Speed-Sensorless model predictive current control of permanent magnet synchronous motors

PErmanent magnet synchronous motors (PMSMs) are widely used in industrial applications and electricvehicles which require high-performance variable torque and speed due to their high efficiency, simplestructure, and wide speed range. In this study, an extended complex Kalman filter (ECKF) based observer is designed for simultaneous estimation of the load torque with the stator stationary axis components of statorcurrents and rotor angular velocity/position required for speed-sensorless model predictive current controlof PMSMs. The designed ECKF observer and model predictive current control system has been tested andvalidated with challenging scenarios under different load torques in a wide speed range including zero speedand speed reversals. In addition, the performance of both the ECKF and the model predictive current control system is analyzed against parameter changes PMSM. The simulation results confirm that the ECKFobserver and the speed-sensorless model predictive current control system using this observer have very highperformance. In addition, the computational burden of the ECKF observer was compared with theconventional extended Kalman filter, which estimates the states and parameters estimated in this study, andit was shown that the processing computational burden decreased