Dynamic Performance Enhancement and Comparative Analysis of Fault Tolerant Five Phase Induction Motor using PSO and GWO Algorithms

Abstract

The multiphase induction motor is a highly preferable choice for the electric vehicle application where the reliability and safety of passengers are one of the major concerns. In such safety critical applications, it is necessary to have the smooth speed transition under the occurrence of fault with minimum disturbance in the system. Therefore this paper proposes GWO (Grey Wolf Optimization) based optimal speed controller, which deals with fault tolerant mode of operation in rotor field oriented controlled (RFOC) five phase induction motor (FPIM). In this paper an open phase fault on FPIM is considered due to leg switches failure in the power electronic converter. It is modeled by applying back EMF calculation in faulty phase, which minimizes the controller reconfiguration under fault. The motive of the paper is to optimize the speed controller gains to enhance the controller performance against the uncertainties of fault occurrence and application of fault tolerant technique in FPIM. Hence this work proposes an application of GWO (Grey Wolf Optimization) algorithm to finely tune speed controller gains which will generate optimal torque reference under all such disturbances. The superiority of algorithm is proved by comparing its performance with standard PSO (Particle swarm optimization) algorithm under healthy, faulty and fault tolerant modes of operations. The comparative analysis of both the algorithms is presented considering their convergent time, number of parameters needed as well as time response parameters and calculation of various performance indices under different modes of operations. The simulation results and comparative analysis prove the effectiveness of GWO algorithm to enhance different speed tracking performances under healthy, faulty and fault tolerant modes of operation.