吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (1): 35-42.doi: 10.13229/j.cnki.jdxbgxb201601006

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基于疲劳寿命的轿车后悬架扭转梁轻量化设计

蒋荣超1, 王登峰1, 秦民2, 蒋永峰2   

  1. 1.吉林大学 汽车仿真与控制国家重点实验室,长春 130022;
    2.中国第一汽车股份有限公司 技术中心,长春 130011
  • 收稿日期:2014-08-17 出版日期:2016-01-30 发布日期:2016-01-30
  • 通讯作者: 王登峰(1963-),男,教授,博士生导师.研究方向:汽车轻量化设计与应用.E-mail:caewdf@jlu.edu.cn
  • 作者简介:蒋荣超(1985-),男,博士研究生.研究方向:汽车轻量化设计与应用.E-mail:jrch123@126.com
  • 基金资助:
    吉林省科技发展计划重大项目(20126004); 吉林大学研究生创新基金项目(2015084)

Lightweight design of twist beam of rear suspension of passenger car based on fatigue life

JIANG Rong-chao1, WANG Deng-feng1, QIN Min2, JIANG Yong-feng2   

  1. 1.State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2.R&D Center, FAW Group Corporation, Changchun 130011, China
  • Received:2014-08-17 Online:2016-01-30 Published:2016-01-30

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摘要： 以某国产轿车后悬架扭转梁的轻量化为研究目标,利用多体动力学软件建立考虑后悬架扭转梁柔性的整车刚柔耦合模型,并通过扭转梁自由模态试验和整车行驶平顺性实车道路试验验证了模型的正确性。在耐久性强化路面上进行整车动力学仿真分析,计算扭转梁模态位移时间历程,通过模态应力恢复得到扭转梁应力时间历程,并采用名义应力法进行疲劳寿命分析。基于网格变形技术建立扭转梁参数化模型并定义设计变量,以质量和疲劳寿命为优化目标,以一阶扭转模态频率和扭转刚度为约束条件,结合Kriging近似模型和多目标粒子群优化算法对扭转梁进行多目标优化设计,获取Pareto最优解集,并选取一个最优解验证扭转梁轻量化效果。结果表明,在使疲劳寿命满足设计要求的同时,优化后扭转梁质量减少20.35%,轻量化效果比较明显。

关键词: 车辆工程, 轻量化设计, 模态应力恢复, 疲劳寿命, 网格变形, 粒子群优化

Abstract: This paper studies the lightweight design method of the twist beam of rear suspension of a domestic passenger car. The whole vehicle's rigid-flexible coupling model with flexible twist beam was built using multi-body dynamics software. Modal test of the twist beam in a free-free configuration and vehicle road test of ride comfort were carried out to verify the validity of the proposed model. On this basis, the modal displacement time history of the twist beam was calculated from a dynamic simulation on the durability enhancement road. Then the stress time history of the twist beam was obtained based on Modal Stress Recovery (MSR). According to the nominal stress method, fatigue life of the twist beam was assessed. Furthermore, mesh morphing technology was employed to build the parametric model of the twist beam, which was used to define the design variables. Then, the Kriging approximation model and particle swarm algorithm were adopted to perform the multi-objective optimization of the twist beam. The mass and fatigue life were defined as the objective functions, while the first modal frequency and torsional stiffness were taken as the constraints. The Pareto optimal set was found and one of the optimal solutions was chosen to check the effectiveness of the optimization method. The results indicate that the weight of the optimized twist beam is reduced 20.35% while its fatigue life satisfies the design requirement.

Key words: vehicle engineering, lightweight design, modal stress recovery, fatigue life, mesh morphing, particle swarm optimization

中图分类号: 

  • U463.33
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