摘要
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防滑控制策略的关键.文中针对双转子电机四轮驱动电动车的特点,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附着率-滑转率曲线的斜率,以对路面附着状况进行准确评估.然后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限度地利用附着系数的能力,获得最佳的驱动防滑控制效果.
The real-time choice of an optimal slip rate control target for various road adhesion conditions is the key component in the traction control strategy for electric vehicle （EV）. In this paper, according to the traits of the four wheel-driven EV with bi-rotor motor, an adaptive Kalman filtering is adopted to estimate the information of vehicle velocity and traction forces on the four wheels. With the estimated information, the slope of the curves of the adhesion coefficient versus the slip rate is then calculated in real time, and, consequently, the road adhesion condition is accurately identified. Then, by taking the estimated road conditions and the pedal input as the controller inputs, a fuzzy control strategy with velocity correction factors is presented to control the output torque of the driving motor. It is demonstrated that the proposed strategy improves the capability of furthest utilizing the adhesion coefficient in various road conditions by the EV and result in an optimal anti-slip effect.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2008年第6期95-100,107,共7页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(50605020)
广东省科技攻关项目(2006A10501001)
关键词
电动车
滑转率
防滑控制
自适应滤波
模糊控制
electric vehicle
slip rate
traction control
adaptive filtering
fuzzy control
