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

Abstract

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.

Modified switching control of SRM drives for electric vehicles application with torque ripple reduction

“…The rotor structure becomes complex and needs precise design aspects like winding connection, arc angle, and saturation conditions, for high level of optimization [30]. Commonly used torque minimization control techniques include PI controllers for speed and torque ripple control [31]. However, this method is less efficient compared to fuzzy logic and neural control [32].…”

Reducing torque ripple of induction motor control via direct torque control

“…However, this technique of control has drawbacks such as flux droop at lower speeds, the inverter having variable losses of switching, and high ripples in current and torque [19]. Hence, adding a new loop for speed with PID controller in order to minimize the torque ripples as well enhancing overall performance [20], [21].…”