CN113127978A - Optimization method for light weight of instrument board beam - Google Patents

Optimization method for light weight of instrument board beam Download PDF

Info

Publication number
CN113127978A
CN113127978A CN202110467902.6A CN202110467902A CN113127978A CN 113127978 A CN113127978 A CN 113127978A CN 202110467902 A CN202110467902 A CN 202110467902A CN 113127978 A CN113127978 A CN 113127978A
Authority
CN
China
Prior art keywords
instrument panel
thickness
instrument
instrument board
individual
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.)
Granted
Application number
CN202110467902.6A
Other languages
Chinese (zh)
Other versions
CN113127978B (en
Inventor
瞿元
胡广地
周红梅
李国超
郭熙
刘雷
杨梅
秦玉林
柯俊
朱杰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chery Automobile Co Ltd
Original Assignee
Chery Automobile Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Chery Automobile Co Ltd filed Critical Chery Automobile Co Ltd
Priority to CN202110467902.6A priority Critical patent/CN113127978B/en
Publication of CN113127978A publication Critical patent/CN113127978A/en
Application granted granted Critical
Publication of CN113127978B publication Critical patent/CN113127978B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/10Geometric CAD
    • G06F30/15Vehicle, aircraft or watercraft design
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • G06F30/27Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14Force 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)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computational Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Instrument Panels (AREA)

Abstract

The invention relates to the technical field of automobile weight optimization, and provides an optimization method for the lightweight of an instrument board beam, which comprises the following steps: s1, constructing a fitness function based on the target function and the constraint condition, taking the minimum mass of the instrument panel beam as the target function, and taking the modal analysis and the rigidity analysis of the instrument panel beam as the constraint condition; s2, carrying out gene coding on the thickness of each part of the instrument board beam, and determining the mapping relation between the individual gene and the thickness of each part of the instrument board beam; s3, obtaining the individual genes with the optimal fitness value through a genetic algorithm, namely the optimal values of the thicknesses of the parts of the instrument board beam. By utilizing the very strong global optimization capability of the genetic algorithm, the constraint conditions required to be met during the lightweight design of the instrument panel beam are comprehensively considered, and the optimal size design scheme is sought under various constraint conditions, so that the maximized weight reduction requirement of the instrument panel beam is met, and the more effective lightweight design of the instrument panel beam is realized.

