三厢轿车多参数气动优化
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摘要
使用遗传算法开展带内流的车身多参数气动优化,寻找气动性能优异的车身外形。三厢轿车气动阻力系数C_d和进气量的试验和数值仿真结果误差分别约为7%和6%,表明所采用的数值仿真方法正确。比较内流简化模型与真实模型得到进气量和速度云图,可以发现两者差异较小,可以采用内流简化模型进行气动优化。选取车身表面6个关键参数,建立带内流的参数化模型,基于轮盘赌选择法和Taguchi方法的遗传算法开展气动优化,得到了气动阻力系数为0.298的优化模型。对比原始模型与优化模型可以发现,优化模型尾部行李箱盖倾角和离去角均向内收缩。本文所建立的内流简化方法和多参数气动优化方法可为相关车型气动开发提供参考。
A multi-parameters aerodynamic optimization of vehicle body with internal flow is carried out using genetic algorithm.The error of the aerodynamic drag coefficient between the experimental and numerical results is about 6%,indicating that the numerical simulation method is correct.Comparing the obtained intake flow and velocity contour,the difference between the simplified model with internal flow and the real model is small.Therefore,the aerodynamic optimization can be performed using the simplified flow model.Six key parameters of the body surface are selected to build a parameterized model with internal flow.The genetic algorithm based on the roulette wheel selection method and the Taguchi method is used in the aerodynamic optimization.An optimization model with an aerodynamic drag coefficient of 0.298 is obtained.Comparing with the original model,the rear trunk lid dip angle and departure angle obtained with the optimization model both contract inward.The simplified method with internal flow and the multi-parameters aerodynamic optimization method can be used to provide reference for the aerodynamic development of related model of vehicle.
A multi-parameters aerodynamic optimization of vehicle body with internal flow is carried out using genetic algorithm.The error of the aerodynamic drag coefficient between the experimental and numerical results is about 6%,indicating that the numerical simulation method is correct.Comparing the obtained intake flow and velocity contour,the difference between the simplified model with internal flow and the real model is small.Therefore,the aerodynamic optimization can be performed using the simplified flow model.Six key parameters of the body surface are selected to build a parameterized model with internal flow.The genetic algorithm based on the roulette wheel selection method and the Taguchi method is used in the aerodynamic optimization.An optimization model with an aerodynamic drag coefficient of 0.298 is obtained.Comparing with the original model,the rear trunk lid dip angle and departure angle obtained with the optimization model both contract inward.The simplified method with internal flow and the multi-parameters aerodynamic optimization method can be used to provide reference for the aerodynamic development of related model of vehicle.
引文
[1]刘湘云,冯俊虎,郑智贞,等.不同前车窗角度对汽车动力性能影响的数值模拟[J].北京工业大学学报,2009,35(7):987-990.Liu Xiang-yun,Feng Jun-hu,Zheng Zhi-zhen,et al.Effect of different front window angles on the automobile dynamic performances[J].Journal of Beijing University of Technology,2009,35(7):987-990.
[2]Khondge A,Sovani S,Verma G.Automation of vehicle aerodynamic shape exploration and optimization using integrated mesh morphing and CFD[C]∥SAE Paper,2011-01-0170.
[3]Magazoni F,Buscariolo F,Maruyama F,et al.Aerodynamic shape improvement for driver side view mirror of hatchback vehicle using adjoint optimization method[C]∥SAE Paper,2015-36-0156.
[4]郭建成,谷正气,容江磊,等.基于Kriging模型的某轿车前轮阻风板优化[J].郑州大学学报:工学版,2011,32(3):125-128.Guo Jian-cheng,Gu Zheng-qi,Rong Jiang-lei,et al.Optimization of air dam skirts of the front-wheels of a car based on kriging model[J].Journal of Zhengzhou University(Engineering Science),2011,32(3):125-128.
[5]容江磊,谷正气,杨易,等.基于Kriging模型的跑车尾翼断面形状的气动优化[J].中国机械工程,2011,22(2):243-247.Rong Jiang-lei,Gu Zheng-qi,Yang Yi,et al.Aerodynamic optimization of cross sectional shape for a sports car′s rear wing based on kriging surrogate model[J].China Mechanical Engineering,2011,22(2):243-247.
[6]Han T,Kaushik S,Karbon K,et al.Adjoint-driven aerodynamic shape optimization based on a combination of steady state and transient flow solutions[C]∥SAE Paper,2016-01-1599.
