• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (9): 135-143.doi: 10.3901/JME.2017.09.135

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基于自由变形技术的汽车气动减阻优化*

汪怡平1,2, 王涛2,3, 黎帅2   

  1. 1. 吉林大学汽车仿真与控制国家重点实验室 长春 130025;
    2. 武汉理工大学现代汽车零部件技术湖北省重点实验室 武汉 430070;
    3. 湖南中车时代电动汽车股份有限公司 株洲 412007
  • 出版日期:2017-05-05 发布日期:2017-05-05
  • 作者简介:

    汪怡平(通讯作者),男,1984年出生,博士、副教授。主要研究方向为汽车空气动力学、气动声学。

    E-mail:wangyiping@whut.edu.cn

  • 基金资助:
    * 国家自然科学基金(51305312)和汽车仿真与控制国家重点实验室开放基金(20121111)资助项目; 20160802收到初稿,20170220收到修 改稿;

Aerodynamic Drag Reduction of Vehicle Based on Free Form Deformation

WANG Yiping1,2, WANG Tao2,3, LI Shuai2   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025;
    2. School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070;
    3. Hunan CRRC Times Electric Vehicle Co., Ltd., Zhuzhou 412007
  • Online:2017-05-05 Published:2017-05-05

摘要:

针对目前汽车气动减阻中基于工程师经验的试凑法所存在的盲目性和低效性,以及气动优化设计中车身曲面难于参数化等问题,将自由变形(Free form deformation, FFD)技术引入汽车气动减阻优化设计中,为减阻优化设计提供一种快速、有效的参数化方法。当前的研究以某款轿车模型为研究对象,根据优化的拉丁方试验设计构建样本空间,并采用FFD方法对各样本点模型进行参数化;通过CFD仿真获得各样本的气动阻力系数;采用Kriging模型构建近似模型;利用多岛遗传算法求解近似模型的最优值;根据优化结果重新构建最优模型并采用CFD计算其气动阻力系数。计算结果显示优化后轿车模型的气动阻力系数减少了4.09%,表明FFD方法在汽车气动减阻优化中有很好的应用效果。

关键词: CFD仿真, FFD, Kriging模型, 气动减阻

Abstract:

:At present, the most common approach for vehicle aerodynamic drag reduction is trial and error method, which completely depended on the engineers’ experience. Inevitably, this method is certain blindness and low efficiency. Moreover, it is quite difficult to parametrize the auto body in the aerodynamic optimization design. To solve these problems, a fast and effective parametrization method named free form deformation (FFD) is introduced into the vehicle aerodynamic optimization design. Firstly, selecting a car model as the simulation object, sample space is constructed based on the optimal Latin hypercube experiment design, and FFD method is used to parameterize the model of each sample point. Secondly, the aerodynamic drag coefficient of each sample is obtained by CFD simulation. Then, according to the sample space and computational results obtained by CFD, Kriging model is selected to build the approximate model. Finally, the multi-island genetic algorithm is employed to get the optimal combination of the design variables. To validate the reliability of the final results, a new model is reconstructed according to the results of the optimization, and aerodynamic drag coefficient is computed by CFD again. The computational results show that the car model aerodynamic drag coefficient has decreased by 4.09% after optimization, which confirms that FFD method deserves to be popularized in vehicle aerodynamic optimization design.

Key words: CFD simulation, FFD, Kriging approximate model, aerodynamic drag reduction