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Why MagNet: Quantifying the Complexity of Modeling Power Magnetic Material Characteristics

Author(s): Chen, Minjie; Serrano, Diego; Li, Haoran; Wang, Shukai; Guillod, Thomas; et al

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dc.contributor.authorChen, Minjie-
dc.contributor.authorSerrano, Diego-
dc.contributor.authorLi, Haoran-
dc.contributor.authorWang, Shukai-
dc.contributor.authorGuillod, Thomas-
dc.contributor.authorLuo, Min-
dc.contributor.authorBansal, Vineet-
dc.contributor.authorJha, Niraj-
dc.contributor.authorChen, Yuxin-
dc.contributor.authorSullivan, Charles R.-
dc.identifier.citationChen, Minjie. (Why MagNet: Quantifying the Complexity of Modeling Power Magnetic Material Characteristics. 10.36227/techrxiv.21340989.v3en_US
dc.description.abstractThis paper motivates the development of sophisticated data-driven models for power magnetic material characteristics. Core losses and hysteresis loops are critical information in the design process of power magnetics, yet the physics behind them is not fully understood. Both losses and hysteresis loops change for each magnetic material, are highly nonlinear, and depend heavily on the electrical operating conditions (e.g., waveform, frequency, amplitude, dc bias), the mechanical properties (e.g., pressure, vibration), as well as temperature and geometry of the magnetic components. Understanding the complexity of these factors is important for the development of accurate models and their applicability and limitations. Existing studies on power magnetics are usually developed based on a small amount of data and do not reveal the full magnetic behavior across a wide range of operating conditions. In this paper, based on a recently developed large-scale open-source database – MagNet – the core losses and hysteresis loops of Mn-Zn ferrites are analyzed over a wide range of amplitudes, frequencies, waveform shapes, dc bias levels, and temperatures, to quantify the complexity of modeling magnetic core losses, amplitude permeability, and hysteresis loops and provide guidelines for modeling power magnetics with data-driven methods.en_US
dc.relation.ispartofIEEE Transactions on Power Electronicsen_US
dc.rightsAuthor's manuscripten_US
dc.titleWhy MagNet: Quantifying the Complexity of Modeling Power Magnetic Material Characteristicsen_US
dc.typeJournal Articleen_US

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