Estimation for Tire-Road Adhesion Coefficient Based on PMSM Sensorless Control for Distributed Drive Electric Vehicle

被引:0
作者
Li, Haoran [1 ]
Zhou, Haichao [1 ]
Wang, Guolin [1 ]
Zhang, Rongyun [2 ]
机构
[1] Jiangsu Univ, Sch Automot & Traff Engn, Automobile Engn, Zhenjiang 212013, Peoples R China
[2] Anhui Polytech Univ, Sch Mech & Automot Engn, Wuhu 241000, Peoples R China
基金
中国国家自然科学基金;
关键词
Tires; Estimation; Vehicle dynamics; Sensors; Heuristic algorithms; Wheels; Accuracy; Sensorless control; Force; Kalman filters; Active disturbance rejection control (ADRC); permanent magnet synchronous motor (PMSM) sensorless control; seventh-degree cubature Kalman filter (KF) (7thCKF); tire-road adhesion coefficient (TRAC) estimation; vehicle state parameters estimation; ADRC;
D O I
10.1109/JSEN.2025.3537112
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
Accurate estimation of the tire-road adhesion coefficient (TRAC) is important for the vehicle active safety control system to make corresponding control decisions under different driving conditions and road surface conditions. This article, therefore, proposes a TRAC estimation method for distributed drive electric vehicle (DDEV) based on permanent magnet synchronous motor (PMSM) sensorless control. First, for improving the speed control accuracy of PMSM, this article combines sliding mode control (SMC) with active disturbance rejection control (ADRC), and the speed control method for PMSM based on new reaching SMC-ADRC (NRSMC-ADRC) is designed. Second, the seventh-degree cubature Kalman filter (KF) (7thCKF) algorithm is derived based on the seventh-order spherical-radius criterion, and the QR decomposition and memory attenuation (MA) filter are introduced to design the square root seventh-degree cubature Kalman filter with MA (MA-SR7thCKF) algorithm, which ensures the semipositive character of the filtering and solves the problem of degradation of the filtering accuracy due to the excessive use of historical data. The MA-SR7thCKF algorithm is used to estimate the speed of PMSM and vehicle state parameters to reduce the use of sensors and the complexity of the dynamic system. Finally, the estimated vehicle state parameters are used as inputs to the Dugoff model for the calculation of the normalized tire force, and the TRAC is estimated using the MA-SR7thCKF algorithm. The effectiveness of the proposed method is verified under simulation and experiment, the results show that the proposed method has high estimation accuracy.
引用
收藏
页码:15402 / 15418
页数:17
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