학술논문
Artificial Intelligence Applications in High-Frequency Magnetic Components Design for Power Electronics Systems: An Overview
Document Type
Periodical
Author
Source
IEEE Transactions on Power Electronics IEEE Trans. Power Electron. Power Electronics, IEEE Transactions on. 39(7):8478-8496 Jul, 2024
Subject
Language
ISSN
0885-8993
1941-0107
1941-0107
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.