Semi-empirical calendar capacity degradation modeling of graphite/lithium iron phosphate (LFP) pouch cells: Non-constant fitting coefficient functions

To accurately and efficiently predict the lifetime of Li-ion batteries for their practical applications in battery electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, energy storage systems, etc., accurate semiempirical life models are desired for battery lifetime simulation. In this work, semiempirical calendar aging models considering nonconstant fitting coefficient functions based on storage aging tests for 20 Ah graphite/lithium iron phosphate pouch cells under various temperatures ranging from 0℃ to 60℃ and state-of-charges ranging from 20% to 100% were developed. It was found that the “best” calendar capacity life model with non-constant fitting coefficient functions compared with the common calendar capacity life model with constant fitting coefficients reduces the mean absolute error and root mean square error of the calendar capacity fitting by 7.4% and 6.6%, respectively. Moreover, the “best” calendar capacity life model proposed in this work outperforms 2 existing reference models reported in the literature, especially at high temperatures, that is, 40℃ and 60℃. It is expected that this work would benefit accurate and efficient calendar capacity prediction of Li-ion batteries. • Calendar aging tests under a wide window of storage temperatures were conducted. • Semi-empirical calendar capacity degradation models of battery cells were developed. • Non-constant fitting coefficients were incorporated in the calendar aging models. • Calendar aging models with non-constant fitting factors match better with data.