Synopsis
The repurposing of second-life lithium-ion batteries (LIBs) provides a sustainable solution for applications like light electric vehicles (LEVs) or stationary storage. However, limited knowledge of their usage history and internal condition complicates effective reuse. This study introduces a hybrid modelling (HM) approach, combining a data-driven model (DDM) and a physics-based model (PBM), to assess battery health and predict performance. The DDM estimates key parameters from a simple charge test, which initialize the PBM to simulate degradation and remaining useful life under LEV profiles.
