Real-World Mobility and Environmental Data for the Assessment of In-Vehicle Battery Capacity Fade

Abstract

This work develops scenario-based analyses for predicting in-vehicle performance degradation of automotive traction batteries. It combines recent capacity performance-based models of NCM-LMO Li-ion (Nickel Cobalt Manganese Oxide—Lithium Manganese Oxide) variant batteries with real-world vehicle driving data from different geographical areas of Europe. The analysis addresses different battery and vehicle architectures (PHEVs (Plug-in Hybrid Electric Vehicles) and BEVs (Battery Electric Vehicles)) combined with different recharging strategies and mobility patterns and environmental temperatures. The mobility pattern datasets used in this analysis refer to six European cities and include up to 508,609 private vehicles, corresponding to 1.78 billion GPS records, 9.1 million trips and parking events and a total driven distance of 106.1 million kilometers. The results show the effect that the environmental temperature, the recharging power, and the driven kilometers have on the calendar and cycling aging. The majority of the combinations of the considered vehicle architectures and recharge strategies do not lead to battery capacity drop below 80% of its nominal value in less than five calendar years for a usage profile of up to 1000 km/month.