Empirical calendar ageing model for electric vehicles and energy storage systems batteries

Abstract

Transport electrification and energy storage are considered part of the solution to decrease CO2 emissions from the energy and transport sectors. In this context, batteries can be a promising technology, since advances in the last few years have ensured a larger lifetime and better performance. Depending on actual use of the batteries, calendar ageing can be considered as the main origin of degradation in both transport electrification and energy storage since electric vehicles are parked 96 % of the time and battery energy storage stations (BESSs) can remain at a high State of Charge (SoC) for a long time along their lifetime. Therefore, a lifetime model or a degradation model of batteries is necessary to optimally develop an application of these in every sector. In this sense, this paper presents a calendar ageing model of a nickel‑manganese‑cobalt (NMC) battery, which is used in commercialised electric vehicles. The degradation model presented here is based on the Hermite Cubic Interpolation Polynomial (PCHIP) over an experimental results data set in combination with a power law for modeling the influence of the storing time. In this context, four fitting equations have been compared in search of the most appropriate time depending rate, and the accuracy of the most commonly used model was improved. The storing temperature and SoC have been found to be the most harmful factors in the degradation of these batteries by calendar ageing. The degradation model developed yields of an average root-mean-square error (RMSE) of 0.8 % in capacity fade (CF), while in power fade (PF), the average RMSE has been 2.3 %.