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汽车安全与节能学报

汽车安全与节能学报 ›› 2013, Vol. 4 ›› Issue (4): 339-347.DOI: 10.3969/j.issn.1674-8484.2013.04.006

• 汽车安全 • 上一篇    下一篇

稳健性和轻量化在整车侧面碰撞性能优化中的应用

张继游，门永新，彭 鸿，冯擎峰   

  1. 吉利汽车研究院 浙江省安全控制技术重点实验室，杭州 311228，中国
  • 收稿日期:2013-06-20 出版日期:2013-12-25 发布日期:2014-01-15
  • 作者简介:张继游（1984—），男（汉），福建，工程师。E-mail ：zhangjiyou2012@163.com

Application of robustness and light-mass in car side crash#br# performance optimization

ZHANG Jiyou, MEN Yongxin, PENG Hong, FENG Qingfeng   

  1. Geely Automobile Research Institute, Zhejiang Key Laboratory of Automobile Safety Technology,
    Hangzhou 311228, China
  • Received:2013-06-20 Online:2013-12-25 Published:2014-01-15

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摘要：

针对某自主品牌多用途汽车(MPV)，进行侧面碰撞的轻量化和稳健性优化设计。优化过程中，
提出了基于离散设计变量和噪声因素的组合方法。该方法综合了试验设计（DOE）、近似建模、Monte
Carlo 采样和基于响应面模型的稳健优化技术，考虑了侧面碰撞工艺参数（关键件板厚）和碰撞工况
的波动（移动壁障的位置和高度）。进行了3 轮优化，分析了其中的灵敏度、确定性和6σ 稳健性。
结果表明：优化后车身结构的质量减少4.60 kg，侧面碰撞性能的可靠度高于99.97%。因此，该优化
方法能满足响应面模型的精度要求。

关键词: 汽车安全；侧面碰撞；轻量化；试验设计(DOE) ；6&sigma, 稳健性优化；响应面模型

Abstract:

Robustness optimization and light-mass of side crash performance were performed for an ownedbrand
multi-purpose vehicle (MPV). The optimization method was a combination method based on discrete
design variables and noise factors, which including the design of experiments (DOE), the approximation model,
the Monte Carlo sampling technique, and the robust optimization based on a respond surface model, and
considering with the process parameters of side crash performance (the thicknesses of key parts) and the
differences of a crash load case (the position and the height of a movable barrier). A three-stage optimization
was used to analyzing the sensitivity, the deterministic, and the 6-sigma robustness for side crash. The results
show that the body structure mass is reduced by 4.60 kg, while the reliability of side crash performance is higher
than 99.97%, after the optimization. Therefore, the method ensures the accuracy of the approximate model to
meet the optimization requirements.

Key words: vehicle safety, side crash, light-mass, design of experiments (DOE), six sigma robustness
optimization, respond surface model

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