Genetic algorithm-based optimization design method of the Formula SAE racing car’s rear wing

Author:

Wang Hui12,Bai Qiuyang12,Hao Xufei12,Hua Lin12,Meng Zhenghua12

Affiliation:

1. Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, PR China

2. Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan, PR China

Abstract

The aerodynamic devices play an important role on the performance of the Formula SAE racing car. The rear wing is the most significant and popular element, which offers primary down force and optimizes the wake. In traditional rear wing optimization, the optimization variables are first selected, and separately enumerated according to the analyzing experience of the racing car’s external flow field, and thus the optimal design is chosen by comparison. This method is complicated, and even might lose some key sample points. In this paper, the attack angle of the rear wing and the relative position parameters are set as design variables; then the design variables’ combination is determined by the DOE experimental design method. The aerodynamic lift and drag of the racing car for these variables’ combinations are obtained by the computational fluid dynamics method. With these sample points, the approximation model is produced by the response surface method. For the sake of gaining the best lift to drag ( FL/ FD) ratio, i.e. maximum down force and the minimum drag force, the optimal solution is found by the genetic algorithm. The result shows that the established optimization procedure can optimize the rear wing’s aerodynamic characteristic on the racing car effectively and have application values in the practical engineering.

Publisher

SAGE Publications

Subject

Mechanical Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Optimal Blade Design for Mini Wind Generators Mountable on the Spoiler of a Vehicle;Proceedings of the 7th Brazilian Technology Symposium (BTSym’21);2022

2. In-mold lightweight integrating for structural/functional devices;Journal of Polymer Engineering;2021-07-22

3. Lightweight optimization of passenger car seat frame based on grey relational analysis and optimized coefficient of variation;Structural and Multidisciplinary Optimization;2020-07-25

4. Multiobjective optimization of a newly developed additively manufactured functionally graded anisotropic porous lattice structure;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2020-02-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3