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Predicting lithium-ion battery degradation for efficient design and management
World Electric Vehicle Journal
Being able to predict the Li-ion battery degradation is necessary for applications such as electric vehicles (EVs) and hybrid ones (HEVs). Most of the time, battery life prediction is based on accelerated cycling datasets obtained under different conditions. However, cell aging occurs not only during cycling but also at rest (calendar mode), the latter representing about 90 % of its lifetime. In this work, an empirical model of a 12 Ah commercial graphite/nickel-manganese-cobalt (C/NMC) celldoi:10.3390/wevj6030549 fatcat:lq7lbrk5vrbubaqmibplg7kedu