Torque ripple and noise control of switched reluctance motor using an adaptive fuzzy PI control with the aid of AR algorithm

In recent days switched reluctance motor is widely used for numerous industrial applications due to its simple structure, minimum cost and maximum efficiency. Regardless of numerous exclusive benefits of the switched reluctance motor (SRM), acoustic noise of this motor is high and it is important to accomplish more analysis on the noise lessening, which is the primary goal of this paper. The major causes of acoustic noise in a SRM are torque ripple and radial magnetic force. Since radial magnetic force is highly influential by the design of motor, torque ripple control is analysed in this article for acoustic noise control. Torque ripple control of SRM is proposed using optimization in direct torque control (DTC) method. Nowadays, optimisation plays a crucial role in motor drives for enhanced control. In this paper, artificial raindrop algorithm is proposed in DTC of SRM to minimise torque ripple. Performance of proposed ARA based DTC of four-phase 8/6 SRM is analysed using Matlab and compared with the performance of fuzzy gain scheduling PI controller based DTC