摘要
为了降低车辆行驶受路面激励产生振动幅度,采取混合算法优化车辆振动模型.创建1/4车辆振动模型简图,构建车辆垂直方向动力学方程式.设置车辆参数优化目标函数,采用混合算法对1/4车辆振动设计参数进行优化.优化参数变量分别为座椅质量、簧上质量、簧下质量、座椅刚度系数、弹簧刚度系数、轮胎刚度系数、座椅阻尼系数及弹簧阻尼系数.在Matlab软件中建立车辆振动仿真模型,并输出仿真结果,与优化前仿真结果形成对比.仿真曲线显示:优化后的车辆不仅垂直方向的位移、加速度及座椅加速度峰值有所降低,而且振动幅度波动较小.采用混合算法优化车辆被动悬架系统参数,能够抑制车辆行驶受路面激励的干扰,提高车辆行驶的稳定性和舒适度.
In order to reduce vibration amplitude induced by road excitation,a hybrid algorithm is applied to optimize vehicle vibration model.A quarter vehicle vibration model is established,and the vertical dynamics equation of vehicle is built.The objective function of vehicle parameters optimization is constructed,and the hybrid algorithm is applied to optimize the design parameters of quarter vehicle vibration.The parameter variables are the seat quality,the spring quality,the reed quality,the seat stiffness coefficient,the spring stiffness coefficient,the tire stiffness coefficient,the seat damping coefficient and the spring damping coefficient.A vehicle vibration simulation model is set up in mathematical software Matlab,and the simulation results are output,which is compared with the simulation results before optimization.The simulation curve shows that the optimized vehicle not only reduces the vertical displacement,acceleration and seat acceleration peak value,but also has smaller fluctuation amplitude.The hybrid algorithm is used to optimize the parameters of the vehicle passive suspension system,which can restrain the disturbance of the vehicle driving by the road,and improve the stability and comfort of the vehicle.
作者
王秀梅
张庆涛
王雨
WANG Xiumei;ZHANG Qingtao;WANG Yu(Vehicle Engineering College,Changzhou Vocational Institute of Mechatronic Technology,Changzhou 213164,Jiangsu,China;Office of Academic Affairs,Yantai Technical College of Engineering,Yantai 264006,Shandong,China;School of Automotive Studies,Tongji University,Shanghai 201804,China)
出处
《中国工程机械学报》
北大核心
2019年第1期24-28,共5页
Chinese Journal of Construction Machinery
基金
上海自然科学基金资助项目(16ZR14122)
关键词
混合算法
车辆被动悬架
振动模型
优化
仿真
hybrid algorithm
vehicle passive suspension
vibration model
optimization
simulation