基于敏感性分析的悬架多目标优化函数构建方法研究  

Development of multi-objective optimization function of suspension based on sensitivity analysis

作　　者：张飞 石琴 陈一锴 彭成旺 ZHANG Fei;SHI Qin;CHEN Yikai;PENG Chengwang(School of Automobile and Traffic Engineering,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学汽车与交通工程学院

出　　处：《合肥工业大学学报（自然科学版）》2020年第1期14-19,25,共7页Journal of Hefei University of Technology：Natural Science

基　　金：国家自然科学基金资助项目(71431003;51305117)

摘　　要：文章构建了前轮定位参数与轮胎磨损、回正力矩的数学模型,采用敏感性分析定量研究了前轮定位参数对回正力矩、轮胎磨损的影响程度,分别确定出高、低速工况下主销后倾角与主销内倾角、外倾角与前束角之间的权重系数;在ADAMS/Car中建立整车仿真模型,并基于整车平顺性试验的仿真数据,分别拟合出高、低速工况下前轮定位参数与其各自静态值之差的绝对值最大值和硬点坐标的响应面函数,进而构建悬架硬点坐标的多目标优化模型,采用多目标粒子群优化(multi-objective particle swarm optimization,MOPSO)算法对悬架硬点坐标进行优化。结果表明,该优化方法能有效减轻轮胎磨损,提高操纵稳定性。The relationship model between tire wear,aligning torque and wheel alignment parameters was established.Then,the sensitivity analysis was used to quantitatively analyze the effects of wheel alignment parameters on aligning torque and tire wear.The weight coefficients between the caster angle and kingpin inclination angle,the camber angle and toe angle were determined respectively in high and low speed conditions.Finally,the model for vehicle was built with ADAMS/Car module,and the response surface functions for the absolute maximum value of the difference between the front wheel alignment parameters and the each static value in low and high speed conditions were fitted on account of the experimental data of ride comfort testing.A multi-objective optimization model for the hard-point coordinates of Mcpherson suspension was constructed,and the hard-point coordinates were optimized with the multi-objective particle swarm optimization(MOPSO)algorithm.The results show that the method proposed in this paper can effectively reduce tire wear and improve vehicle handling stability.

关 键 词：轮胎磨损 回正力矩 权重系数 响应面函数 多目标粒子群优化(MOPSO)算法 

分 类 号：U461.6[机械工程—车辆工程]