Induction motor parameter estimation from manufacturer data using genetic algorithms and heuristic relationships

Abstract

This paper presents a methodology based on genetic algorithms and heuristic relationships for the determination of all parameters of the equivalent circuit of induction motors from manufacturer catalog data. The approach employs the complete steady state model of the motor and aims at the calculation of efficiency, power factor, current, torque and other quantities at any load. The methodology consists of a first stage, in which a search space for the genetic algorithm is determined, and a second stage in which the circuit parameters and auxiliary slip values are determined. Three different types of motors were investigated, with pole number and power varying from 2 to 6 and from 10 hp to 100 hp, respectively. The accuracy is verified based on deviation from catalog data, reference parameter values obtained experimentally and experimental data. Results indicate that the proposed methodology is capable of finding parameter values which fit the catalog data, although the inaccuracy of these data causes deviation from reference parameter values. The used heuristics is shown to reduce the deviation of less sensitive parameters.