This paper proposes a reduced-order model of power electronic components based on the proper orthogonal decomposition. Starting from a full-wave finite-element model and several snapshots/frequencies, the reduced-order (RO) model is constructed. Local field values (e.g. magnetic flux density, electric current density, magnetic or electric field) and global quantities (e.g. characteristic complex impedance, joule losses) can be determined for the intermediate frequencies with a very low computational cost and high accuracy. Particular attention is paid to the choice of the most suitable snapshots by means of three different greedy algorithms, the performance of which is compared. We adopt an automatic greedy algorithm that only depends on the RO model.
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). Index Terms-Reduced-order model, proper orthogonal decomposition, Krylov subspace methods, finite elements, eddy currents.
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