Description

Optimization method for light weight of instrument board beam
Technical Field
The invention relates to the technical field of instrument beam weight optimization, and provides a method for optimizing the weight of an instrument board beam.
Background
The new energy automobile has become one of the important directions of automobile development in China due to the characteristics of low carbon, environmental protection and energy conservation. In order to improve the endurance mileage of a new energy automobile, the new energy automobile generally has a large overall mass. The dashboard cross member is a very important part in the automobile structure, is responsible for important subsystems such as a dashboard assembly, an air conditioning system, a steering system, an airbag and the like, and provides a mounting interface for a plurality of electronic modules related to control. The design quality of the instrument panel beam can directly influence the NVH performance of the automobile, such as idle speed vibration of a steering wheel, vibration abnormal sound in an instrument panel assembly when the automobile runs at a constant speed and the like. In addition, as the demand for lightweight automobiles is higher, the development of a structure that can satisfy various performance requirements and has lighter weight is becoming a challenge for design engineers. At present, most instrument panel cross beams of passenger vehicles are generally formed by welding steel pipes and sheet metal parts, and the weight of the instrument panel cross beams is heavier. Along with the requirement of light weight of vehicles and the gradual maturity of magnesium alloy die-casting technology, magnesium alloy's instrument board crossbeam has obtained a large amount of applications, compares with the instrument board crossbeam of selecting for use steel, and magnesium alloy can integrate a large amount of welded parts, and weight reduces 30% -40%, has better fuel economy, and crashworthiness and damping performance promote by a wide margin. Therefore, it is particularly important to optimize the design by reducing the weight of the instrument panel cross member.
Disclosure of Invention
The invention provides an optimization method for the lightweight of an instrument board beam, aiming at improving the problems.
The invention is realized in such a way, and provides an optimization method for the lightweight of an instrument board beam, which comprises the following specific steps:
s1, constructing a fitness function based on the target function and the constraint condition, taking the minimum mass of the instrument panel beam as the target function, and taking the modal analysis and the rigidity analysis of the instrument panel beam as the constraint condition;
s2, carrying out gene coding on the thickness of each part of the instrument board beam, and determining the mapping relation between the individual gene and the thickness of each part of the instrument board beam;
s3, obtaining the individual genes with the optimal fitness value through a genetic algorithm, namely the optimal values of the thicknesses of the parts of the instrument board beam.
Further, the objective function is expressed as:
Figure BDA0003044021520000021
wherein M is the total mass of the instrument panel beam, aiIs the material density, S, of part iiIs the cross-sectional area, t, of part iiIs the thickness value of part i.
Further, the constraint is expressed as:
s.t.ξm<<ξ
δ<δm
d<dm
tmin<ti<tmax
where xi is the first order natural frequency ximIs the natural frequency of the vehicle, d is the maximum strain under load, dmAllowable strain for the material, delta is the maximum stress under load, deltamAllowable stress for the material, tmin、tmaxThe thickness maximum and the thickness minimum are respectively.
Further, the fitness function is:
Figure BDA0003044021520000022
wherein, C1、C2、C3、C4Is a weight factor, and
Figure BDA0003044021520000031
m is the total mass of the instrument panel beam, MmTo optimize the total mass of the front instrument panel beam, xi is a first-order natural frequencymIs the natural frequency of the vehicle, d is the maximum strain under load, dmAllowable strain for the material, delta is the maximum stress under load, deltamAllowing stress for the material.
Further, the step S3 specifically includes the following steps:
s31, setting the population scale, and randomly generating an initial population under the thickness size constraint condition of each part;
s32, calculating an individual fitness value;
s33, detecting whether the optimization times reach a time threshold value, if so, outputting an individual with an optimal fitness value, and if not, executing a step S34;
and S34, sequentially carrying out individual selection operation on the population, carrying out cross operation and mutation operation on the selected individuals until the population number reaches the set scale of the population to form next generation population individuals, and returning to the step S32.
Further, the individual selection in step S34 is performed using the tournament method.
Furthermore, the mutation operation adopts a non-uniform mutation method.
According to the invention, the very strong global optimization capability of the genetic algorithm is utilized, the constraint conditions required to be met during the lightweight design of the instrument board beam are comprehensively considered, and the optimal size design scheme is sought under various constraint conditions, so that the maximized weight reduction requirement of the instrument board beam is met, and the more effective lightweight design of the instrument board beam is realized.
Drawings
Fig. 1 is a flowchart of an optimization method for reducing weight of an instrument panel beam according to an embodiment of the present invention.
Detailed Description
The following description of preferred embodiments of the invention will be made in further detail with reference to the accompanying drawings.
The common instrument board beam comprises a tubular beam, an H-shaped support, a front upper structure, a left mounting support, a right mounting support and the like, and before lightweight design, a complete three-dimensional model of the instrument board beam is usually provided. The invention aims to optimize the thickness sizes of different parts of an instrument panel beam by using the minimum mass of the instrument panel beam as a target function and using modal analysis and rigidity analysis of the instrument panel beam as constraints and using a genetic algorithm on the basis of determining the general structure of the instrument panel beam.
Fig. 1 is a flowchart of an optimization method for reducing the weight of an instrument panel beam, which is provided by the embodiment of the invention, and the method specifically comprises the following steps:
step S1, determining an optimization objective and constraint conditions for the instrument panel beam size optimization, where in this example, the optimization objective is selected as the minimum mass of the instrument panel beam, and the objective function is set as:
Figure BDA0003044021520000041
wherein M is the total mass of the battery case, aiIs the material density, s, of part iiIs the cross-sectional area, t, of part iiThe thickness value of the part i is the total mass of the instrument board beam is the sum of the mass of each part of the instrument board beam, the mass of the part is obtained by multiplying the material density of the part, the middle section area of the part and the thickness value of the part, wherein the material density of the part and the middle section area of the part can be known in the initial optimization stage, and the thickness value of the part is converted from the optimal individual gene value obtained by optimization.
In the embodiment of the invention, the constraint condition is selected as the maximum stress of the instrument panel beam under the conditions of the first-order natural frequency of the modal analysis of the instrument panel beam and the load; wherein the load operating mode is static calculation, loads of a certain direction are loaded on the left end of the instrument board beam and the clamp plate respectively, and the constraint conditions are as follows:
s.t.ξm<<ξ
δ<δm
d<dm
tmin<ti<tmax
wherein xi is the first-order natural frequency of the instrument board beam, ximIs the natural frequency of the vehicle, d is the maximum strain of the dashboard cross member under load, dmAllowable strain for material, delta is the maximum stress of the instrument panel beam under load, deltamAllowable stress for the material, tmin、tmaxThe thickness maximum and the thickness minimum are respectively.
The function of the constraint conditions is as follows: (1) ximThe frequency of the idle vibration excitation of the vehicle is. In order to reduce part damage and improve driving comfort, the natural frequency of the parts of the running vehicle is required to be far away from the idle vibration excitation frequency of the vehicle, so as to prevent resonance; (2) under the loading condition, the maximum stress delta is less than deltamWherein δmAllowing stress for the material; in order to prevent the stress concentration of the part, which causes the part to break and endangers the driving safety of the automobile, the maximum stress of the part is required to be within the allowable stress range of the part material. (3) Under the loading condition, the maximum stress d is less than dmWherein d ismAllowing stress for the material; (4) optimized thickness tiWithin the thickness constraint range tmin~tmaxAnd (4) the following steps.
Step S2, according to the objective function and the optimization condition determined in step S1, the optimized parameters of the instrument board beam are selected, the coding rule is determined, in the embodiment, the optimized parameters are selected to be the thickness of the instrument board beam parts, the instrument board beam parts are classified and numbered according to the coding rule, the mapping relation between the individual genes and the thickness of the instrument board beam parts is determined, one individual gene corresponds to the thickness value of each part of a group of instrument board beams, the total mass M of the instrument board beam corresponding to each gene, the first-order natural frequency xi of the instrument board beam, the maximum strain d of the instrument board beam under the load condition, the maximum stress delta of the instrument board beam under the load condition are obtained in a simulation mode, and the adaptive value of each gene individual is calculated,
step S3, setting a population scale N and a cross variation probability f, randomly generating an initial population under the thickness dimension constraint condition of each part, and randomly generating the initial population according to the thickness dimension constraint condition;
the population size and the size of the cross variation probability settings affect the accuracy and efficiency of the algorithm solution. The larger the population scale is, the easier the global optimal solution is to be found, but the solution time is greatly increased, and the smaller the population scale is, the shorter the solution time is, but the more easily the local optimal solution is trapped. The cross mutation probability mainly influences the speed of generating new individuals, and the larger the cross mutation probability is, the faster the new individuals are generated, and the easier the new individuals are generated.
Step S4, obtaining a fitness function according to the optimization objective and the constraint condition mapping determined in step S1, in the embodiment of the present invention, the fitness function is:
Figure BDA0003044021520000061
wherein: c1、C2、C3、C4Is a weight factor, and
Figure BDA0003044021520000062
m is the total mass of the instrument panel beam, MmIn order to optimize the total mass of the front instrument panel, xi is the first-order natural frequency of the instrument panel beam, ximIs the natural frequency of the vehicle, d is the maximum strain of the dashboard cross member under load, dmAllowable strain for material, σ is the maximum stress of the instrument panel beam under load, σmAllowing stress for the material. The fitness function is an index for measuring the excellence of the individual, the higher the fitness is, the better the representative individual gene is, and the individual with the maximum fitness is taken as the final optimization result.
Step S5, calculating the fitness value of each individual in the population based on the fitness function;
and step S6, selecting individuals from the population, and performing crossover and variation operations on the selected individuals to increase the diversity of the population and form next generation population individuals.
Selecting and reserving optimal individuals by adopting a tournament method, taking a certain number of individuals from a population each time, and carrying out cross operation and mutation operation on the selected individuals, wherein the cross operation selects variable values from parent individuals by adopting an intermediate recombination mode to form new sub-individuals, and the diversity of the individuals is increased. The mutation operation adopts a non-uniform mutation method, random perturbation is carried out on the original gene, and the perturbed result is used as a new gene value after mutation.
And step S6, detecting whether the optimization times reach a time threshold value, if the detection result is negative, repeating the step S5, if the detection result is positive, outputting an individual with the maximum fitness, wherein the gene of the individual is the optimal thickness size of the instrument panel beam.
According to the invention, the very strong global optimization capability of the genetic algorithm is utilized, the constraint conditions required to be met during the lightweight design of the instrument board beam are comprehensively considered, and the optimal size design scheme is sought under various constraint conditions, so that the maximized weight reduction requirement of the instrument board beam is met, and the more effective lightweight design of the instrument board beam is realized.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (7)

