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Synchronous Reluctance Motor Iron Losses: Analytical Model and Optimization

Mahmoud, Hanafy; Degano, Michele; Bacco, Giacomo; Bianchi, Nicola; Gerada, Chris

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Authors

Hanafy Mahmoud

Giacomo Bacco

Nicola Bianchi



Abstract

The complex rotor structure of synchronous reluctance machines causes a high harmonic content in the air-gap flux density and then flux density fluctuations in different iron parts. The importance of determining accurately the total iron losses in the whole motor structure is crucial even during the first design stage. An analytical model is presented to predict the total iron losses as well as the average torque and ripple. Then, an optimization approach is applied to such a model to improve the motor performance. In addition, in several applications a field weakening is required to extend the speed range of the motors. Therefore, it is important to design and optimize the machine not only considering the base speed working point, but also the field weakening operation. An optimization process is applied to two different operating conditions, simultaneously, applying the fast analytical synthesis. The validation of the model accuracy is assessed by means of finite element analysis.

Conference Name 2018 IEEE Energy Conversion Congress and Exposition (ECCE)
Conference Location Portland, Oregon, USA
Start Date Sep 23, 2018
End Date Sep 27, 2018
Acceptance Date May 1, 2018
Online Publication Date Dec 6, 2018
Publication Date Dec 3, 2018
Deposit Date Oct 30, 2018
Publicly Available Date Nov 1, 2018
Publisher Institute of Electrical and Electronics Engineers
Pages 1640-1647
Series ISSN 2329-3748
Book Title 2018 IEEE Energy Conversion Congress and Exposition (ECCE)
ISBN 978-1-4799-7313-2
DOI https://doi.org/10.1109/ECCE.2018.8558292
Public URL https://nottingham-repository.worktribe.com/output/1211388
Publisher URL https://ieeexplore.ieee.org/document/8558292
Additional Information © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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