Grey Wolf Optimization Algorithm for Tuning PI Controller Based Speed Control of Switched Reluctance Motor for Ship Propulsion Systems

Abstract

Electric ship propulsion is no longer a revolutionary idea in the marine sector today. Lights were the first thing that needed electricity on board a ship, and it later applied to an electric ship propeller that is powered by an electric motor. Eventually, the idea of all-electric ships enters the picture, allowing all ship power sources to run both auxiliary and propulsion loads. Due to the great electric power constraints, numerous electric motors are used in industrial and naval ships, and the development of power electronics has made it easier to manage and regulate these motors. The switching resistance motor is becoming more popular despite its low dependability and straightforward design. Such benefits make SR motors superior to conventional adjustable speed devices. Due to their significant torque fluctuations, variable reluctance motors have recently been used in restriction traction systems. On the other side, torque ripple reduces motor performance by generating repeated noise and vibration. The suggested system controls the speed of an 8/6 pole SRM using a metaheuristic Grey Wolf Optimization Algorithm (GWO), Proportional Integral (PI) controller, and a (n+1) Semiconductor (n+1) Diode power conversion. This article's goal is to increase the proposed Switched Reluctance Motor's output cogging torque. GWO algorithm has been chosen as a promising strategy when compared to other algorithms because of its generality, decreased complexity, stability, and accuracy. MATLAB/Simulink was used to create the simulation tool.