A Multidimensional Classification Framework for Second-Life Lithium-Ion Batteries

The rapid growth of electric vehicles will generate a substantial volume of retired lithium-ion batteries over the coming years. Although many of these batteries no longer satisfy the performance requirements of mobile applications, they often retain sufficient capacity for second-life energy storage systems. However, the lack of transparent and standardized classification methods remains a major barrier to the safe, reliable, and efficient deployment of second-life batteries. This paper proposes a multidimensional classification framework for retired lithium-ion batteries based on battery shape, chemistry, state of health, and safety condition. The main novelty of this work is the development of an integrated decision matrix that combines battery chemistry, health class, thermal behavior, power capability, and safety-screening outcomes within a single application-routing framework. Compared with conventional approaches that mainly rely on SoH, the proposed framework provides a more complete basis for distinguishing batteries suitable for high-demand, medium-demand, low-demand, or recycling pathways. The proposed matrix promotes more transparent and consistent decision-making for battery reuse, repurposing, and recycling while supporting sustainability and circular economy principles. The integrated decision matrix provides a structured basis for matching retired batteries to appropriate stationary applications, improving deployment consistency, reducing premature recycling, and maximizing the environmental and economic value of second-life lithium-ion batteries. The proposed framework is presented as a qualitative decision-support approach, providing a structured basis for more consistent second-life battery classification and application routing.