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汽车安全与节能学报

汽车安全与节能学报 ›› 2020, Vol. 11 ›› Issue (3): 314-321.DOI: 10.3969/j.issn.1674-8484.2020.03.006

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考虑侧面柱碰的电动汽车车门多学科优化设计

郝琪，李海伦，崔宏伟，田钰楠，刘正午   

  1. （湖北汽车工业学院 汽车工程学院，湖北 十堰 442002，中国） 
  • 收稿日期:2020-03-08 出版日期:2020-09-30 发布日期:2020-10-20
  • 作者简介:第一作者 / First author ： 郝琪（1973—），女（汉），山西，教授。E-mail: 1293169789@qq.com。
  • 基金资助:
    湖北省重点实验室协同创新基金（2015XTZX041）。

Multidisciplinary design optimization of an electric vehicle door based on pole side crash 

HAO Qi, LI Hailun, CUI Hongwei, TIAN Yunan, LIU Zhenwu   

  1. (Hubei University of Automotive Technology，Automotive Dept，Shiyan 442002, China) 
  • Received:2020-03-08 Online:2020-09-30 Published:2020-10-20

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摘要： 为综合考虑车门结构刚度、振动特性和侧面柱碰撞安全性能，对电动汽车车门进行基于近似 模型的多目标多学科优化设计 (MDO)。以全新设计的单排两座小型电动汽车 (EV) 为目标车型，建立 了与实验对标的整车及车门有限元模型。基于欧洲侧面柱碰实验标准，利用 Hammersley 实验设计 (DOE) 方法，结合主效应分析，确定 9 个车门关键零件的尺寸为设计变量；结合径向基函数 (RBF) 近 似方法，进行全局优化。结果表明：在保证车门振动特性的同时，多学科优化方法有效提高车门刚度 及侧面柱碰综合指标，并实现车门减质量 7.5%。

关键词: 电动汽车 (EV) ；车门；侧面柱碰撞；多学科优化设计 (MDO) ；近似模型 

Abstract: A multi-objective, multi-disciplinary design optimization (MDO) of an electric vehicle door was achieved with approximate model considering the door construction stiffness characteristics, the door vibration performance, and the door pole side crash safety comprehensively. Based on a single-row two-seater electric vehicle (EV) designed newly, an effective finite element models of the vehicle and the vehicle door were established and benchmarked experiments. According to the Euro Pole Side Crash Rules, the dimensions of 9 key parts were determined as design variables using a Hammersley experiment of design (DOE) method and a main effect analysis method. Based on the radial basis function (RBF) approximate method, a global respond optimization was achieved. The results show that by using an MDO method ensures the vibration performance with a good level, reduces the door mass of 7.5% with improving validly the stiffness of door and the pole side crash safety performances.

Key words: electric vehicle (EV), door, pole side crash, multidisciplinary design optimization(MDO); approximate model 

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