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Chinese Journal of Engineering Design  2021, Vol. 28 Issue (1): 80-88    DOI: 10.3785/j.issn.1006-754X.2021.00.012
Optimization Design     
Structure optimization of experimental target vehicle chassis based on multi-objective genetic algorithm
HUANG Wei1,2, LIU Wei-yi1,2, LIU Zhi-en1,2, LU Chi-hua1,2
1.Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
2.Hubei Collaborative Innovation Center of Auto Parts Technology, Wuhan University of Technology, Wuhan 430070, China
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Abstract  Carrying out experimental target vehicle crash tests on actual roads is one of the important test means in the development of intelligent vehicles. In order to ensure the safety of intelligent vehicles, the chassis of the experimental target vehicle must have the ability to resist the large rolling impact. Since the rolling process of the experimental target vehicle chassis involves problems such as contact nonlinearity and geometric nonlinearity, it is difficult to design and optimize its structure based on simulation analysis alone. For this reason, the explicit nonlinear finite element method was first used to analyze the anti-rolling performance of the experimental target vehicle chassis; then, the multi-objective genetic algorithm based on the local amplification method was used to establish a multi-objective optimization model of the chassis structure with the materials as discrete variables and the geometry dimensions as continuous variables; lastly, a chassis structure optimization method with high adaptability and high fit prediction accuracy was constructed by HyperStudy software, and the chassis structure optimization scheme that met the requirements of anti-rolling performance and lightweight was obtained. The research results show that the multi-objective genetic optimization method based on the collision and rolling simulation has the characteristics of strong adaptability, accurate optimization results and high degree of multi-objective collaborative satisfaction for solving the structure optimization problem of the experimental target vehicle chassis that considers discrete-continuous variables and the highly nonlinear response surface, which can provide a reference for the structure optimization design that requires comprehensive consideration of discrete variables and multiple properties in practical applications.

Received: 12 May 2020      Published: 25 February 2021
CLC:  TH 22  
  U463.6  
Cite this article:

HUANG Wei, LIU Wei-yi, LIU Zhi-en, LU Chi-hua. Structure optimization of experimental target vehicle chassis based on multi-objective genetic algorithm. Chinese Journal of Engineering Design, 2021, 28(1): 80-88.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2021.00.012     OR     https://www.zjujournals.com/gcsjxb/Y2021/V28/I1/80


基于多目标遗传算法的实验目标车底盘结构优化

在实际道路上开展实验目标车碰撞试验是智能汽车开发过程中的重要测试手段之一。为保证智能汽车的安全性,实验目标车的底盘必须具有抵抗较大碾压冲击的能力。由于实验目标车底盘的碾压过程涉及接触非线性和几何非线性等问题,仅基于仿真分析对其进行结构设计和优化存在较大困难。为此,首先采用显式非线性有限元法对实验目标车底盘的抗碾压性能进行分析;然后采用基于局部放大法的多目标遗传算法建立以材料为离散变量、几何尺寸为连续变量的底盘结构多目标优化模型;最后利用HyperStudy软件搭建了一种适应性强且拟合预测精度高的底盘结构优化方法,并获得了满足抗碾压性能和轻量化要求的底盘结构优化方案。研究结果表明,基于碰撞碾压仿真的多目标遗传优化方法对解决考虑离散-连续型变量和响应面高度非线性的实验目标车底盘结构优化问题具有适应性强、优化结果准确和多目标协同满足程度高的特点,可为实际应用中需综合考虑离散变量和多种性能的结构优化设计提供参考。
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