| 考虑气动阻力和横风稳定的汽车车身多目标优化设计 |
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| 引用本文： | 亓昌,韩元吉,杨姝,吕振华. 考虑气动阻力和横风稳定的汽车车身多目标优化设计[J]. 汽车安全与节能学报, 2020, 11(1): 53-60 |
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| 作者姓名： | 亓昌 韩元吉 杨姝 吕振华 |
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| 作者单位： | 工业装备结构分析国家重点实验室,大连理工大学,大连116024,中国;大连理工大学,汽车工程学院,大连116024,中国;汽车安全与节能国家重点实验室,清华大学,北京 100084,中国;大连理工大学,汽车工程学院,大连116024,中国;中国核动力研究设计院,核反应堆系统设计技术重点实验室,成都 610213,中国;大连理工大学,汽车工程学院,大连116024,中国;汽车安全与节能国家重点实验室,清华大学,北京 100084,中国 |
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| 基金项目： | 国家自然科学基金资助项目(51475070);汽车安全与节能国家重点实验室开放基金(KF1809)。 |
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| 摘 要： | 综合考虑了气动阻力特性和横风稳定性,对车身外形参数进行了多目标自动优化设计。综合利用参数化建模技术、计算流体力学(CFD)仿真、试验设计方法、响应面模型和智能优化算法,集成Pro/Engineer参数化建模和ICEM网格划分工具以及Fluent仿真软件,在多学科优化平台modeFRONTIER上,搭建了一种自动优化设计流程。利用该流程,基于遗传算法(GA)对MIRA快背式模型车身几何外形进行了改型设计,得到了考虑车身气动阻力特性和横风稳定性的最优权衡设计解集。该结果使得气动阻力因数降低了5.2%,侧向力因数降低了5.8%。因而,实现了车身气动阻力和横风稳定性的多目标优化。
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| 关 键 词： | 汽车车身设计 空气动力学 计算流体力学(CFD) 多目标优化 响应面模型 遗传算法(GA) |
Multi-objective optimization design of auto body considering aerodynamic resistance and crosswind stability |
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| Affiliation: | (State Key Laboratory of Structural Analyst for Industrial Equipment,Dalian University of Technology,Dalian 116024,China;School of Automotive Engineering,Dalian University of Technology,Dalian 116024,China;State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing 100084,China;Nuclear Power Institute of China,Science and Technology on Reactor System Design Technology Laboratory,Chengdu 610005,China) |
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| Abstract: | A multi-objective automatic optimization-design of the body shape parameters was carried out considering aerodynamic drag characteristics and cross-wind stability.An automayic optimization process was set up on an optimization platform modeFRONTIER,comprehensively using parametric modeling technology,computational fluid dynamics(CFD),design of experiment(DOE),response surface model(RSM)and intelligent optimization algorithm,integrating Pro/Engineer,ICEM,and Fluent.Using this process,an MIRA fast-back auto body geometry was modified and designed to obtain an optimal trade-off design-solution-set considering the aerodynamic drag characteristics and cross-wind stability based on the genetic algorithm(GA).The result reduces the aerodynamic drag coefficient by 5.2%and reduces the lateral force coefficient by 5.8%.Therefore,a multi-objective optimization of aerodynamic resistance and crosswind stability of the vehicle body has been achieved. |
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| Keywords: | auto-body design aerodynamic computational fluid dynamics(CFD) multi-objective optimization response surface model genetic algorithm(GA) |
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