Application of the Extended Kalman Filter to Speed and Rotor Position Estimation of Brushless DC Motor

Abstract

A method for speed and rotor position estimation in a speed control system with a brushless dc motor has been presented in this paper. The extended Kalman filter has been applied to motor state variables and parameter estimation, using only such electric machine variables as can be measured: the stator line voltages and currents. During this procedure the voltage and current measuring signals are not filtered, which is othervise usually done when applying similar methods. The voltage average value during the sampling interval is obtained by combining measurements and calculations, owning to the application of predictive current controller. Estimation accuracy is verified by computer simulation, for which purpose two mathematical models have been made. The use of an actual model drive was simulated and actual motor variables werw obtained. The other model, by means of which estimated variables and parameters are obtained, is based on the application of the extended Kalman filter and for this it is necessary to define the discrete time model of the motor. Simulation results show good accuracy of speed and rotor position estimation in steady-state and dynamic conditions.

Božo Terzić

Full Professor | Department of Electrical Drives and Industrial Control

Full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split, with significant contributions in the field of industrial development projects including the design of prototypes of electronic converters used in industrial plants around the world. His research interests are focused on the application of electronic converters in electric drives and renewable energy sources.