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

Antonino Sferlazza, Angelo Accetta, Marcello Pucci, Maurizio Cirrincione

Research output: Contribution to conferenceOtherpeer-review

8 Citations (Scopus)

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.
Original languageEnglish
Pages4460-4465
Number of pages6
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

Fingerprint Dive into the research topics of 'A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms'. Together they form a unique fingerprint.

Cite this