Cloud-connected battery management for decision making on second-life of electric vehicle batteries

Abstract

The Second-Life use of retired electric vehicles' (EV) batteries in stationary storage systems can not only help to reduce the CO2 footprint of EVs but also generate a significant residual value before recycling. However, the nowadays repurposing process from vehicle batteries to Second-Life storage systems is characterized by time and cost intensive process steps like disassembly to module level and manual state of health (SOH) measurements with costly test equipment. Therefore, the aim of this paper is to introduce a novel cloud-connected battery management approach to estimate the residual value of vehicle batteries in respect to various potential Second-Life applications. Based on measurement data acquired by the battery management system (BMS) during regular vehicle operation, the state of the vehicle battery is continuously updated in the form of an electric-thermal system model on a server backend. In combination with an empirical aging model, the degradation behaviour for different Second-Life scenarios' load cycles can be predicted and thus the residual value calculated. Besides the introduction of the overall concept, the focus of this paper lies on the electric-thermal modelling approach as well as the algorithms used for dynamic electric parameter estimation.