4WD电动车滑转率识别及防滑控制研究

实时地根据路面附着状况选择最优的滑转率控制目标是电动车驱动防滑控制策略的关键。针对双转子电机四轮驱动电动车的特点，本文首先采用自适应Kalman滤波估计车速信息和轮胎驱动力信息并利用该信息实时计算出附着率－滑转率曲线的斜率k，以对路面附着状况进行准确评估。以估计的路面信息和踏板输入信息为模糊控制器输入，利用带速度修正因子的模糊控制方法对驱动电机输出转矩进行控制以提高电动车在各种道路条件下最大地利用附着系数的能力，获得最佳的驱动防滑控制效果。

Study on 4WD Electric Vehicle Longitudinal Slip Identification and Traction Control

To choose the optimized slip control targets for the various road conditions in real time is the key of the effect of traction control strategy for electric vehicle (EV). Aiming at the traits of the Anti-Directional Bi-Rotor motor four-wheel drive EV, an adaptive Kalman filter is applied to gain the information of vehicle velocity and traction forces on four wheels. With the estimated vehicle velocity and the driving forces on four wheels, the slope k of the curves of adhesion coefficient versus slip rate could be calculated and consequently the road adhesion condition can be identified accurately. With the input variables both the estimated road conditions and the pedal input, a fuzzy control strategy with the velocity correctional factors is applied. The strategy can improve the capability of utilizing the adhesion coefficient furthest on various road conditions by the EV and therefore, an optimal effect of anti-slip can be achieved.