• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (18): 128-133.

• 论文 • 上一篇    下一篇

大客车车身骨架多学科协同优化设计

苏瑞意;桂良进;吴章斌;田程;马林;范子杰   

  1. 清华大学汽车系;清华大学汽车安全与节能国家重点实验室
  • 发布日期:2010-09-20

Multidisciplinary Design and Collaborative Optimization for Bus Body

SU Ruiyi;GUI Liangjin;WU Zhangbin;TIAN Cheng;MA Lin;FAN Zijie   

  1. Department of Automotive Engineering, Tsinghua University State Key Laboratory of Automotive Safety and Energy, Tsinghua University
  • Published:2010-09-20

摘要: 对某全承载大客车车身骨架结构进行包括轻量化、刚度、强度、振动模态和翻滚的多学科设计优化,以提高客车的综合性能。为克服客车翻滚分析的高度非线性带来的寻优困难,并解决结构有限元分析的低效问题,建立各学科的近似模型。首先建立大客车车身结构有限元模型,其中刚度、强度以及振动模态分析由Msc.Nastran完成,翻滚分析由显式动力学软件Ls-dyna完成。其次结合工艺要求和灵敏度分析结果,选择出各学科的设计变量,用优化的拉丁方方法完成试验设计。在此基础上,采用响应面方法建立各学科结构响应的近似模型。建立客车车身骨架结构的多学科优化模型,并用协同优化方法求解。结果显示,优化后的设计方案在轻量化、刚度、强度、模态振动和翻滚安全性方面均优于原设计方案。

关键词: 多学科设计, 客车车身, 响应面方法, 协同优化

Abstract: A multidisciplinary design optimization (MDO), considering lightweight, stiffness, strength, vibration mode and rollover, is implemented to an integral bus body structure to improve its synthetic performance. To conquer the difficulty of high nonlinearity brought by rollover analysis and to resolve the time consuming problem of structural finite element (FE) analysis, multidisciplinary approximate models are built. The FE models of the bus body are established, in which the stiffness, strength and vibration mode analyses are finished by Msc.Nastran, and the rollover analysis is solved by the explicit dynamic software Ls-dyna. The disciplinary variables are selected on the basis of technological requirements and sensitivity analysis results. The experimental design is finished by using optimal Latin hypercube method. Then the multidisciplinary approximate models are constructed by using the response surface method. The MDO problem is solved by using collaborative optimization approach. The result shows that the optimal solution is better than the original design in aspects of lightweight, stiffness, strength, modal vibration, and safety of rollover.

Key words: Bus body, Collaborative optimization, Multidisciplinary design, Response surface method

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