摘要
针对四轮独立驱动电动汽车四轮转矩易于获得的特点,基于无轨卡尔曼滤波(UKF)理论设计了四轮独立驱动电动汽车纵向车速和侧向车速估计算法。该算法利用纵向加速度、侧向加速度和横摆角速度等低成本传感器测量信号,采用带有HSRI轮胎的具有纵向、侧向和横摆运动的非线性三自由度估算模型,实现对四轮独立驱动电动汽车的纵向车速、侧向车速的实时估算。仿真实验结果表明:算法能够准确估算四轮独立驱动电动汽车纵向车速和侧向车速。
The four wheel torque is easy to get in the four--wheel independent drive electric vehicle and the vehicle velocity estimation was studied by Unscented Kalman Filter （UKF）. The velocity estimation algorithm made use of the longitudinal acceleration, and lateral acceleration and yaw rate signals measured by low cost sensors. 3-DOF vehicle estimation model with the HSRI tire model was used. The algorithm was verified by simulation experiment. The results showed that the longitudinal velocity and lateral velocity were estimated accurately using the algorithm.
出处
《机械设计与制造》
北大核心
2013年第9期83-85,共3页
Machinery Design & Manufacture
基金
国家863项目资助(2012AA110904)
