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

Accetta, A. and Cirrincione, Maurizio and Pucci, M. and Sferlazza, A. (2018) A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms. [Conference Proceedings]

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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.

Item Type: Conference Proceedings
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Fulori Nainoca
Date Deposited: 13 Jan 2020 16:23
Last Modified: 13 Jan 2020 16:23
URI: http://repository.usp.ac.fj/id/eprint/11915
UNSPECIFIED

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