主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

汽车实用技术 ›› 2023, Vol. 48 ›› Issue (8): 85-90.DOI: 10.16638/j.cnki.1671-7988.2023.08.014

• 设计研究 • 上一篇    下一篇

汽车前纵梁结构耐撞性分析及多目标优化设计

汪 婷 1,2,李翼良 1,2,张代胜 1,2,谷先广*1,2   

  1. 1.合肥工业大学 智能制造技术研究院,2.合肥工业大学 汽车与交通工程学院
  • 出版日期:2023-04-30 发布日期:2023-04-30
  • 通讯作者: 谷先广
  • 作者简介:汪婷(1998—),女,硕士研究生,研究方向为汽车轻量化,E-mail:wt13615650902@163.com。
  • 基金资助:
    安徽省新能源汽车暨智能网联汽车产业技术创新工程项目(IMIZX2019004)。

Crashworthiness Analysis and Multi-objective Optimization Design of Automobile Front Longitudinal Beam Structure

WANG Ting1,2 , LI Yiliang1,2, ZHANG Daisheng1,2, GU Xianguang*1,2   

  1. 1.Institute of Intelligent Manufacturing Technology, Hefei University of Technology,2.School of Automotive and Traffic Engineering, Hefei University of Technology
  • Online:2023-04-30 Published:2023-04-30
  • Contact: GU Xianguang

摘要: 为提高汽车前纵梁结构的耐撞性和轻量化水平,文章对其进行多目标优化设计。基于 动态落锤冲击试验,建立并验证了前纵梁有限元模型的准确性以及建模方法的可靠性。结合 试验设计、粒子群优化(PSO)算法改进的支持向量机回归模型(SVR)和非支配排序遗传 算法Ⅱ(NSGA-Ⅱ),以减轻前纵梁质量和增加其比吸能为优化目标,对前纵梁的结构进行确 定性优化和可靠性优化。结果表明,优化后的前纵梁结构耐撞性和轻量化水平都有了提升, 同时也保证了设计的可靠性。

关键词: 前纵梁;耐撞性;轻量化;多目标优化设计

Abstract: In order to improve the crashworthiness and lightweight level of automobile front rail structure, multi-objective optimization design is carried out in this paper. Based on the dynamic drop hammer impact test, the accuracy of the finite element model of the front rail and the reliability of the modeling method are established and verified. Combined with experimental design, particle swarm optimization (PSO) algorithm improved support vector regression (SVR) model and non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ), In order to reduce the weight of the front rail and increase its specific absorption energy, the deterministic optimization and reliability optimization of the front rail were carried out. The results show that the crashworthiness and lightweight level of the optimized front rail structure are improved, and the reliability of the design is also guaranteed.

Key words: Front rail; Crashworthiness; Lightweight; Multi-objective optimization design