Comparative analysis of metaheuristic algorithms for parameters estimation of single-cage and double-cage induction machine models

Abstract

This paper deals with the estimation of parameters of single-cage and double-cage induction machine models using HBA (Honey Badger Algorithm) and EO (Equilbrium Optimizer) algorithms. The input data for the estimation procedure are the induction machine nameplate data – power factor, starting, rated, and maximum torque. Based on the nameplate data, the criterion function is defined. The applicability of both considered methods is proven by comparing the output characteristics of induction machine determined using parameters estimated with other literature known algorithm. The obtained results demonstrate that the applied algorithm is very efficient, accurate, and precise method for the parameters estimation of single-cage and double-cage induction machine models.