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作 者:张勇[1,2] 石佳琦[2] 谷正气 刘水长[2] 米承继[2] ZHANG Yong;SHI Jiaqi;GU Zhengqi;LIU Shuichang;MI Chengji(State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Hunan University,Changsha 410082,China;Hunan Key Laboratory of Biomass Fiber Functional Materials,Hunan University of Technology,Zhuzhou 412007,China)
机构地区:[1]湖南大学汽车车身先进设计制造国家重点实验室,湖南长沙410082 [2]湖南工业大学生物质纤维功能材料湖南省重点实验室,湖南株洲412007
出 处:《湖南大学学报(自然科学版)》2020年第2期14-20,共7页Journal of Hunan University:Natural Sciences
基 金:湖南省自然科学基金资助项目(2019JJ60063,2019JJ60064);湖南省教育厅重点项目(18A270)。
摘 要:汽车尾部结构气动减阻优化时,各几何特征参数间往往存在此消彼长的现象,使得优化变得盲目而复杂.对此,为探明关键几何参数的交互影响规律,以Ahmed类车体为研究对象,在HD-2风洞试验对标验证基础上,对后背3个主要特征参数进行了CFD仿真研究,并在此基础上,为克服盲目性,应用集成优化平台对尾部特征参数进行优化设计.结果表明,后背倾角角度对减阻的贡献量最大,背部两侧圆角半径次之,后背顶部圆角半径最小;三者的改变对气动阻力的影响都具有非单调性;当后背倾角角度、后背顶部圆角半径和背部两侧圆角半径分别为13°、283 mm、58 mm时,能有效减小气动阻力,减阻率达到11.76%,为具体车型减阻优化研究提供借鉴.In the aerodynamic drag reduction optimization of automobile tail structure,there is a phenomenon between geometrical characteristic parameters,which makes optimization become blind and complex.In order to ascertain the interaction law of the key geometrical parameters,this paper carried the CFD simulation research of the three main characteristic parameters on the back of the Ahmed model on the basis of the HD-2 wind tunnel experiment.In order to overcome the blindness of optimization,the integrated optimization platform was applied to optimize the tail characteristic parameters.The results show that the angle of the back inclination has the greatest contribution to drag reduction,the two sides rounded corners on the back has the smaller contribution,the contribution of the top corner of the back is the smallest.The influence of the change of three variables on the aerodynamic resistance is non-monotonic.When the values of the angle of the back inclination,the top corner of the back and the two sides rounded corners on the back are 13°,283 mm and 58 mm respectively,the drag reduction rate reaches 11.76%.This paper provides a reference for the study of the optimization of drag reduction in specific models.
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