Estimation of Hot Resistance for Switched Reluctance Motor using Neural Network

Variable speed drives is one of the significant areas of research in the field of industrial drives. From the published literatures, it is observed that permanent magnet synchronous motors, induction motors and switched reluctance motors are best suited for variable speed industrial drive applications. The loading capacity and the life time of motors are mainly determined by the temperature of the motor. The change in the winding resistance increases the winding temperature of the motor that affects the performance of the motor. Therefore, it is of utmost importance to monitor the winding temperature of the motor. In this work, the temperature of the winding for Switched reluctance motor (SRM) is predicted using hot resistance method. The hot resistance of the winding is modeled using Artificial Neural Network (ANN). The ambient temperature, cold resistance and temperature rise are taken as input parameters. The predicted output agrees well over the whole range of test parameters. Therefore, this implies the success of ANN modeling.