Semi-Empirical Cycle Life Model with Electrolyte Depletion Function for Long Cycle Prediction of Lithium-Ion Battery

Abstract

Lithium-ion batteries (LIBs) have already been adapted for the applications of electric vehicles (EVs) and energy storage systems (ESSs) thanks to their high power density (~1500 W/kg), high energy density (~250 Wh/kg), long cycle life, low self-discharge and among secondary batteries. However, in general, tens of years or thousands of cycles are too long to evaluate the electrochemical performance or reliability of large-format LIBs. moreover, since high-current cyclers are much more expensive in comparison with those for small LIB cells for small device, available channels for long-term tests must be limited. That is why high-level modeling and simulation technologies must be developed for the battery industry. In this study, we developed a new semi-empirical cycle life model for predicting long-term cycle life considering an electrolyte depletion function for the first time. Consequentially, we are able to predict capacity fade depending on operating conditions such as c-rate and depth-of-discharge (DOD), which should be pre-estimated before building up the battery management system for EVs and ESSs application.