A modeling framework and benchmark for end-of-life automotive traction battery pack forecasting

Abstract

To meet climate targets, it is essential to establish a closed-loop system for the critical raw materials used in lithium-ion batteries, necessitating robust planning and forecasting methods for end-of-life battery volumes. Recycling end-of-life automotive batteries is crucial for establishing sustainable circulating flows of raw materials to reduce the use of virgin resources, particularly in the context of electromobility and energy storage. An accurate forecast of the availability of end-of-life automotive batteries for recycling is essential to determine the timing and the business potential of end-of-life battery treatment, driving the appropriate investments by policy makers and industry in battery recycling technologies and facilities. This paper presents a novel methodological framework incorporating multi-metric modeling with a distinct geographical focus and selected statistical approaches, collectively directed towards stakeholder-oriented end-of-life traction battery forecasts. We further benchmark the existing models based on the period under consideration, the geographical scope, the metrics employed, and the statistical techniques applied. This yields a novel recommendation framework for policy makers and industry to provide guidance on how to model end-of-life battery volumes. The recommendation framework links the required modeling approaches with relevant stakeholders, such as car repair shops, disassemblers, recyclers, logistics companies, and policy makers. The framework is validated through a case study for end-of-life automotive battery forecasting. The objective of this study is therefore not only to support the ramp-up of the battery recycling industry with a synthesized forecasting framework, but also to provide precise recommendations to the different industries. The findings of our study yield the core conclusion that global modelings with sophisticated statistical approaches, such as the Weibull approach, should be employed across a range of stakeholder-oriented metrics, including weight, capacity, and the number of end-of-life electric vehicle batteries.