1. A method for optimizing the lightweight of an instrument panel beam is characterized by comprising the following specific steps:
s1, constructing a fitness function based on the target function and the constraint condition, taking the minimum mass of the instrument panel beam as the target function, and taking the modal analysis and the rigidity analysis of the instrument panel beam as the constraint condition;
s2, carrying out gene coding on the thickness of each part of the instrument board beam, and determining the mapping relation between the individual gene and the thickness of each part of the instrument board beam;
s3, obtaining the individual genes with the optimal fitness value through a genetic algorithm, namely the optimal values of the thicknesses of the parts of the instrument board beam.
2. The method for optimizing the weight reduction of an instrument panel cross member as set forth in claim 1, wherein the objective function is expressed as:
Figure FDA0003044021510000011
wherein M is the total mass of the instrument panel beam, aiIs the material density, S, of part iiIs the cross-sectional area, t, of part iiIs the thickness value of part i.
3. The method for optimizing the weight reduction of the instrument panel cross member according to claim 1, wherein the constraint condition is expressed as:
s.t.ξm<<ξ
δ<δm
d<dm
tmin<ti<tmax
where xi is the first order natural frequency ximIs the natural frequency of the vehicle, d is the maximum strain under load, dmAllowable strain for the material, delta is the maximum stress under load, deltamAllowable stress for the material, tmin、tmaxThe thickness maximum and the thickness minimum are respectively.
4. The method for optimizing the weight reduction of the instrument panel cross beam of claim 1, wherein the fitness function is:
Figure FDA0003044021510000021
wherein, C1、C2、C3、C4Is a weight factor, and
Figure FDA0003044021510000022
m is the total mass of the instrument panel beam, MmTo optimize the total mass of the front instrument panel beam, xi is a first-order natural frequencymIs the natural frequency of the vehicle, d is the maximum strain under load, dmAllowable strain for the material, delta is the maximum stress under load, deltamAllowing stress for the material.
5. The method for optimizing the weight reduction of the instrument panel cross member according to claim 1, wherein the step S3 specifically includes the steps of:
s31, setting the population scale, and randomly generating an initial population under the thickness size constraint condition of each part;
s32, calculating an individual fitness value;
s33, detecting whether the optimization times reach a time threshold value, if so, outputting an individual with an optimal fitness value, and if not, executing a step S34;
and S34, sequentially carrying out individual selection operation on the population, carrying out cross operation and mutation operation on the selected individuals until the population number reaches the set scale of the population to form next generation population individuals, and returning to the step S32.
6. The method for optimizing the weight reduction of an instrument panel cross member as set forth in claim 5, wherein the individual selection in step S34 is performed by a championship method.
7. The method for optimizing the weight reduction of the instrument panel cross beam according to claim 5, wherein the variation operation is performed by a non-uniform variation method.
CN202110467902.6A 2021-04-28 2021-04-28 Optimization method for light weight of instrument board beam Active CN113127978B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110467902.6A CN113127978B (en) 2021-04-28 2021-04-28 Optimization method for light weight of instrument board beam

