中文摘要：

以非线性八自由度车辆模型为基础,利用轮毂电机驱动电动汽车四轮转矩容易获得的独特优势,将车轮转角、各个车轮驱动力矩、侧向加速度及横摆角速度作为算法输入,采用扩展卡尔曼滤波（Extended Kalman Filter,EKF）理论设计了轮毂电机驱动电动汽车行驶中状态估计算法。CarSim和Matlab/Simulink联合仿真结果表明,该算法能有效估计轮毂电机驱动电动汽车行驶中的纵向车速、侧倾角、侧倾角速度等状态。

英文摘要：

A state estimation algorithm with the extended Kalman filter （EKF） was developed for in-wheel motor electric vehicles based on an 8-Dof nonlinear vehicle dynamic model. Since the wheel＇s torque could easily be measured, the wheel angle, wheel drive torque, lateral acceleration and yaw rate were taken as the algorithm inputs.The effectiveness was verified based on the simulation by using CarSim in combination with Matlab/Simulink. The results show that the algorithm can accurately estimate in-wheel-motor electric vehicle states, such as longitudinal speed, roll angle, roll angular velocity; etc.