AI-Driven Innovations in Power Electronics Research and Development

Dear Colleagues,

The integration of Artificial Intelligence (AI) in power electronics research and development has ushered in a new era of innovation, efficiency, and performance optimization. This issue aims to explore the cutting-edge applications of AI technologies in advancing power electronics systems and components.

By presenting a comprehensive overview of AI applications in power electronics, this Special Issue aims to provide researchers, engineers, and industry professionals with valuable insights into the latest advancements and prospects in this rapidly evolving field.

Key areas of focus will include the following:

1. AI-driven design and optimization of power electronic circuits and components, leading to improved efficiency and reduced development time.
2. Intelligent control systems for power converters, inverters, and other power electronic devices, enabling adaptive and robust performance under varying operating conditions.
3. AI-based fault detection, diagnosis, and prognosis in power electronic systems, enhancing reliability and reducing downtime.
4. The application of AI in smart grid management and integration of renewable energy sources, optimizing power flow and stability.
5. Machine learning techniques for predictive maintenance of power electronic equipment, minimizing unexpected failures and extending operational life.
6. AI-assisted modeling and simulation of power electronic systems, enabling more accurate predictions of system behavior and performance.
7. The role of AI in developing next-generation wide-bandgap semiconductor devices and their integration into power electronic systems.
8. Challenges and opportunities in implementing AI solutions in power electronics, including computational requirements, data management, and ethical considerations.

We invite submissions of new ideas, novel control algorithms, and electronic network structures and design, as well as new approaches and methods for research and development in the field of power electronics.

By advancing these areas, we aim to provide an in-depth examination of the latest algorithms, architectures, and applications in this domain, offering insights into both the theoretical foundations and real-world impact of AI-driven innovations in power electronics.

Possible topics include, but are not restricted to, those represented below:

• Novel Algorithms, Models, and Architectures for AI-driven Innovations in Power Electronics.
• AI-Driven Discovery of Novel Power Converter Topologies.
• Neural Network-Assisted Optimization of Magnetic Components.
• Emerging Trends and Future Directions in AI-Driven Image Generation.
• Multi-Objective Optimization of Si/SiC/GaN Devices Using Machine Learning.
• Generative AI for Automated Converter Design and Schematic Synthesis.
• Quality Prediction in Power Electronics Manufacturing Using AI.
• AI-Driven Automated Testing and Verification of Power Modules.
• Machine Learning Approaches for Predicting Semiconductor Device Lifetime.
• Deep Learning-Based Fault Diagnosis in Inverters and Motor Drives.
• Hybrid Physics–AI Models for Fast Simulation of Power Systems.
• AI-Based Model Predictive Control for Multilevel Inverters.
• Neural Network Estimators for Sensorless Control in Power Electronics.

We look forward to hearing from you.

Dr. Moshe Averbukh
Dr. Shailendra Rajput
Guest Editors

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