A Q&A with new faculty member Ziyou Song

We are delighted to welcome Ziyou Song to the ECE community. Song joined the faculty January 2025 as an assistant professor in the area of power and energy. His group focuses on modeling, estimation, optimization, and control of energy storage systems, including batteries, supercapacitors, and flywheels, for electrified vehicles and renewable energy systems.

Before joining Michigan, Song was an Assistant Professor of Mechanical Engineering at the National University of Singapore. He received his PhD from Tsinghua University with highest honors, and remained at the University as a Research Scientist. He then spent three years at Michigan ECE as a Postdoctoral Research Fellow and Assistant Research Scientist. He also spent a year at Apple as a battery algorithm engineer.

Song has received several paper awards, including Applied Energy 2015-2016 Highly Cited Paper Award, Applied Energy Award for Most Cited Energy Article from China, NSK Outstanding Paper Award of Mechanical Engineering, and 2013 IEEE VPPC Best Student Paper Award. He serves as Associate Editor for four different journals, including IEEE Transactions on Transportation Electrification and SAE International Journal of Electrified Vehicles, and is a Young Editorial Board Member of Applied Energy and eTransportation.

He is currently teaching EECS 418: Power Electronics, and will teach a graduate course in Advanced Energy Storage during the Winter term.

Song is actively seeking new graduate students and Postdoctoral Researchers to join his group; more information can be found on his website.

Here is more information about Ziyou Song, in his own words.

Tell us about your research.

My research focuses on the modeling, estimation, and control of energy storage systems, such as batteries and supercapacitors, for electrified vehicles and renewable energy applications. Recently, my group has been particularly interested in leveraging physics-informed machine learning to characterize fresh and second-life batteries, investigate coupled degradation mechanisms, and predict performance at the cell, module, and pack levels, paving the way for next-generation battery management systems. Using energy storage as a bridge, we are thrilled to connect automotive, transportation, and power system communities through interdisciplinary projects and fill the gap between different sectors.

How does your work impact the world around us?

Energy storage plays a critical role in integrating renewable energy, reducing carbon emissions, and stabilizing electricity grids. It is also essential for advancing electric vehicles and ensuring uninterrupted power for various industries. Despite its importance, our understanding of certain energy storage solutions, such as batteries, remains quite limited. Predicting their performance and degradation/failure behavior under diverse operating conditions remains a big challenge, raising concerns about real-world implementation, particularly regarding safety. To address these challenges, it is important to leverage advanced algorithms, including physical modeling and machine learning, to deepen our understanding and tackle pressing issues in this area, thereby facilitating a sustainable future.

What do you enjoy most about your field?

I enjoy the opportunity to solve interdisciplinary, real-world problems. Working on advanced algorithms for energy storage, electrified vehicles, and renewable energy systems allows me to combine cutting-edge technology and innovative thinking to improve energy efficiency and contribute to a more sustainable future. The dynamic nature of this field enables me to constantly learn and adapt, which I find challenging, satisfying, and rewarding.

What’s your favorite thing about teaching?

I truly enjoy engaging with bright minds and feel fortunate to learn from my students, whose fascinating ideas often inspire me to view things from new perspectives. Teaching also allows me to share my passion for energy storage and sustainable energy while mentoring the next generation of engineers and researchers.

At Michigan, I will be teaching EECS 598: Advanced Energy Storage and EECS 418: Power Electronics.

What qualities do you look for when selecting PhD students to join your team?

I hope my students cultivate an independent spirit and critical thinking skills, possess a sense of exploration, and demonstrate openness. They should treat others with respect and politeness, excel in collaboration, and enjoy working with others.

What is your approach to mentoring graduate students?

My approach to mentoring graduate students is rooted in fostering growth, independence, and collaboration. I strive to help each student shine in their unique way, valuing their strengths and perspectives. My top priority is to create a safe and supportive environment, ensuring students feel comfortable sharing ideas and seeking constructive feedback. Above all, my goal is to empower students to become confident researchers and professionals who can excel in their chosen areas.

Do you have any hobbies or anything else you’d like to share?

I enjoy playing basketball and table tennis to stay active, and IMSB is my favorite place for sports. I also love fishing to relax and challenge my mind. Michigan is a fantastic place for this, and I will be happy to share great spots with mystery big fish.