A Recursive Prediction Error Method with Effective Use of Gradient-Functions to Adapt PMSM-Parameters Online

This paper proposes a method for online estimation of electrical parameters of interior permanent magnet synchronous machines (IPMSM) based on the recursive prediction error method (RPEM). The parameter-sensitivity functions (herein known as the gradient functions, Ψ T ) both in dynamic and steady -states are exploited for this purpose. The RPEM has been computed using the stochastic gradient algorithm (SGA). The scalar Hessian matrix, r[k] appearing in the algorithm has been analyzed for both its steady and dynamic states. Different combinations of Ψ T and r[k] -states have been simulated and compared with respect to performance when used for parameter adaptation. © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.