Abstract:  Energy storage represents one of society’s grand challenges for the 21^st century. As renewable energy generation becomes more prominent, new solutions for efficiently storing and routing energy must be found. Today’s batteries are expensive, oversized, and conservatively operated. Advanced estimation and control can unlock their full potential. That is, real-time state information and optimization enables operation near the physical limits without compromising longevity. This feature is a crucial step towards catalyzing the adoption of energy storage in electrified transportation and smart grids.

In this talk, we focus on the state-of-charge (SOC) and state-of-health (SOH) estimation problem. We cast this problem as a simultaneous state (SOC) and parameter (SOH) estimation design. Unlike most approaches, our design utilizes electrochemical models, thus enabling us to directly estimate the evolution of relevant electrochemical phenomena. This research integrates several recently developed concepts in PDE control theory, adaptive estimation, and battery model reduction. We will also explore how these estimates can be exploited to reduce charge time, enhance energy capacity, and protect against harmful degradation processes. I conclude with an overview of open questions and future research plans in energy systems and control.

Bio:  Scott Moura is a UC President’s Postdoctoral Fellow at UCSD. He received the Ph.D. degree from the University of Michigan in 2011, the M.S. degree from the University of Michigan in 2008, and the B.S. degree from the UC Berkeley, in 2006 – all in Mechanical Engineering. Dr. Moura is a recipient of the National Science Foundation Graduate Research Fellowship, UC Presidential Postdoctoral Fellowship, University of Michigan Distinguished ProQuest Dissertation Honorable Mention, University of Michigan Rackham Merit Fellowship, College of Engineering Distinguished Leadership Award. He has also been honored as a Semi-Plenary speaker at the ASME Dynamic Systems and Control Conference  (DSCC) and Best Student Paper Finalist at the American Control Conference and ASME DSCC. His research interests include optimal & adaptive control, PDE control, energy storage, smart grid systems, and batteries.