Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm

Authors : Selcuk EMİROGLU

Pages : 361-369

Doi:10.16984/saufenbilder.1175899

View : 53 | Download : 11

Publication Date : 2023-04-30

Article Type : Research Paper

Abstract :This study investigates a hybrid algorithm between Grey Wolf Optimization insert ignore into journalissuearticles values(GWO); and Cuckoo Search insert ignore into journalissuearticles values(CS); algorithms to find the parameters of induction motors. The parameters of the induction motor have been estimated by using the data supplied by the manufacturer. The problem for parameter estimation of the induction motor is formulated as an optimization problem. Then, the optimization problem is solved by using GWO and hybrid algorithm based on GWO and CS algorithms for the estimation of induction motor parameters. Numerical results show that both algorithms are capable of solving the optimization problem for finding the parameters of induction motor. Also, two algorithms and other algorithms such as Differential Evolution insert ignore into journalissuearticles values(DE);, Genetic Algorithm insert ignore into journalissuearticles values(GA);, Particle Swarm Optimization insert ignore into journalissuearticles values(PSO);, Shuffled Frog-Leaping Algorithm insert ignore into journalissuearticles values(SFLA);, and Modified Shuffled Frog-Leaping Algorithm insert ignore into journalissuearticles values(MSFLA); are compared for the problem. The results show that the hybrid GWO-CS algorithm gives a smaller objective value and closer torque value to the manufacturer’s data than the GWO algorithm and several algorithms for motor 1. Hybrid GWO-CS algorithm gives nearly the same results with GWO algorithm for motor 2.
Keywords : Parameter estimation, induction motors, grey wolf optimization, cuckoo search optimization, hybrid algorithm

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