Reduced-Order Modeling of High-Fidelity Magnetic Equivalent Circuits

Abstract

Magnetic components, such as inductors and transformers, enable short-term energy storage and transfer and are essential for many power electronic converters. Physics-based models of magnetic systems, such as finite element-based models and/or high-fidelity magnetic equivalent circuit (HFMEC) models, accurately represent the magnetic device. However, these models are computationally intensive and hard to formulate. In this paper, an HFMEC approach for laminated and solid magnetic cores is set forth that avoids conventional geometrical simplifications and assumptions of uniform flux density. The proposed dynamic HFMEC model accurately captures the effects of magnetic saturation, high-frequency eddy currents, corner effects, and 3-D effects. The resulting full-order HFMEC models introduce a large set of state variables. Automated linear and nonlinear order-reduction techniques are introduced to extract the desired essential system dynamics, thus preserving both model accuracy and computational efficiency. The resulting reduced-order models are validated with hardware measurements and the original full-order HFMECs in both time and frequency domains.