Novel MRAS approach for online identification of key parameters for self-sensing control of PM synchronous machines

Some of the remaining challenges of self-sensing control for permanent magnet synchronous machines (PMSM) are: combination of EMF-based and magnetic saliency-based methods, influence of the fundamental current control on saliency-based methods, position-transducerless system identification of key parameters and reduction of computational effort. The authors present a novel Model Reference Adaptive System (MRAS) approach which takes these demands into account. In this paper, the focus is set on identification of key parameters with reduced computational effort. Key parameters like saturation-dependent inductances have a great impact on position estimation, as already reported in the past. As rotor position estimation and parameter identification depend on each other, operating conditions exist where only an ambiguous determination is possible. This demands an appropriate identification strategy which is presented in this paper.