[7]Sun S,Chang Y,Fu Q,et al.Aerodynamic shape optimization of an SUV in early development stage using a response surface method[C]∥SAE Paper,2014-01-2445.
[8]Lundberg A,Hamlin P,Shankar D,et al.Automated aerodynamic vehicle shape optimization using neural networks and evolutionary optimization[C]∥SAE Paper,2015-01-1548.
[9]韦甘,杨志刚,李启良.低阻车身形体的参数化建模与气动试验[J].同济大学学报:自然科学版,2014,42(5):769-772,781.Wei Gan,Yang Zhi-gang,Li Qi-liang.A parametric modeling method of low-drag car body and aerodynamic test[J].Journal of Tongji University(Natural Science),2014,42(5):769-772,781.
[10]韦甘,杨志刚,李启良.基于分步遗传算法的车身气动优化[J].吉林大学学报:工学版,2014,44(6):1578-1582.Wei Gan,Yang Zhi-gang,Li Qi-liang.Aerodynamic optimization method for car body based on process costing genetic algorithm[J].Journal of Jilin University(Engineering and Technology Edition),2014,44(6):1578-1582.
[11]Shih T H,Liou W W,Shabbir A,et al.A newk-εeddy viscosity model for high Reynolds number turbulent flows:model development and validation[J].Computers and Fluids,1995,24(3):227-238.
[12]Mckay M D,Beckman R J,Conover W J.Comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J].Technometrics,1979,21(2):239-245.
[2]Khondge A,Sovani S,Verma G.Automation of vehicle aerodynamic shape exploration and optimization using integrated mesh morphing and CFD[C]∥SAE Paper,2011-01-0170.
[3]Magazoni F,Buscariolo F,Maruyama F,et al.Aerodynamic shape improvement for driver side view mirror of hatchback vehicle using adjoint optimization method[C]∥SAE Paper,2015-36-0156.
[4]郭建成,谷正气,容江磊,等.基于Kriging模型的某轿车前轮阻风板优化[J].郑州大学学报:工学版,2011,32(3):125-128.Guo Jian-cheng,Gu Zheng-qi,Rong Jiang-lei,et al.Optimization of air dam skirts of the front-wheels of a car based on kriging model[J].Journal of Zhengzhou University(Engineering Science),2011,32(3):125-128.
[5]容江磊,谷正气,杨易,等.基于Kriging模型的跑车尾翼断面形状的气动优化[J].中国机械工程,2011,22(2):243-247.Rong Jiang-lei,Gu Zheng-qi,Yang Yi,et al.Aerodynamic optimization of cross sectional shape for a sports car′s rear wing based on kriging surrogate model[J].China Mechanical Engineering,2011,22(2):243-247.
[6]Han T,Kaushik S,Karbon K,et al.Adjoint-driven aerodynamic shape optimization based on a combination of steady state and transient flow solutions[C]∥SAE Paper,2016-01-1599.
[7]Sun S,Chang Y,Fu Q,et al.Aerodynamic shape optimization of an SUV in early development stage using a response surface method[C]∥SAE Paper,2014-01-2445.
[8]Lundberg A,Hamlin P,Shankar D,et al.Automated aerodynamic vehicle shape optimization using neural networks and evolutionary optimization[C]∥SAE Paper,2015-01-1548.
[9]韦甘,杨志刚,李启良.低阻车身形体的参数化建模与气动试验[J].同济大学学报:自然科学版,2014,42(5):769-772,781.Wei Gan,Yang Zhi-gang,Li Qi-liang.A parametric modeling method of low-drag car body and aerodynamic test[J].Journal of Tongji University(Natural Science),2014,42(5):769-772,781.
[10]韦甘,杨志刚,李启良.基于分步遗传算法的车身气动优化[J].吉林大学学报:工学版,2014,44(6):1578-1582.Wei Gan,Yang Zhi-gang,Li Qi-liang.Aerodynamic optimization method for car body based on process costing genetic algorithm[J].Journal of Jilin University(Engineering and Technology Edition),2014,44(6):1578-1582.
[11]Shih T H,Liou W W,Shabbir A,et al.A newk-εeddy viscosity model for high Reynolds number turbulent flows:model development and validation[J].Computers and Fluids,1995,24(3):227-238.
[12]Mckay M D,Beckman R J,Conover W J.Comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J].Technometrics,1979,21(2):239-245.