Improving power factor in switched reluctance motor drive system by optimising the switching angles

Abstract

Switched reluctance motor can be used in many industrial applications. It is simple to construct and has salient pole stator and rotor. The rotor does not have any winding, commutators and brushes. This drives provide high reliability fast dynamic response and fault tolerance. But this SRM drives suffer from the disadvantage of having low power factor. The low power factor result in high losses in power system. To improve the power factor of SRM drives the turn-on angle and turn-off angle are optimized using adaptive neuro-fuzzy controller. The switching angles (the turn-on and turn-off angle) are flexible control parameters for SRM drives. The switching angles have a great effect on the efficiency of SRM drives and the efficiency also can be improved by adjusting the switching angles. Power factor in the SRM drive is dependent upon the switching angles. Therefore, this paper attempts to improve the power factor by adjusting the switching angles rather than using hardware circuits. Adaptive neuro fuzzy controllers combine the expert knowledge of the fuzzy inference system and the learning capability of neural networks. By applying Adaptive neuro fuzzy controllers to a SRM gives better performance and high robustness than those obtained by the application of a conventional controller.