Zhenchao Li

Zhenchao Li is a Doctoral Assistant at the Power Electronics Laboratory (PEL) at École polytechnique fédérale de Lausanne (EPFL), working within the School of Engineering, Institute of Electrical Engineering. He is currently pursuing his PhD in Power Electronics at EPFL since April 2024.

His educational background includes:

• PhD in Power Electronics at EPFL (2024-present)
• Master's degree in Power Electronics & Renewable Energy from Xi'an Jiaotong University (2021-2024)
• Bachelor's degree in Electrical Engineering from Xi'an Jiaotong University (2017-2021)

Zhenchao Li's research focuses on power electronics, specifically in the areas of solid-state transformers, DC/DC converters, and magnetic integration. His work addresses challenges in power distribution networks and energy conversion systems, with a particular emphasis on improving efficiency and reducing component count in power electronic systems. He has made significant contributions to the development of Modularized Bridge Rectifier (mBR) solid-state transformer architectures, which replace active front-end stages with diodes and utilize multiple isolated DC/DC converters.

His recent publications demonstrate expertise in evaluating magnetic integration schemes that can reduce power capacity requirements by 50%, analyzing DC/DC converter performance in solid-state transformers, and developing advanced conversion solutions for DC power distribution networks. His research shows a strong focus on practical implementations with potential applications in renewable energy systems and modern power grids.

Among his achievements:

• Best Presentation Award at PCIM 2025

Zhenchao Li is actively contributing to the field of power electronics through his research at EPFL's Power Electronics Laboratory. His work on modularized diode rectifiers represents a novel approach to solid-state transformer design that could significantly impact future power distribution systems, offering solutions for higher voltage and current ratings while maintaining power factor correction features.