摘要
重型货车的载重变化会引起重心高度发生明显漂移,而准确、及时地获取车辆重心高度,对于车辆主动安全系统至关重要.文中基于无迹卡尔曼滤波方法,结合车辆三自由度动力学模型,通过传感器采集车速、前后轮速等,实现对车辆重心高度的在线估计.通过TruckSim与MATLAB/Simulink的联合仿真实验表明,车辆重心高度的估计结果能在较短时间内逼近真实值,且稳态平均误差控制在12%以内,对车辆主动安全控制具有重要意义.
The height of the Center of Gravity （CG） for heavy-duty vehicles will drift apparently when the load changes, while the accurate and real-time recognition of vehicle＇s CG height is of extremely importance to the vehicle＇s active safety system. An unscented Kalman filter based on three degree of freedom （3-DOF） vehicle dynamics model is proposed to acquire the real time value of vehicle CG height through sensing the vehicle speed, front and rear wheel speed etc. The results of combined simulation studies based on TruckSim and MATLAB/Simulink show that the estimation algorithm is able to obtain to the true value of CG height in a short time with steady-average error less than 12%. The results are instructive for the dynamic control of driver assistance system.
出处
《武汉理工大学学报（交通科学与工程版）》
2016年第4期623-627,共5页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
"十二五"国家科技支撑计划课题专项经费(2014BAG01B03)
湖北省自然科学基金项目(2015CFB252)
车路协同与安全控制北京市重点实验室开放基金项目(KFJJ-201401)资助
关键词
重心高度
参数估计
无迹卡尔曼滤波
车辆动力学
center of gravity height
parameter estimation
unscented Kalman filter
vehicle dynamics
