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.