Fundamental obstacles to the modeling and simulation of magnetic components are lack of high-fidelity models and exhaustive computational burden. Physics-based magnetic components have been recently proposed that accurately present the higher-order dynamics (e.g., eddy current). However, introduction of hundreds to thousands state variables makes those models computationally intensive. Automated order-reduction techniques facilitate efficient physics-based magnetic model development that helps designers synthesize dynamic behavior of the magnetic component within a tight design cycle. This paper provides an overview of existing order reduction tools and techniques suitable for dynamic characterization of magnetic components.
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