Crashworthiness-based multi-objective integrated optimization of electric vehicle chassis frame

Chassis frame of electric vehicle contains several thin-walled tube structures that can provide an important component for installing the power unit and supporting the body in white of vehicle. Thus, design a chassis frame is a multi-objective optimization and multi-parameter problem. To address it, the contributions of design variables to the performance indicators of chassis frame are studied first, and obtained the optimal design variables. The effects of the design parameters on the objective responses are analyzed based on a polynomial response surface model. Moreover, to determine optimal solution between the conflicting performance indicators of the chassis frame, an integrated approach based on lightweight and crashworthiness is presented to analysis the performance and determine the Pareto fronts. In addition, the optimal solution is acquired from the Pareto fronts by the grey relational analysis and game theory. Experiments corresponding to the numerical analysis are performed to verify the feasibility of the optimized strategy and the performance of the optimized chassis frame structure. Results show that according to the optimal parameters of chassis frame, the lightweight performance can be improved significantly, while the linear performance and crashworthiness performance of chassis frame are ensured.

[1]  A. Bhattacharya,et al.  Dissimilar GTAW between AISI 304 and AISI 4340 steel: Multi-response optimization by analytic hierarchy process , 2017 .

[2]  Nader Nariman-Zadeh,et al.  Pareto optimization of a five-degree of freedom vehicle vibration model using a multi-objective uniform-diversity genetic algorithm (MUGA) , 2010, Eng. Appl. Artif. Intell..

[3]  Goran Krajačić,et al.  Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles , 2016 .

[4]  Hongnan Wang,et al.  Multi-objective optimization of the layout of damping material for reducing the structure-borne noise of thin-walled structures , 2019, Thin-Walled Structures.

[5]  Ning Li,et al.  Multi-objective optimization of the trimming operation of CFRPs using sensor-fused neural networks and TOPSIS , 2019, Measurement.

[6]  Dengfeng Wang,et al.  A multi-objective optimization approach for simultaneously lightweighting and maximizing functional performance of vehicle body structure , 2020 .

[7]  Zhu Zhongxiang,et al.  Application of Improved NSGA-II Algorithm in Matching Optimization for Tractor Powertrain , 2020 .

[8]  A. Asanjarani,et al.  Multi-objective crashworthiness optimization of tapered thin-walled square tubes with indentations , 2017 .

[9]  S. Mondal,et al.  Multi-objective optimization in WEDM process of nanostructured hardfacing materials through hybrid techniques , 2016 .

[10]  Rongchao Jiang,et al.  Multi-objective Optimization of Vehicle Dynamics Performance Based on Entropy Weighted TOPSIS Method , 2018 .

[11]  Sameh M. El-Sayegh,et al.  Evaluating supplier selection criteria for oil and gas projects in the UAE using AHP and Delphi , 2016 .

[12]  Qiang Gao,et al.  Multi-objective lightweight and crashworthiness optimization for the side structure of an automobile body , 2018 .

[13]  Xiaohua Zeng,et al.  Multi-objective optimization of drive gears for power split device using surrogate models , 2014 .

[14]  Hoon Huh,et al.  Dynamic tensile characteristics of TRIP-type and DP-type steel sheets for an auto-body , 2008 .

[15]  Kiran Kumar Annamdas,et al.  Multi-objective optimization of engineering systems using game theory and particle swarm optimization , 2009 .

[16]  Mohammad Hassan Shojaeefard,et al.  Multi-objective optimization of a natural aspirated three-cylinder spark ignition engine using modified non-dominated sorting genetic algorithm and multicriteria decision making , 2016 .

[17]  Jianbin Du,et al.  Simultaneous topology optimization of supporting structure and loci of isolators in an active vibration isolation system , 2018 .

[18]  Aiguo Cheng,et al.  Lightweight and crashworthiness design of an electric vehicle using a six-sigma robust design optimization method , 2018, Engineering Optimization.

[19]  Dengfeng Wang,et al.  Multi-objective lightweight design of the container S-beam based on MNSGA-II with grey relational analysis , 2019, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

[20]  Zhe Li,et al.  Multi-objective optimization of active suspension system in electric vehicle with In-Wheel-Motor against the negative electromechanical coupling effects , 2019, Mechanical Systems and Signal Processing.

[21]  Dengfeng Wang,et al.  Optimizing the static–dynamic performance of the body-in-white using a modified non-dominated sorting genetic algorithm coupled with grey relational analysis , 2017 .

[22]  Zhibing Zhang,et al.  Energy-absorbing analysis and reliability-based multiobjective optimization design of graded thickness B pillar with grey relational analysis , 2019 .

[23]  A. F. Sherwani,et al.  Parametric optimization of organic Rankine cycle using TOPSIS integrated with entropy weight method , 2019, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.

[24]  Wenjie Zuo,et al.  Component sensitivity analysis of conceptual vehicle body for lightweight design under static and dynamic stiffness demands , 2014 .

[25]  S. E. Hosseini,et al.  CFD simulation and Pareto-based multi-objective shape optimization of the centrifugal pump inducer applying GMDH neural network, modified NSGA-II, and TOPSIS , 2019, Structural and Multidisciplinary Optimization.