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110467902.6A CN113127978B (en) 2021-04-28 2021-04-28 Optimization method for light weight of instrument board beam

Publications (2)

Publication Number Publication Date
CN113127978A true CN113127978A (en) 2021-07-16
CN113127978B CN113127978B (en) 2024-04-09

Family

ID=76780983

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110467902.6A Active CN113127978B (en) 2021-04-28 2021-04-28 Optimization method for light weight of instrument board beam

Country Status (1)

Country Link
CN (1) CN113127978B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113127944A (en) * 2021-04-28 2021-07-16 奇瑞汽车股份有限公司 Optimization method for light weight of battery box

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102012958A (en) * 2010-12-29 2011-04-13 奇瑞汽车股份有限公司 Method for designing automobile body structure layout
CN102024082A (en) * 2010-12-15 2011-04-20 同济大学 Method for realizing multidisciplinary and multi-objective optimization of structural system of automobile instrument panel
CN105574300A (en) * 2016-02-24 2016-05-11 武汉理工大学 Optimum design method for steel rail weld seam finish-milling machine tool beam body based on BP neural network and genetic algorithm
CN106682254A (en) * 2016-09-30 2017-05-17 杭州谱谐特科技有限公司 Stereoscopic garage optimization method based on self-adaption genetic algorithm
JP2020071725A (en) * 2018-10-31 2020-05-07 マツダ株式会社 Design supporting method for structure
CN112464382A (en) * 2020-11-30 2021-03-09 奇瑞汽车股份有限公司 Automobile instrument board beam size optimization design method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102024082A (en) * 2010-12-15 2011-04-20 同济大学 Method for realizing multidisciplinary and multi-objective optimization of structural system of automobile instrument panel
CN102012958A (en) * 2010-12-29 2011-04-13 奇瑞汽车股份有限公司 Method for designing automobile body structure layout
CN105574300A (en) * 2016-02-24 2016-05-11 武汉理工大学 Optimum design method for steel rail weld seam finish-milling machine tool beam body based on BP neural network and genetic algorithm
CN106682254A (en) * 2016-09-30 2017-05-17 杭州谱谐特科技有限公司 Stereoscopic garage optimization method based on self-adaption genetic algorithm
JP2020071725A (en) * 2018-10-31 2020-05-07 マツダ株式会社 Design supporting method for structure
CN112464382A (en) * 2020-11-30 2021-03-09 奇瑞汽车股份有限公司 Automobile instrument board beam size optimization design method

