Electrification and Autonomy: Enablers for Sustainable Transportation Systems

Transportation electrification and autonomy are pivotal for mitigating climate change by reducing greenhouse gas emissions from transportation and decreasing dependency on fossil fuels. Electrification enables the adoption of renewable energy sources, and autonomy promises safer roads, increased efficiency, and enhanced accessibility for individuals unable to drive. Together, these advancements represent a transformative shift towards sustainable, efficient, and equitable transportation systems crucial for the future well-being of our planet.

This talk will focus on how to strategically utilize energy storage and leverage autonomy to improve performance and reduce emissions of the electrified transportation system. Specifically, several key topics will be discussed. Firstly, hybrid energy storage systems (HESS) emerge as promising solutions for electrified vehicles, ships, and smart grids by combining the advantages of various storage systems. An integrated design framework for HESS will be introduced, highlighting the necessity of a multi-dimensional co-design process. Secondly, eco-driving techniques, which can smoothen acceleration, anticipate traffic flow, and minimize energy consumption, can increase the driving range and reduce the environmental impact of electric vehicles (EVs). In this talk, some cutting-edge methodologies that can enable the eco-driving of individual EVs and mixed traffic flows (including both autonomous and human-driven vehicles) will be discussed. Lastly, the vision and future research plans, including the development of the next-generation battery management system and initiatives of using physics-informed data-enabled predictive control to advance transportation autonomy, will be presented.

Dr. Ziyou Song is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. He earned his bachelor’s degree with honors and Ph.D. degree with the highest honors in Automotive Engineering from Tsinghua University, China, in 2011 and 2016, respectively. Prior to joining the University of Michigan, Dr. Song served as an Assistant Professor at the National University of Singapore and worked as a battery algorithm engineer at Apple.
Dr. Song's research focuses on modeling, estimation, optimization, and control of energy storage systems, especially for the electrified transportation sector. Dr. Song has received several paper awards, including Automotive Innovation Best Paper Award, Applied Energy Highly Cited Paper Award, NSK Outstanding Paper Award of Mechanical Engineering, and IEEE VPPC Best Student Paper Award. Dr. Song serves as an Associate Editor and Editorial Member for IEEE Transactions on Transportation Electrification, IEEE Transactions on Intelligent Vehicles, Applied Energy, and eTransportation, among others.