A product–component framework for modeling stock dynamics and its application for electric vehicles and lithium‐ion batteries

Abstract

Models that study the socio-economic metabolism often apply a lifetime approach to capture the stock dynamics of products. The lifetime is usually obtained empirically from statistical information and is assumed to describe the dynamics of the product and its components. However, for new types of products for which historic outflow data is limited, or in cases where a critical component plays a significant role in determining product end-of-life, a more refined understanding of the dynamics of product–component systems is needed. Here, we provide a new framework for product–component systems and 12 different approaches to model their stock dynamics. Then, we discuss which approaches are best suited in different contexts. We illustrate the use of the framework with a case study on electric vehicles and their batteries, highlighting the potential of battery replacement and reuse for reducing material demand. Improving the understanding of these complex systems is relevant for the study of the socio-economic metabolism because (i) accounting for component dynamics can support identifying unintended consequences of product-specific policies; (ii) component replacement and reuse can be a key circular economy strategy to foster efficient resource use; and (iii) accounting for these complex dynamics can lead to more accurate estimates for resource demand and waste-generation expectations, creating more resilient information streams. This article met the requirements for a Gold-Gold JIE data openness badge described at https://jie.click/badges.