A Computationally-Efficient Analytical Model for SPM Machines Considering PM Shaping and Property Distribution
Nowadays, various analytical models (AMs) have been developed to analyze SPM machines with magnet shaping technique consideration, but their mechanism are all based on division and superposition theory, and numerous repetitive model calculations are required, which greatly attenuates the inherent sp...
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Published in | IEEE transactions on energy conversion Vol. 39; no. 2; pp. 1034 - 1046 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.06.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 0885-8969 1558-0059 |
DOI | 10.1109/TEC.2024.3352577 |
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Summary: | Nowadays, various analytical models (AMs) have been developed to analyze SPM machines with magnet shaping technique consideration, but their mechanism are all based on division and superposition theory, and numerous repetitive model calculations are required, which greatly attenuates the inherent speed superiority of AMs. In this article, a new fast AM is proposed, which can analytically solve the magnetic field generated from an arbitrary number of currents to obtain the magnetic field solution for shaping PM without any repetitive model calculation. Besides, five existing typical AMs considering shaping PMs are implemented and compared with the new model, viz., radial and tangential PM segmented method, traditional equivalent current method, and conformal mapping models. The comparison study investigates the adjustable model parameters, the dimension of the stiffness matrix, the number of repetitive model calculations, and the actual time consumption. Then, by finite element model validation, the new proposed model can maintain high accuracy and breakneck computational speed simultaneously. Ultimately, the broad application scope and rich added value of new AM are also expounded. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0885-8969 1558-0059 |
DOI: | 10.1109/TEC.2024.3352577 |