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Mathematical Models for Battery Efficiency

SUMMARY:  Among all commercially available battery chemistries, Lithium-ion batteries are the best power source for mobile devices, electric vehicles, emergency power backup, and solar power storage, etc.  Lithium-ion batteries offer high power and energy density allowing them to satisfy the power demands while occupying less weight and volume than a nickel cadmium or lead acid cells. However, safety and long-term reliability of Lithium-ion batteries are the critical concerns. The discharge rate (i.e. acceleration of EV), operating temperature and amount of usage could result in battery degradation over time or even thermal runaway. Through mathematical modeling and battery simulation, we can understand the battery behavior and further track and control these factors to ensure the better utilization of the batteries.


BIO:  Jerry Chen | Jerry is a Ph.D. in Chemical Engineering at the University of Washington. He has been studying different numerical methods and efficient algorithms in order to solve stiff nonlinear partial differential algebraic equations (DAEs) which describe physics-based battery models, for example, the Pseudo 2-Dimensional (P2D) model. He received the Jagjeet and Janice Bindra Endowed Fellowship in 2015, the Clean Energy Institute Fellowship in 2016 and joined Data Intensive Research Enabling Clean Technologies (DIRECT) program funded by the National Science Foundation in 2017. Now, he is also the Educational Chair of the Electrochemical Society Chapter at UW. Jerry received his MBA, Master of Science and Bachelor in Chemical Engineering from National Taiwan University. He is going to present “Time Stepping Methods and Solvers for Battery Models” at the 231st ECS Meeting in New Orleans on 5/29.


Links for Learning More: 


Subramanians’ research group, UW

Clean Energy Institute, UW

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