Interior Permanent Magnet Synchronous Motor (IPMSM) Adaptive Genetic Parameter Estimation

Abstract

Abstract- Interior permanent magnet synchronous motors (IPMSMs) are receiving increased attention for high performance drive applications because of their high power density, high efficiency and flux weakening capability. However, their high efficiency characteristic is influenced by applied control strategies. Thus much effort has been directed towards the efficiency optimization of the IPMSM by minimizing motor copper loss.This loss is influenced by machine parameters. Thus online estimation of these parameters is essential. On the other hand Genetic Algorithm (GA) is a tool for optimization and can be used for solving some problems that can be formulate in those forms that this algorithm can handle it. In this paper we formulate nonlinear state equation of this motor in such form that we can use GA for estimating the unknown parameters. Simulation results show that the estimated parameters converge to correct values after several iterations. Index Terms — Genetic algorithm; parameter estimation; nonlinear system; IPMSM; copper loss; efficiency.