MagNet: A Machine Learning Framework for Magnetic Core Loss Modeling-Reference-Cited by-同舟云学术

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MagNet: A Machine Learning Framework for Magnetic Core Loss Modeling

Published:2020-11-09 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE 21st Workshop on Control and Modeling for Power Electronics (COMPEL)
language:
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Author:

Li Haoran,Lee Seungjae Ryan,Luo Min,Sullivan Charles R.,Chen Yuxin,Chen Minjie

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9265539/9265640/09265869.pdf?arnumber=9265869

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Circuits and magnetics co-design for ultra-thin vertical power delivery: A snapshot review;MRS Advances;2023-12-18

2. Small power litz wire ferrite inductor loss model based on neural network;2023 IEEE 4th China International Youth Conference On Electrical Engineering (CIYCEE);2023-12-08

3. MagNet-AI: Neural Network as Datasheet for Magnetics Modeling and Material Recommendation;IEEE Transactions on Power Electronics;2023-12

4. A Series Resonant Converter based Experimental Measurement of B-H Curve for Core Loss Estimation of a High Frequency Inductor;2023 IEEE Energy Conversion Congress and Exposition (ECCE);2023-10-29

5. On the Impact of DC Magnetization on Core Losses: A Model Based on Extensive Experimental Results from the MagNet Database;2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe);2023-09-04

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