Proper orthogonal decomposition for order reduction of permanent magnet machine model

M. Farzamfar*, P. Rasilo, F. Martin, A. Belahcen

*Corresponding author for this work

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

8 Citations (Scopus)


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 publicationProceedings of the 18th International Conference on Electrical Machines and Systems, ICEMS 2015
Number of pages5
ISBN (Print)9781479988044
Publication statusPublished - 18 Jan 2016
MoE publication typeA4 Conference publication
EventInternational Conference on Electrical Machines and Systems - Pattaya City, Thailand
Duration: 25 Oct 201528 Oct 2015
Conference number: 18


ConferenceInternational Conference on Electrical Machines and Systems
Abbreviated titleICEMS
CityPattaya City
Internet address


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