This paper proposes a complete saturation model of the Synchronous Reluctance Motor (SynRM), accounting for both the self-saturation and cross-saturation effects. This model is based on an analytical relationship between the stator flux and current components, and is characterized by parameters presenting an interesting physical interpretation, differently from many other saturation model in the scientific literature. It proposes also an identification technique of such a model based on stand-still tests, without the need of locking the rotor. The proposed saturation model permits the complete description of the magnetic behaviour of the machine with 8 parameters, fewer than those required by other models in the scientific literature. Finally, the parameters of this model have been retrieved by a adopting Genetic Algorithm (GAs). The proposed identification technique has been tested in both numerical simulation and experimentally on a suitably developed test set-up. Experimental results clearly show a good superimposition between the measured stator flux components and those computed with the proposed saturation model, by using the identified parameters.

Accetta, A., Cirrincione, M., Pucci, M., Sferlazza, A. (2018). A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms. In IEEE Energy Conversion Congress and Exposition (pp. 4460-4465). Institute of Electrical and Electronics Engineers Inc. [10.1109/ECCE.2018.8558250].

A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms

Sferlazza, Antonino
2018-01-01

Abstract

This paper proposes a complete saturation model of the Synchronous Reluctance Motor (SynRM), accounting for both the self-saturation and cross-saturation effects. This model is based on an analytical relationship between the stator flux and current components, and is characterized by parameters presenting an interesting physical interpretation, differently from many other saturation model in the scientific literature. It proposes also an identification technique of such a model based on stand-still tests, without the need of locking the rotor. The proposed saturation model permits the complete description of the magnetic behaviour of the machine with 8 parameters, fewer than those required by other models in the scientific literature. Finally, the parameters of this model have been retrieved by a adopting Genetic Algorithm (GAs). The proposed identification technique has been tested in both numerical simulation and experimentally on a suitably developed test set-up. Experimental results clearly show a good superimposition between the measured stator flux components and those computed with the proposed saturation model, by using the identified parameters.
2018
Settore ING-INF/04 - Automatica
9781479973125
Accetta, A., Cirrincione, M., Pucci, M., Sferlazza, A. (2018). A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms. In IEEE Energy Conversion Congress and Exposition (pp. 4460-4465). Institute of Electrical and Electronics Engineers Inc. [10.1109/ECCE.2018.8558250].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/339720
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