Certain investigations on speed control techniques for switched reluctance motor drives using novel bio inspired algorithms

Abstract

The Switched Reluctance Motor (SRM) that is popularly used today is an electric motor that works with reluctance torque and has salient poles on the stator and rotor. There is also a basic design and electronic power requirements for machines with adjustable speed AC and DC drives. The main aim of this research is to implement a bio-inspired algorithm based on an asymmetric converter with a PI (Proportional Integral)-PWM (Pulse with Modulation) controller, primarily aimed at reducing SRM torque and speed control. To control the settling time, the controller takes the optimum value of the torque ripple and the square root of the speed error. The proposed study is compared to the three proposed optimization algorithms, CSA (Crow Search Algorithm), IALOA (Improved Ant Lion Optimization Algorithm) and MCSPS (Modified Chaotic Starling Particle Swarm) that controls the reduction of SRM torque and speed when using in Aerospace applications. The problem with this is that the SRM construction with double-salient poles creates a ripple of the output torque, which leads to poor motor speed control. To enhance the values of optimal parameter, apply optimization methods and compare the results of the optimized controller to other common controller results. The motor works simultaneously with two phases during normal operation, but it is designed to satisfy the load specifications of the faulty single-phase and two-phases. A five-phase SRM can ensure efficient operation without influencing the stability of the aircraft when single phase is open. Three types of optimization techniques have been used successfully in the improvement of parameters that controls the speed of SRM. Settling time, Rise time, Steady-state error, Peak Overshoot and Torque ripple parameters can be reduced in this presented method. newline