基于离散伴随法和试验设计的汽车气动减阻优化
Aerodynamic Drag Reduction Optimization of Automobiles Based on Discrete Adjoint Method and Experimental Design
李文杰 1赵健 1汪怡平 1朱志林1
作者信息
- 1. 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
- 折叠
摘要
为解决当前汽车气动减阻设计中基于工程师经验的试凑法所带来的盲目性与低效性,以及车身曲面难于参数化的问题,作者将离散伴随法和试验设计(Design of Experiment,DOE)引入汽车减阻优化流程,以阶梯背式MIRA模型为研究对象,通过对外流场进行数值计算,根据外流场特性和车辆表面灵敏度分析,确定优化变量;通过DOE创建样本空间,并采用网格变形技术对各优化变量进行参数化;通过CFD仿真获取各样本点的风阻系数;采用Kriging空间插值法来建立近似模型;使用自适应模拟退火算法对模型优化.优化后模型风阻系数较原模型共计降低16 counts,减阻5.4％,表明该方法在汽车气动减阻优化中有较好的减阻效果和可行性.
Abstract
In order to solve the problem of blindness and inefficiency caused by the trial method based on engineers'ex-perience in the current automotive aerodynamic drag reduction design,as well as the difficulty of parameterization of the body surface,this paper introduces the discrete adjoint method and Design of Experiment(DOE)into the automotive drag reduction optimization process.The sample space was created by DOE,and the mesh deformation technique was used to parameterize each optimization variable.The drag coefficient of each sample point was obtained by CFD simulation.The Kriging spatial interpolation method was used to establish the approximate model.The model was optimized using an a-daptive simulated annealing algorithm.Compared with the original model,the drag coefficient of the optimized model is re-duced by 16 counts and 5.4％,indicating that the method has a good drag reduction effect and feasibility in the optimiza-tion of automobile aerodynamic drag reduction.
关键词
气动减阻优化/外流场特性/离散伴随法/试验设计Key words
optimization of pneumatic drag reduction/external flow field characteristics/discrete adjoint method/design of experiment引用本文复制引用
基金项目
湖北省支持企业科技创新发展专项(2021BA015)
湖北省科技重大专项(2021AAA006)
出版年
2024
NETL
NSTL
万方数据