calculation again.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent modifications made by the present invention and the contents of the drawings or directly or indirectly applied to the related technical fields are included in the scope of the present invention.
Claims (1)
1. A multidisciplinary optimization method for an automobile frame based on a Hyperstudy integration platform is characterized by comprising the following steps:
s1, establishing an automobile frame finite element model for optimization analysis based on a CAE technology and a finite element method, and finishing the definition of a shape variable and a size variable on the basis of the frame finite element model;
s2, performing basic performance analysis on the finite element model of the frame, wherein the basic performance analysis comprises modal analysis, torsional rigidity analysis, bending rigidity analysis, strength analysis and fatigue analysis:
s2.1, performing modal analysis on the frame by adopting a Lanzcos method and setting a frequency range to be 0-100 Hz;
s2.2, constraining the degree of freedom 123 at the midpoint position of the left leaf spring at the rear side, constraining the degree of freedom 13 at the midpoint position of the right leaf spring at the rear side, constraining the degree of freedom in the direction of the midpoint position 3 of the first cross beam at the front end, and applying two counter forces in opposite directions at the midpoints of the left leaf spring and the right leaf spring at the front end so as to analyze the torsional rigidity of the frame and obtain the torsional rigidity value of the frame;
s2.3, constraining the degree of freedom 123 at the middle point position of the left-side plate spring at the rear part, constraining the degree of freedom 13 at the middle point position of the right-side plate spring at the rear part, constraining the degree of freedom 23 at the middle point position of the left-side plate spring at the front end, constraining the degree of freedom 3 at the middle point position of the right-side plate spring at the front end, and applying forces in the same direction at the left and right sides of the middle part of the frame so as to analyze the bending rigidity of the frame and obtain the;
s2.4, extracting the ultimate static strength load based on the established multi-physical model, calculating by adopting an inertia release method, wherein the model is free of constraint and is calculated according to eight working conditions: the maximum main stress of the eight working condition frames is respectively obtained by static state, downward jumping, upward jumping, turning braking, turning, twisting, front braking and rear braking;
s2.5, calculating the fatigue working condition by using radio software;
s3, setting a modal frequency value, a bending stiffness value, a torsion stiffness value, a maximum main stress and a fatigue life value under a strength working condition as response functions, and carrying out sensitivity analysis on the main section size and the plate thickness of the frame by adopting a Hammersley method;
s4, eliminating design variables with low sensitivity, and carrying out experimental design on each design variable by adopting an optimal Latin hypercube method to obtain Latin hypercube experimental design sample distribution;
s5, establishing a Radial Basis Function (RBF) model according to the sample distribution data, evaluating the precision of the RBF model and the RBF model, and constructing an approximate model meeting the precision requirement;
and S6, optimizing the main section size and the plate thickness of the frame by the approximate model respectively by adopting a Sequence Quadratic Programming (SQP) algorithm and a multi-objective genetic algorithm in a multidisciplinary optimization algorithm to obtain optimal design parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010417186.6A CN111581730A (en) | 2020-05-18 | 2020-05-18 | Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010417186.6A CN111581730A (en) | 2020-05-18 | 2020-05-18 | Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111581730A true CN111581730A (en) | 2020-08-25 |
Family
ID=72110911
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010417186.6A Pending CN111581730A (en) | 2020-05-18 | 2020-05-18 | Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111581730A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112069599A (en) * | 2020-08-28 | 2020-12-11 | 北京科技大学 | Reliability prediction method for running performance of tracked vehicle |
| CN112257189A (en) * | 2020-11-12 | 2021-01-22 | 湖北汽车工业学院 | Light-weight multi-disciplinary optimization method for passenger car framework |
| CN112380622A (en) * | 2020-11-13 | 2021-02-19 | 西藏宁算科技集团有限公司 | Vehicle body lightweight parameter optimization method based on cloud computing technology |
| CN112464412A (en) * | 2020-12-07 | 2021-03-09 | 上海无线电设备研究所 | Method for designing arc-shaped anti-backlash torsion spring of servo mechanism |
| CN113239581A (en) * | 2021-04-02 | 2021-08-10 | 陕西同力重工股份有限公司 | Method for analyzing strength of frame of off-highway dump truck |
| CN113312827A (en) * | 2021-06-30 | 2021-08-27 | 湖北汽车工业学院 | Multi-objective optimization method for automobile framework |
| CN113591219A (en) * | 2021-07-29 | 2021-11-02 | 重庆长安汽车股份有限公司 | Multi-working-condition CAE transient fatigue analysis loading method for whole vehicle |
| CN114741936A (en) * | 2022-05-23 | 2022-07-12 | 一汽解放汽车有限公司 | Frame rigidity optimization method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102449623A (en) * | 2009-03-31 | 2012-05-09 | 东京毅力科创株式会社 | Method and system for detection of tool performance degradation and mismatch |
| CN106919767A (en) * | 2017-03-09 | 2017-07-04 | 江铃汽车股份有限公司 | Automobile body-in-white lightweight analysis method |
