Tire-Road Friction Coefficient Estimation for Distributed Drive Electric Vehicles Using PMSM Sensorless Control

被引:6
|
作者
Zhang, Rongyun [1 ]
Feng, Yongle [1 ]
Shi, Peicheng [2 ]
Zhao, Linfeng [3 ]
Du, Yufeng [1 ]
Liu, Yaming [1 ]
机构
[1] Anhui Polytech Univ, Sch Mech & Automot Engn, Wuhu 241000, Peoples R China
[2] Anhui Polytech Univ, Automot New Technol Anhui Engn & Technol Res Ctr, Wuhu 241000, Peoples R China
[3] Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei 230009, Peoples R China
基金
中国国家自然科学基金;
关键词
Distributed drive electric vehicle; tire-road friction coefficient estimation; PMSM sensorless control; orthogonal transformation; sliding mode control; CUBATURE KALMAN FILTER; REAL-TIME ESTIMATION; STRONG TRACKING; SPEED CONTROL; STATE; BRAKING; SLIP;
D O I
10.1109/TVT.2023.3248866
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Many tire-road friction coefficient estimation methods require the wheel angular speed sensor to provide a signal. In this paper, a tire-road friction coefficient estimation algorithm for distributed drive electric vehicles using permanent magnet synchronous motors(PMSM) sensorless control is proposed to reduce the use of wheel angular speed sensors. The wheel angular speed signal is replaced by the rotor speed signal obtained from PMSM sensorless control. First, the three degrees of freedom vehicle dynamics model and the PMSM mathematical model are established, and a strong tracking cubature Kalman filtering algorithm based on orthogonal transformation (T-STCKF) is derived to overcome the problem that the STCKF algorithm is prone to nonlocal sampling when dealing with high dimensional systems. Second, a PMSM sensorless control system based on the adaptive exponent reaching law of sliding mode control and the T-STCKF algorithm is established, and confirmed its validity. Finally, the feasibility of the proposed algorithm is demonstrated through multicase simulation and experiment and the results shows that the T-STCKF algorithm is more accurate than the STCKF algorithm.
引用
收藏
页码:8672 / 8685
页数:14
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