“Increasing Battery Potential: Estimation & Control of Electrochemical Models”
Prof. Scott Moura, UC Berkeley
Wednesday, March 29, 2017 2:00 – 3:00PM EEB 248
Abstract: Batteries are ubiquitous. However, today’s batteries are expensive, range-limited, power-restricted, die too quickly, and charge too slowly. Batteries are conservatively operated because their control systems treat the internal electrochemical dynamics as a black-box. Given real-time estimates of the electrochemical states, however, one can safely operate batteries near their physical limits, thus significantly enhancing performance beyond current state-of-art battery management systems. This talk reviews recent advancements in enhanced battery performance via estimation and control of PDE electrochemical models. First, we review battery electrochemistry. Second, we discuss canonical state-of-charge (SOC), state-of-health (SOH), and other so-called SOx estimation algorithms. Third, we present recent theoretical results in state estimation and optimal control with PDE models. Finally, we close with exciting new opportunities for next-generation battery management systems.
Bio: Scott Moura is an Assistant Professor at the University of California, Berkeley in Civil & Environmental Engineering and Director of eCAL. 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. He was a postdoctoral scholar at UC San Diego in the Cymer Center for Control Systems and Dynamics, and a visiting researcher in the Centre Automatique et Systèmes at MINES ParisTech in Paris, France. He is a recipient of the O. Hugo Shuck Best Paper Award, Carol D. Soc Distinguished Graduate Student Mentoring Award, Hellman Faculty Fellows Award, UC Presidential Postdoctoral Fellowship, National Science Foundation Graduate Research Fellowship, University of Michigan Distinguished ProQuest Dissertation Honorable Mention, University of Michigan Rackham Merit Fellowship, and Distinguished Leadership Award. He has received multiple conference best paper awards, as an advisor & student. His research interests include control & estimation theory for PDEs, optimization, machine learning, batteries, electric vehicles, and the smart grid.