摘要
基于车辆悬架系统模型设计了Kalman滤波器,由测量的车身和车轮加速度信号估计振动速度。分析了过程噪声协方差不准确对速度估计效果的影响,然后讨论了基于预测滤波器的自适应Kalman滤波器。仿真结果表明:Kalman滤波器能够实时准确估计车辆振动速度;预设过程噪声协方差值不准确对车身速度估计影响较大,甚至可能使滤波器失效;自适应Kalman器能够修正过程噪声协方差不准确引起的估计误差,获得准确的车辆振动速度。
Based on the vehicle suspension system model,a Kalman filter was designed to estimate the vibration velocity by measuring the sprung mass accelerations and unsprung mass accelerations.The influence of the covariance matrix of process noise on vibration velocity estimation was analyzed.Then an adaptive Kalman filter based on predictive filter was discussed.The simulation results show that the designed Kalman filter can accurately estimate the vehicle vibration velocity in real time.The inaccuracy of process noise covariance matrix has larger influence on body velocity estimation,or even makes the filter fail.The adaptive Kalman filter can compensate the estimation error caused by the unknown process noise covariance and obtain accurate vehicle vibration velocity.
出处
《振动与冲击》
EI
CSCD
北大核心
2014年第13期111-116,共6页
Journal of Vibration and Shock
基金
国家自然科学基金(51205021)
