A Framework and an Open-Loop Method to Identify PMSM Parameters Online

Abstract

A method for online adaptation of electric parameters of a rotating machine is proposed herein. The concept adopts the recursive prediction error method (RPEM) for parameter adaptation, that exploits the prediction-error gradient functions (Ψ T ) With the aim of setting a general framework for the cause, the method is systematically demonstrated for online identification of permanent magnet flux linkage (Ψ m ) and stator-winding resistance (R s ) of an interior permanent magnet synchronous machine (IPMSM). Additionally, an experiment to estimate R s at the start-up is presented. The gain-matrix is identified using the stochastic gradient algorithm (SGA). Simulation results validate the rapid convergence performance, adaptability and tuning flexibility of the proposed method.