Increasing accuracy of Kalman filter-based sensorless control of wind turbine PM synchronous generator

Wind turbines require periodic maintenance procedures to ensure reliable operation of the system. Regular servicing of the rotor demands calibration of the speed and position sensor in aggravated circumstances of the dynamic wind. This sensor is one of the most critical components for the drive reliability and the calibration greatly increases the time of repair. The main focus of the paper is to eliminate the need for encoder mounted on the generator shaft in wind turbine applications by implementing an algorithm for speed and flux position estimation. Two unscented Kalman filters are used in a dual configuration to ensure both robust and accurate control performance under the variable wind conditions. The estimation algorithm is comprised of stationary frame model-based observer for enabling robust speed estimation, superposed with rotor flux frame model-based observer for fine accuracy tuning of the flux position needed for generator field-oriented control. Experimental results obtained on a scaled laboratory setup show that presented method performs well with improved accuracy of speed and flux position estimation, and ensures smooth performance of sensorless generator control.