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Artificial Intelligence Applications in High-Frequency Magnetic Components Design for Power Electronics Systems: An Overview

Authors :
Shen, Xiaobing
Zuo, Yu
Kong, Jiaze
Martinez, Wilmar
Source :
IEEE Transactions on Power Electronics; 2024, Vol. 39 Issue: 7 p8478-8496, 19p
Publication Year :
2024

Abstract

This article provides an overview of how artificial intelligence (AI) is applied in designing high-frequency magnetic components, primarily high-frequency inductors and transformers, for power electronics systems. Four categories of AI, including expert systems, fuzzy logic, metaheuristic methods, and machine learning techniques, are addressed. First, AI models for estimating losses in high-frequency magnetic components are discussed. Subsequently, AI-based design methods in high-frequency inductors and transformers are observed. Then, AI tools applied to the automatic design of high-frequency magnetic components are introduced and compared. Drawing insights from an analysis of over 200 publications, this article highlights significant advancements: the development of AI-driven models for precise loss estimation in high-frequency magnetic components, the application of AI in optimizing design configurations for the components, and the automation of design processes. These achievements demonstrate AI's capability to enhance the efficiency, performance, and innovation in high-frequency magnetic component design, offering a roadmap for future research in power electronics systems.

Details

Language :
English
ISSN :
08858993
Volume :
39
Issue :
7
Database :
Supplemental Index
Journal :
IEEE Transactions on Power Electronics
Publication Type :
Periodical
Accession number :
ejs66449734
Full Text :
https://doi.org/10.1109/TPEL.2024.3381431