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Artificial Intelligence Applications in Power Electronics

Year: 2025

Type: conference-paper

Abstract: Power electronics is at the core of modern energy systems, including renewable integration, electric vehicles, and smart grids. With increasing system complexity and performance demands, Artificial Intelligence (AI) has emerged as a transformative tool in optimizing design, enhancing control strategies, diagnosing faults, and improving power quality. This paper presents a comprehensive review of AI applications in power electronics, focusing on four critical domains: converter design, control strategies, fault diagnosis, power quality. Key AI techniques, including neural networks, fuzzy logic, support vector machines, and reinforcement learning, are discussed in the context of their practical deployment. The paper also highlights future directions, challenges, and opportunities for integrating AI in next-generation power electronic systems.

Source: International Conference on Energy Systems and Electrical Power (ICESEP)

DOI: 10.1109/icesep66633.2025.11155618

Authors: Tianqi(Kirk) Ding, Dawei Xiang, Tianyao Sun, YIJIASHUN QI, YIJIASHUN QI, Zunduo Zhao, Yijiazhen QI, Yijiazhen QI

Institutions: Baylor University, University of Connecticut, University of Michigan, New York University, University of Hong Kong

Language: English

Topic: Advanced DC-DC Converters

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W4414199013

FWCI: 18.56

Cites: 25

Cited by: 9

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