Parameters identification of a thermal model for a three-phase induction motor using genetic algorithm

Abstract

Genetics algorithms are an alternative way to identify the parameters of an induction motor thermal model. Initially, this work briefly describes the concepts related to electric motors thermal models and the key concepts of genetic algorithms. Then it presents a simplified model for an M3558 Baldor motor, 2 HP, 230V, 60 Hz, the thermal model have two nodes, a set of differential equations and its analytical solutions is derived for each one. To determine the parameters of the thermal model, a genetic algorithm is fed with the calculation of motor losses and temperatures captured by a tests bench. The genetic algorithm changes each parameter of the analytical solution until adjustment criteria are met. At the end of this work, the thermal capacitances and inductances obtained are compared with theoretical calculations of the physical constants of the motor. We demonstrate that the parameters obtained with genetic algorithms fit better to the data and require little knowledge of the magnitude and physical constants related to the motor.