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
WANG PING 等: "Multidisciplinary Design Optimization of Vehicle Instrument Panel Based on Multi-objective Genetic Algorithm", CHINESE JOURNAL OF MECHANICAL ENGINEERING, vol. 26, no. 02, pages 304 - 312 *
冯弟瑶 等: "基于轻量化的汽车仪表板横梁总成优化分析", PROCEEDINGS OF THE 13TH INTERNATIONAL FORUM OF AUTOMOTIVE TRAFFIC SAFETY(INFATS), pages 181 - 190 *
叶坤武 等: "基于遗传算法的飞机驾驶舱布局优化设计", 兵器装备工程学报, vol. 38, no. 03, pages 108 - 110 *
周磊 等: "基于遗传算法的汽车仪表板横梁参数优化", 计算机应用与软件, vol. 34, no. 06, pages 75 - 79 *
梁森 等: "大阻尼高比刚度复合材料仪表板结构设计及动态特性分析", 振动与冲击, vol. 36, no. 06, pages 212 - 217 *
蔡庆荣 等: "基于Isight的仪表板横梁优化", 计算机辅助工程, vol. 22, no. 2, pages 221 - 225 *
郭旋: "管柱型仪表板横梁结构优化设计", 中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑, no. 05, pages 035 - 430 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113127944A (en) * 2021-04-28 2021-07-16 奇瑞汽车股份有限公司 Optimization method for light weight of battery box
CN113127944B (en) * 2021-04-28 2024-03-26 奇瑞汽车股份有限公司 Optimization method for light weight of battery box

Also Published As

Publication number Publication date
CN113127978B (en) 2024-04-09

Similar Documents

Publication Publication Date Title
Chen et al. Multi-objective optimization of the vehicle ride comfort based on Kriging approximate model and NSGA-II
CN111444623B (en) Collaborative optimization method and system for damping nonlinear commercial vehicle suspension dynamics
Wang et al. Structure-material-performance integration lightweight optimisation design for frontal bumper system
Mohan et al. New mass optimization technique to achieve low mass BIW designs using optimal material layout methodology on the frontal vehicle crash
CN113127978A (en) Optimization method for light weight of instrument board beam
CN113591230B (en) Multi-objective optimization method for commercial vehicle cab based on beam section
Wang et al. Crashworthiness-based multi-objective integrated optimization of electric vehicle chassis frame
Karthick et al. Structural analysis of motorcycle spokes design using finite element analysis with alloy materials
CN112257189B (en) Multidisciplinary optimization method for light weight of passenger car framework
Baskin et al. A case study in structural optimization of an automotive body-in-white design
CN113127944B (en) Optimization method for light weight of battery box
CN115828438B (en) Method, medium and equipment for predicting ultimate performance of automobile
CN112016160A (en) Design and optimization method for side impact resistance of automotive aluminum alloy thin-wall beam
Padmanabhan et al. Investigation of lightweight wheel design using alloy materials through structural analysis
CN115292823B (en) Method and equipment for optimizing structure of automobile power battery pack
Zhou et al. An enhanced hybrid and adaptive meta-model based global optimization algorithm for engineering optimization problems
CN116383969A (en) Robustness matching method for suspension and whole vehicle performance considering uncertain factors
CN115099093A (en) Entropy weight TOPSIS-based white vehicle body structure multi-objective optimization design method
Sithik et al. Simplified approach of chassis frame optimization for durability performance
CN113312827A (en) Multi-objective optimization method for automobile framework
Moaaz et al. FINITE ELEMENT STRESS ANALYSIS OF TRUCK CHASSIS USING ANSYS
Ouyang et al. Multi-objective Combination Optimization of Automobile Subframe Dynamic Stiffness
Chen et al. Lightweight Design and Multi-Objective Optimization for a Lower Control Arm Considering Multi-Disciplinary Constraint Condition
Dai et al. Electric Bus Frame Optimization for Side-Impact Safety and Mass Reduction Based on the Surrogate Model Method
Yang et al. Six-sigma robust design optimisation of an electric bus considering crashworthiness and lightweight

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
GR01 Patent grant
GR01 Patent grant