某微型电动汽车麦弗逊前悬架设计优化  

Design optimization of McPherson suspension for micro electric vehicle

作　　者：高坤明 郭宗和[1] 于瑶瑶 张裕晨 GAO Kunming;GUO Zonghe;YU Yaoyao;ZHANG Yuchen(School of Transportation and Vehicle Engineering,Shandong University of Technology,Zibo 255049,China;School of Materials Science and Engineering,Shandong University of Technology,Zibo 255049,China)

机构地区：[1]山东理工大学交通与车辆工程学院,山东淄博255049 [2]山东理工大学材料科学与工程学院,山东淄博255049

出　　处：《山东理工大学学报（自然科学版）》2020年第3期23-28,33,共7页Journal of Shandong University of Technology:Natural Science Edition

基　　金：山东省自然科学基金项目(ZR2016EEM12)。

摘　　要：针对车辆的车身垂直加速度、悬架动行程以及轮胎动位移性能冲突,采用多目标遗传算法对麦弗逊悬架进行减振控制研究。结合虚位移原理推导出悬架螺旋弹簧刚度的计算公式,并对电动汽车前稳定杆进行受力分析,计算稳定杆各段所产生的弯曲位能和扭转位能,推导出稳定杆线刚度的计算公式,进而计算麦弗逊前悬架侧倾角刚度;采用多目标遗传算法对麦弗逊悬架参数进行优化并进行数值仿真模拟。仿真结果显示,经过多目标优化后的麦弗逊悬架各项性能均优于优化前,显著改善了电动汽车的乘坐舒适性和行驶稳定性。Aiming at the vertical acceleration of the suspension body, the suspension travel and the dynamic displacement performance of the tire, this paper uses the multi-objective genetic algorithm to control the vibration control of the MacPherson suspension. The calculation formula of the stiffness of the suspension coil spring is derived by the virtual displacement principle. The force analysis of the front stabilizer bar of the electric vehicle is carried out. The bending potential energy and the torsional potential energy generated by each section of the stabilizer bar are calculated, and the stiffness of the stabilizer bar is derived. The calculation formula is used to calculate the roll stiffness of the McPherson front suspension. The multi-objective genetic algorithm is used to optimize the McPherson suspension parameters. The simulation results show that the performance of the MacPherson suspension after multi-objective optimization is better than that before optimization, and significantly improves the ride comfort and driving stability of the electric vehicle.

关 键 词：微型电动汽车 麦弗逊悬架 多目标优化 遗传算法 数值仿真 

分 类 号：U463.33[机械工程—车辆工程]