Implementation of sensorless speed control of synchronous reluctance motor using extended Kalman filter

Abstract

This paper presents an extended Kalman filter (EKF) based sensorless speed control which was performed for controlling a synchronous reluctance motor (SynRM). Maximum torque per ampere (MTPA) control strategy was used to obtain a maximum electromagnetic torque with lowest current for the motor. In this study, all control parameters were optimized using a particle swarm optimization (PSO) algorithm to achieve the lowest control speed error and the lowest amplitude stator currents with low total harmonic distortion (THD). Also, the optimization was able to achieve the minimum difference between d-q axes currents. The motor was controlled without using a shaft sensor which plays an important role in rotor synchronization. A TMS320F28379D was used as a dual-core microcontroller capable of performing 32-bit floating point operations at 200 MHz operating frequency. The speed estimation algorithm was operated on the other core while the speed control and switching algorithms were operated on the first core. The sampling time for both cores was set to 80us. These two cores were communicated over an internal memory of the microcontroller. Experimental results for both MTPA and EKF-based sensorless algorithms were presented in the paper.

Keywords

• extended Kalman filter
• digital signal processor
• sensorless control
• speed estimation
• synchronous reluctance motor