Artificial Intelligence Applications in High-Frequency Magnetic Components Design for Power Electronics Systems: An Overview
Xiaobing Shen, Yu Zuo, J. A. Kong, Wilmar Martínez
Abstract
The paper provides an overview of how Artificial Intelligence (AI) is applied in designing highfrequency 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. Firstly, 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, the paper highlights significant advancements: the development of AI-driven models for precise loss estimation in highfrequency 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.