Proper orthogonal decomposition for order reduction of permanent magnet machine model

Mehrnaz Farzam Far, Paavo Rasilo, Floran Martin, Anouar Belahcen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

6 Citations (Scopus)

Abstract

Model order reduction is an approach for reducing size, complexity, and computation cost of mathematical models in numerical simulations. This paper describes the application of proper orthogonal decomposition method, as one of the most efficient model order reduction techniques, in generating lower dimensional model of a permanent magnet machine. In proper orthogonal decomposition, data collected from high-dimensional numerical simulations (called snapshots) are projected onto a set of orthonormal basis functions. Thereafter, these basis functions are combined with the original model equations to build a reduced order model. The comparison of computational results of the original model with the reduced model indicates that the reduced model is able to accurately reproduce both local and global operation quantities of the machine under investigation.
Original languageEnglish
Title of host publication2015 18th International Conference on Electrical Machines and Systems (ICEMS)
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1945 - 1949
ISBN (Electronic)978-1-4799-8805-1
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
Event18th International Conference on Electrical Machines and Systems, ICEMS - Pattaya City, Thailand
Duration: 25 Oct 201528 Oct 2015

Conference

Conference18th International Conference on Electrical Machines and Systems, ICEMS
Abbreviated titleICEMS
CountryThailand
CityPattaya City
Period25/10/1528/10/15

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