Electric Vehicle Tire Slip Identification Method Based on Self-adaptive Kalman Filter

摘要：

　　Based on the traits of the four-wheel drive EV,a self-adaptive Kalman filter was 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 could be accurately identified.Through calculating the difference between the estimated slope k with the optimized slope k as a control reference,the output torques of the motors were adjusted instantaneously to improve the using rate of the adhesion as well as the rationality of the traction control strategy.Simulation results illustrate that whether on high adhesion or low adhesion roads the vehicle is passing,the strategy can estimate the k effectively.

关键词： slip identification electric vehicle self-adaptive filter

作者: Zhou Sijia Long Jiangqi Xia Jingyan Su Zhonggen

作者单位: Wenzhou University,Wenzhou 325035,China

会议类型: 国际会议

会议名称: the 2012 2nd International Conference on Frontiers of Manufacturing Science and Measuring Technology (第二届制造科学与检测技术国际会议(ICFMM 2012))

会议地点: 西安

会议语种:英文

页码: 1070-1073

在线出版日期: 2012-06-12（万方平台首次上网日期，不代表论文的发表时间）