Nonlinear Identification of PMSM Rotor Magnetic Linkages Based on an Improved Extended Kalman Filter

Abstract

The permanent magnet synchronous motor (PMSM) has complex nonlinear, strongly coupled characteristics and the variation of motor parameters makes its control more difficult. Therefore, parameter identification is of great significance for the stable operation of its closed-loop control system. In this paper, a method based on an improved extended Kalman filter (EKF) for the identification of the rotor flux ( ${\psi }_f$ ) of a permanent magnet synchronous motor is investigated for this nonlinear and strongly coupled model. Simulation results show that the method has a more fast convergence rate and more accurate identification result than traditional EKF algorithm.