摘要
为了更好地改进车辆的气动特性,讨论了一种将参数化建模、CFD计算和数值寻优方法相结合的气动优化方法。设计了一种根据使用工况可调的汽车后扰流器,针对高速行驶和高速制动2种典型工况,对该扰流器的形状和位置进行气动优化。首先对可变后扰流器进行参数化设计,并用拉丁方法对参数化模型进行试验设计,通过CFD计算获取响应值;然后采用Kriging模型构建参数变量与气动特性之间响应关系的近似模型;最后以该模型为基础使用遗传算法对扰流器形状和位置进行优化设计。研究结果表明:优化后的可变扰流器可使整车在高速行驶工况下阻力系数减小3.3%,升力系数减小22.4%;在高速制动工况下,升力系数减小69.9%,整车的气动特性获得了较大的改善。
To improve the aerodynamics of vehicles a method which combined parametric modelling, CFD computing and numerical optimization was presented. A variable rear spoiler, which could be adjusted under different conditions, was designed. The shape and position of this spoiler were optimized under two typical working conditions: high speed driving and high speed braking. The variable rear spoiler was parameterized. Then, the method of Latin was adopted for the design of experiments and the corresponding value was got with CFD computing. An approximate model of parameter variables correspondent with aerodynamics was established using the Kriging model which was subsequently used for executing the optimization of aerodynamics in shape and position with genetic algorithm. The results indicate that the drag coefficient of the optimized vehicle decreases by 3.3%, while the lift coefficient decreases by 22.4% at high speed driving. The lift coefficient of the optimized vehicle decreases by 69.9% at high speed braking. As a result, the aerodynamics of vehicle is significantly improved.
出处
《中国公路学报》
EI
CAS
CSCD
北大核心
2012年第5期146-151,共6页
China Journal of Highway and Transport
基金
国家自然科学基金项目(50975083)
关键词
汽车工程
可变后扰流器
遗传算法
气动优化
KRIGING模型
automobile engineering
variable rear spoiler
genetic algorithm
optimization of aerodynamics
Kriging model