Aging and life prediction of Li-ion batteries

In this project, the effective life of advanced Li-ion batteries will be assessed using experimental tools and predictive modeling. Li-ion batteries have emerged as an alternative source of energy on-board cars, i.e., electric vehicles (EVs). Unlike internal combustion engine (ICE) vehicles, EVs suffer from performance degradation over driving and idle time posing limitations on their widespread deployment in the market. The life target for Li-ion batteries determined by the Department of Energy is in the range of 8 to 10 years of service with 80% of cell capacity being considered as the end of life. Examining battery performance degradation experimentally over such a long period of time is extremely costly and, even if doable, would fall behind in the examination of new technologies. As such, predictive modeling comes in use as a powerful approach to reduce cost and shorten the investigation time for a particular battery technology. TO BE CONT'D

Intern: 
Mohammad Farkhondeh Borazjani
Faculty Supervisor: 
Michael Fowler
Province: 
Ontario
Partner: 
Partner University: 
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