@inproceedings{d0ad524cbb844359baeba1abae25ed97,
title = "MagNetX: Extending the MagNet Database for Modeling Power Magnetics in Transient",
abstract = "This paper introduces the MagNetX1 - an extension of the MagNet database to investigate transient hysteresis of magnetic materials. By employing automated data acquisition and measurement systems, detailed transient phenomena are observed and evaluated across a wide range of waveforms and operational conditions. Results reveal significant core loss variations during frequency transitions, and the B-H loop analysis further demonstrates loop area changes during transient phases. The platform enables advanced data-driven modeling of core losses and hysteresis loops over a wide range of amplitudes, frequencies, temperatures, and duty cycles under transient conditions, which are critical for practical circuit design when steady-state models are inadequate, such as modeling the magnetic core behaviors in ac-dc converters, motor drives, or power amplifiers.",
keywords = "core loss, hysteresis loop, machine learning, neural networks, power magnetics, transient",
author = "Hyukjae Kwon and Shukai Wang and Haoran Li and Youssef Elasser and Kang, \{Gyeong Gu\} and Daniel Zhou and Davit Grigoryan and Minjie Chen",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025 ; Conference date: 16-03-2025 Through 20-03-2025",
year = "2025",
doi = "10.1109/APEC48143.2025.10977252",
language = "English (US)",
series = "Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "566--572",
booktitle = "APEC 2025 - 14th Annual IEEE Applied Power Electronics Conference and Exposition",
address = "United States",
}