Proper orthogonal decomposition versus Krylov subspace methods in reduced-order energy-converter models

被引：0

作者：

Hasan, M. D. Rokibul ^{[1
]}

Sabariego, Ruth V. ^{[1
]}

Geuzaine, Christophe ^{[2
]}

Paquay, Yannick ^{[3
]}

机构：

[1] Katholieke Univ Leuven, EnergyVille, Leuven, Belgium

[2] Univ Liege, ACE, Liege, Belgium

[3] FRS FNRS, Brussels, Belgium

来源：

2016 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON) | 2016年

关键词：

Reduced-order model; proper orthogonal decomposition; Krylov subspace methods; finite elements; eddy currents; TRANSFORMERS;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this paper, the proper orthogonal decomposition and the Arnoldi-based Krylov subspace methods are applied to the magnetodynamic finite element analysis of power electronic converters. The performance of these two model order reduction techniques is compared both in frequency and time domain. Moreover, two original, adaptive and automated greedy snapshots selection methods are investigated using either local or global quantities for selecting the snapshots (frequencies or time steps).

引用

页数：6

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