An empirical generic Li-ion aging model, compatible with a large number of aging mechanisms without their a priori knowledge has been developed as well as a calibration methodology allowing its fast and automated parameter setting. This model has been applied to simulate the aging behavior of a 26 Ah cell. To train this model, a large aging test campaign has been conducted dedicated to both calibration and validation purposes. This one takes into account calendar, cycling, and their combinations. Based on the design of the aging campaign it is able to account for the effect of State Of Charge, temperature and current on aging. As its calibration is based on an automated process, it can be trained automatically and does not need expert knowledge for operation. Simulation data are validated to a 2% error in comparison to experimental data and is then validated for automotive applications.

This paper deals with the Mobicus project which aims at developing empirical Li-ion battery aging models and using them to define the best management strategies in order to extend the battery lifetime for a given application in a usage scenario. A complete case study based on a PHEV vehicle is presented. This study implements various simulators using a calibrated empirical aging model, a battery module prototype and a complex test environment able to reproduce the thermal and electrical scenario associated with the different management strategies of the battery.