Switched reluctance motor control without position sensor by using data obtained from finite element method in artificial neural network

Abstract

Switched reluctance motors (SRMs) require sensitive rotor information in order to work sensitively and properly and especially for the commutation of phase currents. Position information is generally acquired from a sensor which is generally placed into the stator or connected to the rotor. However, sensors have disadvantages in terms of cost, safety, complexity and volume. In order to remove these disadvantages, recent studies concentrate on SRMs working without a position sensor. In this study control methods working without a position sensor are examined, the applied method is presented comprehensively. The education and test data of the artificial neural network is not obtained from simulation or experimental results; it is obtained from magnetic analyses carried out in ANSYS 10 and the results are used in position speed and current sensorless control of SRM. The validity of proposed method is demonstrated by using DS 1103.