Sensorless Vector Control of an IPMSM using Unscented Kalman Filtering

This paper presents a sensorless vector control of an interior permanent magnet synchronous motor (IPMSM) using unscented Kalman filtering (UKF) for speed and position estimation. The UKF algorithm represents a serious alternative to the extended Kalman filter (EKF) for the highly nonlinear systems because there is no more need for determining the Jacobian matrix of the system. In this context, generally forsaken for the dq synchronous model, the alphabeta stationary model becomes a viable option in applying the UKF for speed and position estimations of an IPMSM. The modeling of the sensorless vector control in Matlab/Simulink environment including UKF algorithm is exposed. The effectiveness of this method is verified through various simulations and experimental validation on Envitech´s motor test bench