Comparison of evolutionary algorithms for estimation of parameters of the equivalent circuit of an AC motor

Abstract

This work shows the comparison of three evolutionary algorithms used to estimate the parameters of the equivalent circuit of a three-phase induction motor. The evolutionary algorithms utilized are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and, Bacteria Foraging Optimization (BFO). The number of executions needed to obtain confident results is calculated using statistical methods. With this value, each algorithm is used to estimate the parameters of the equivalent circuit of AC motor and, a comparison is done to select the best technique to use in a device which will estimate the efficiency of an AC motor at its operation place. The simulations show that a good selection to this application is the PSO technique.