广东工业大学学报 ›› 2013, Vol. 30 ›› Issue (3): 105-108.doi: 10.3969/j.issn.1007-7162.2013.03.020

• 综合研究 • 上一篇    下一篇

基于ADAMS的FSAE赛车前悬架优化设计

王行,阳林,彭仁杰,冯勇   

  1. 广东工业大学 机电工程学院,广东 广州 510006
  • 收稿日期:2013-03-18 出版日期:2013-09-30 发布日期:2013-09-30
  • 作者简介:王行(1988-),女,硕士研究生,主要研究方向为电动汽车关键技术、方程式赛车. 通讯作者:阳林(1966-),男,教授,博士,主要研究方向为电动汽车关键技术、 车身模具CAD/CAE/CAM/VR.
  • 基金资助:

    国家级大学生创新创业训练项目(201211845008)

Optimization of a FSAE Racing Car's Front Suspension Based on ADAMS

Wang Hang, Yang Lin,Peng Ren-jie, Feng Yong   

  1. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2013-03-18 Online:2013-09-30 Published:2013-09-30

摘要: 为更好地研究方程式赛车的操纵稳定性,基于机械系统动力学仿真软件ADAMS对某大学的大学生方程式赛车(Formula SAE racing car)的前悬架系统建立仿真模型,并进行运动学仿真分析,得到车轮在跳动时主销内倾角、主销后倾角、车轮外倾角和前轮前束4项参数的变化曲线,分析各参数变化对赛车操纵稳定性的影响,利用ADAMS/Insight模块对悬架的硬点位置进行多目标优化.结果表明,前悬架系统的运动特性得到有效提升,满足设计要求,该研究对于赛车的悬架设计具有一定的指导意义.

关键词: 双横臂独立悬架;方程式赛车(FSAE);ADAMS仿真软件;仿真优化

Abstract: In order to study the handling and stability of Formula SAE racing car better, based on the College Students' Formula SAE racing competition (Formula SAE racing car) of a university, it established the simulation model for the front double wishbone independent suspension system by using the mechanical system simulation software ADAMS, obtained the variation curve of kingpin inclination angle, caster, camber and toe-in four parameters by simulating and analyzing the wheels jumping, analyzed the influence of each parameter changes on the handling and stability of Formula SAE racing car, and used Insight module in ADAMS for the multi-objective optimization of the suspension system' hard point position. The results show that the motion characteristics of front  double wishbone independent suspension system are effectively improved, which meets the expected design requirements of the Formula SAE racing car. This study has a certain guiding significance for the designing of the racing car suspension system.

Key words: double wishbone independent suspension; FSAE; ADAMS; simulation optimization

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