| CN109063389A (en) * | 2018-09-28 | 2018-12-21 | 重庆长安汽车股份有限公司 | A kind of vehicle structure lightweight forward design method and system based on more performance constraints |
| CN109829257A (en) * | 2019-03-25 | 2019-05-31 | 江铃汽车股份有限公司 | Automobile frame lightweight optimization method |
-
2020
- 2020-05-18 CN CN202010417186.6A patent/CN111581730A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102449623A (en) * | 2009-03-31 | 2012-05-09 | 东京毅力科创株式会社 | Method and system for detection of tool performance degradation and mismatch |
| CN106919767A (en) * | 2017-03-09 | 2017-07-04 | 江铃汽车股份有限公司 | Automobile body-in-white lightweight analysis method |
| CN109063389A (en) * | 2018-09-28 | 2018-12-21 | 重庆长安汽车股份有限公司 | A kind of vehicle structure lightweight forward design method and system based on more performance constraints |
| CN109829257A (en) * | 2019-03-25 | 2019-05-31 | 江铃汽车股份有限公司 | Automobile frame lightweight optimization method |
Non-Patent Citations (2)
| Title |
|---|
| CHARLES MORTISHED 等: "Multidisciplinary Optimisation of an Automotive Body-in-White Structure Using Crushable Frame Springs and Sub Space Metamodels in Trust-Regions", 《ADVANCES IN STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION》 * |
| 吴杨 等: "基于isight响应面模型的白车身轻量化研究", 《北京汽车》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112069599A (en) * | 2020-08-28 | 2020-12-11 | 北京科技大学 | Reliability prediction method for running performance of tracked vehicle |
| CN112069599B (en) * | 2020-08-28 | 2023-08-22 | 北京科技大学 | Method for predicting reliability of running performance of tracked vehicle |
| CN112257189A (en) * | 2020-11-12 | 2021-01-22 | 湖北汽车工业学院 | Light-weight multi-disciplinary optimization method for passenger car framework |
| CN112257189B (en) * | 2020-11-12 | 2023-12-15 | 湖北汽车工业学院 | Multidisciplinary optimization method for light weight of passenger car framework |
| CN112380622A (en) * | 2020-11-13 | 2021-02-19 | 西藏宁算科技集团有限公司 | Vehicle body lightweight parameter optimization method based on cloud computing technology |
| CN112464412A (en) * | 2020-12-07 | 2021-03-09 | 上海无线电设备研究所 | Method for designing arc-shaped anti-backlash torsion spring of servo mechanism |
| CN113239581A (en) * | 2021-04-02 | 2021-08-10 | 陕西同力重工股份有限公司 | Method for analyzing strength of frame of off-highway dump truck |
| CN113312827A (en) * | 2021-06-30 | 2021-08-27 | 湖北汽车工业学院 | Multi-objective optimization method for automobile framework |
| CN113591219A (en) * | 2021-07-29 | 2021-11-02 | 重庆长安汽车股份有限公司 | Multi-working-condition CAE transient fatigue analysis loading method for whole vehicle |
| CN114741936A (en) * | 2022-05-23 | 2022-07-12 | 一汽解放汽车有限公司 | Frame rigidity optimization method |
| CN114741936B (en) * | 2022-05-23 | 2024-05-14 | 一汽解放汽车有限公司 | Frame rigidity optimization method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111581730A (en) | Automobile frame multidisciplinary optimization method based on Hyperstudy integration platform | |
| Donders et al. | A reduced beam and joint concept modeling approach to optimize global vehicle body dynamics | |
| CN113408055B (en) | Automobile frame structure optimization method | |
| US7788070B2 (en) | Product design optimization method and system | |
| US7877239B2 (en) | Symmetric random scatter process for probabilistic modeling system for product design | |
| CN106991216B (en) | Robustness estimation and optimization method for steering wheel shake caused by automobile cooling module | |
| CN111125946B (en) | Method for optimizing structure of boarding body based on MDO technology | |
| Aulig et al. | Preference-based topology optimization for vehicle concept design with concurrent static and crash load cases | |
| CN110414052A (en) | A kind of vehicle structure fatigue life calculation method composed based on digital sample car and virtual road | |
| Mihaylova et al. | Beam bounding box–a novel approach for beam concept modeling and optimization handling | |
| Abdullah et al. | Computational modal analysis on finite element model of body-in-white structure and its correlation with experimental data | |
| Geren et al. | Automated sizing of automotive steering ball joints in parametric CAD environment using expert knowledge and feature-based computer-assisted 3D modelling | |
| CN116049989A (en) | Bogie digital twin model construction method, system, electronic equipment and medium | |
| CN112395685B (en) | Topology optimization bicycle component design method suitable for additive manufacturing | |
| Ramnath et al. | Load Case Preference Patterns based on Parameterized Pareto-Optimal Vehicle Design Concept Optimization | |
| Moroncini et al. | NVH structural optimization using beams and shells FE concept models in the early car development phase at BMW | |
| Taksande et al. | Design, modeling and failure analysis of car front suspension lower arm | |
| US20230169232A1 (en) | Optimization analysis method and device for joining locations of automotive body | |
| Bylund | Simulation driven product development applied to car body design | |
| Łukaszewicz | Testing virtual prototype of a new product in two simulation environments | |
| Chang et al. | A Multilevel Product Model for Simulation-Based Design of Mechanical Systems | |
| Wang et al. | An improved system for efficient shape optimization of vehicle aerodynamics with “noisy” computations | |
| Gurumoorthy et al. | Automotive Wheel Metamodeling Using Response Surface Methodology (RSM) Technique | |
| CN114065387A (en) | Frame optimization method and device, computer equipment and storage medium | |
| Ensor et al. | Optimising simulation and test techniques for efficient vehicle durability design and development |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200825 |
|
| RJ01 | Rejection of invention patent application after publication |