Sensorless Control of Permanent Magnet Synchronous Motor Based on Extended Kalman Filter

Abstract A discrete mathematical model of a permanent magnet synchronous motor (PMSM) is established, then the fifth-order cubature Kalman filter (CKF) algorithm is introduced. A Gauss–Newton iterative method is introduced into the iterative process of the fifth-order CKF algorithm to generate the innovation variance and covariance. Therefore, an iterative fifth-order CKF algorithm is proposed as the basis of a PMSM sensorless control is implemented. Then, a PMSM sensorless control based on the iterative fifth-order CKF algorithm is applied to an electric power steering (EPS) system, whose control system is constructed by adopting the typical assist and return control strategy. Finally, to verify the performance of the proposed PMSM sensorless control method, the EPS system model of the PMSM sensorless control is built by using the common phase-locked loop (PLL), the CKF algorithm, the fifth-order CKF algorithm, and the proposed iterative fifth-order CKF algorithm. The simulation analyses and the experimental tests show that the proposed iterative fifth-order CKF algorithm can estimate the PMSM speed with good accuracy and has a strong resistance to disturbances in the load and speed. The assist and return performances of the EPS system are also improved.

Download Full-text

Research on sensorless control method of permanent magnet synchronous motor based on iterated cubature Kalman filter

Science Progress ◽

10.1177/0036850419890272 ◽

2019 ◽

Vol 103 (1) ◽

pp. 003685041989027

Author(s):

Shi Peicheng ◽

Wang Chen ◽

Zhang Rongyun ◽

Wang Suo

Keyword(s):

Kalman Filter ◽

Permanent Magnet ◽

Sensorless Control ◽

Permanent Magnet Synchronous Motor ◽

Estimation Method ◽

Synchronous Motor ◽

Position Estimation ◽

Motor Speed ◽

Rotor Position ◽

Cubature Kalman Filter

Aiming at the problems of high cost, increased volume, low reliability, and environmental interference caused by sensor installation on permanent magnet synchronous motor, estimation method for motor speed and rotor position is proposed based on iterated cubature Kalman filter algorithm and applied to permanent magnet synchronous motor sensorless control. First, discrete mathematical model of permanent magnet synchronous motor in α-β coordinate system is established. Then, based on cubature Kalman filter and iterated cubature Kalman filter, simulation model of sensorless vector control system with dual closed-loop of permanent magnet synchronous motor speed and current is established. Also, simulation verification of two working conditions with given rotation speed and load is carried out. Finally, hardware experimental verification platform is built based on TMS320F28335 chip. Both simulation analysis and experimental results show that iterated cubature Kalman filter application to sensorless control of permanent magnet synchronous motor demonstrates good anti-load variation interference, stable motor operation, high motor speed and rotor position estimation accuracy, which suits the application with high requirement for precise motor control and mean important reference value and promotion significance.

Download Full-text