COinS
Adaptive DAE Observer for Joint State and Parameter Estimation in Parallel-Connected Li-ion Batteries with Experimental Validation
Adaptive DAE Observer for Joint State and Parameter Estimation in Parallel-Connected Li-ion Batteries with Experimental Validation
Biography of all authors
Jorge Espin received his B.S. degree in Electronics and Control Engineering from the National Polytechnic School of Ecuador in 2021, and his M.S. degree in Project Management from Nebrija University in 2022. He is currently pursuing a Ph.D. in the School of Aerospace and Mechanical Engineering at the University of Oklahoma, where he is a member of the Energy Systems and Controls Lab. His research interests include control theory, state estimation, machine learning, and optimal control, applied to battery management systems and energy storage solutions.
He was selected as a finalist for the Best Student Research Paper Award at the 2024 Modeling, Estimation, and Control Conference.
Dong Zhang received the B.S. degree in Civil and Environmental Engineering from the University of Michigan, Ann Arbor, MI, USA, in 2015, the B.S. degree in Electrical and Computer Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2015, and the M.S. and Ph.D. degrees in systems and control engineering from the University of California at Berkeley, Berkeley, CA, USA, in 2016 and 2020, respectively.
He was a postdoctoral fellow with the Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, from 2020 to 2021. He is currently an Assistant Professor in the School of Aerospace and Mechanical Engineering at the University of Oklahoma, Norman, OK, USA, while directing the Energy Systems and Controls Laboratory. He is also a faculty affiliate with the Institute for Resilient Environmental and Energy Systems (IREES) at the University of Oklahoma. His current research interests include dynamical system modeling and control, state estimation, optimization, and data-driven methods, with application to advanced battery management systems and electrified mobility systems.
Dr. Zhang is a recipient of the CAREER Award and the EPSCoR Research Fellow from the U.S. National Science Foundation (NSF), as well as the Best Paper Award from the ASME Energy System Technical Committee at the 2020 American Control Conference (ACC).