Rotor Position Estimation of Sensorless PMSM Based on Extented Kalman Filter

被引：0
|
作者：
Tian, Gao [1 ]
Yan, Yang [1 ]
Jun, Wang [1 ]
Ru, Zhou Yu [2 ]
Peng, Zhao Xiao [2 ]
机构：
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian, Shaanxi, Peoples R China
[2] FACRI, Sci & Technol Aircraft Control Lab, Xian, Shaanxi, Peoples R China
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS, ROBOTICS AND AUTOMATION (ICMRA) | 2018年
关键词：
permanent magnet synchronous motor(PMSM); extented Kalman filter(EKF); sensorless; position estimation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Taking permanent magnet synchronous motor as the research object, a rotor position estimation algorithm based on extended Kalman filter algorithm is proposed. According to this algorithm, the PMSM control system can estimate the position and speed of the rotor on line by measuring the phase current of the motor winding to realize the space vector control of the sensorless permanent magnet synchronous motor. The simulation model of permanent magnet synchronous motor is established, and the feasibility of the algorithm is verified. Finally, the algorithm is implemented on the experimental platform of the motor control system. The experimental results show that the algorithm proposed in this paper can estimate rotor position and speed in real time and high accuracy. This algorithm is used for space vector control with wide speed range and stable operation of motor control system.
引用
收藏
页码：12 / 16
页数：5
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