Novel Bio-Inspired Algorithm for Speed Control and Torque Ripple Reduction of Switched Reluctance Motor in Aerospace Application

Abstract

Switched Reluctance Motor (SRM) is an electrical motor which operates by a reluctance torque that has stator and rotor salient poles. It also has a simple configuration and reasonable power electronics necessity for both AC and DC machines within adjustable-speed drives. The problem working on it is, SRM with doubly salient poles introduce a torque ripple in its output which leads to deteriorated performance on speed control. In this proposed work, torque ripple reduction and speed control of SRM is implemented, utilizing an asymmetrical converter with PI-PWM controller with the aid of Bio-inspired algorithms. By utilizing the best value of flux, torque ripple and integral square error of speed and settling times, controller design is performed. The proposed research work compares three optimization algorithms namely Crow Search Algorithm, an Improved Ant Lion Optimization Algorithm and Modified Chaotic Starling Particle Swarm technique to control the speed and torque reduction of SRM in aerospace applications. To obtain the optimal parameter values, optimization techniques are introduced and the optimized controller results are compared with other conventional controller results. In normal operation, the engine operates with two phases simultaneously, but it is modelled to meet the load specification, which is single and double phase faulty. Detection of fault gives a great outcome in control of an electrical drive system. Reduction of faulty operation time leads to better motor lifetime that is obtained by early detection of a fault. This paper presents how the five-phase switched reluctance motor is designed to meet the needs of flap actuators in mid-sized aircraft. Electrical systems are modelled to provide the right functionality at the right time in advanced aircraft. However, requirement of power for the landing gear and secondary flight control only a short duration. The system is powered on and off as required, thus preserving power. Control performance and fault analysis were verified by the results of the MATLAB simulation. Experiments have been carried out more effectively to compare the results obtained with those of simulations.