自然科学版 英文版
自然科学版 英文版
自然科学版 英文版
自然科学版 英文版
英文版编委
自然科学版 英文版
英文版首届青年编委

您目前所在的位置:首页 - 期刊简介 - 详细页面

中南大学学报(自然科学版)

Journal of Central South University

第50卷    第11期    总第303期    2019年11月

[PDF全文下载]    [Flash在线阅读]

    

文章编号:1672-7207(2019)11-2732-11
某轿车车门轻量化与疲劳寿命多目标综合优化
龙岩1, 2,蒋凌山2,刘雪强2,熊海林2,陈志勇1,钟慧卿2

(1. 吉林大学 汽车仿真与控制国家重点实验室,吉林 长春,130022;
2. 一汽-大众汽车有限公司 技术开发部,吉林 长春,130011
)

摘 要: 为了提高某轿车车门的综合性能,对车门总成进行轻量化和疲劳寿命的多目标综合优化设计。首先建立并试验验证车身及车门总成有限元模型,基于模型分析车门总成装备件质量、结构尺寸、刚度和安装位置等8项参数对车门疲劳寿命的影响;然后,以这8项参数作为优化设计变量建立车门总成多目标综合优化参数模型,以车门总成质量和疲劳寿命为优化目标,以车门框刚度为约束条件,应用多目标粒子群优化算法对车门总成进行综合优化计算,得到Pareto最优解集,依据工程实际选取1组最优解,并依此进行样件试验以验证优化方法的有效性。研究结果表明:在保证车门总成刚度和提高疲劳寿命的同时,车门总成质量减少2.44 kg,说明优化方法是有效的。

 

关键词: 疲劳寿命;轻量化;刚度;粒子群优化

Multi-objective optimization of lightweight and fatigue life for car door
LONG Yan1, 2, JIANG Lingshan2, LIU Xueqiang2, XIONG Hailin2, CHEN Zhiyong1, ZHONG Huiqing2

1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
2. Department of Technology Development, FAW-Volkswagen Automotive Co. Ltd., Changchun 130011, China

Abstract:In order to improve the performance of a domestic car door synthetic, a multi-objective optimization method considering lightweight and fatigue life was implemented. Firstly, the finite element models (FEM) of car body and door were established and validated by test. Based on FEM, eight parameters that have effect on car door fatigue life were calculated and analyzed, which include mass, structure parameters, stiffness, positioning errors and so on. Then, a car door parametric optimization model was established, in which the eight parameters were used as the design variables. The mass and fatigue life were defined as the optimization objective, and the door stiffness was taken as the constraints, with the particle swarm algorithm being adopted to perform the multi-objective optimization of car door. The Pareto optimal set was obtained and one of the optimal solutions was selected by sample test to validate the effectiveness of the optimization method. The results show that the mass of the optimized door is reduced by 2.44 kg, while door stiffness and fatigue life satisfy the design requirement, which indicates that the optimization method is effective.

 

Key words: fatigue life; lightweight; stiffness; particle swarm optimization

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
版权所有:《中南大学学报(自然科学版、英文版)》编辑部
地 址:湖南省长沙市中南大学 邮编: 410083
电 话: 0731-88879765(中) 88836963(英) 传真: 0731-88877727
电子邮箱:zngdxb@csu.edu.cn 湘ICP备09001153号