Future Energy Demand for Automotive and Stationary Lithium- and Sodium-Ion Battery Production towards a European Circular Economy

Abstract

Europe is currently heavily dependent on imports for the critical raw materials needed for lithium-ion battery (LIB) production, as most of these resources are distributed outside the region. Despite this dependency, Europe accounts for around 25% of global electric vehicle (EV) sales. This creates an indirect form of energy dependency, as much of the energy used in battery cell production is embedded in imported materials and cells. Persistent supply chain bottlenecks have made battery access a strategic priority for automakers, prompting efforts to build more resilient domestic supply chains. However, this shift also means that a significant amount of energy will need to be sourced within Europe itself, raising concerns about energy consumption amid surging European battery capacity demand - an important factor that will shape strategic decisions in both industry and policy. This work addresses the future energy demand of LIBs and their potential near-term competitiors, sodium-ion batteries, by quantifiying the cradle-to-gate and cradle-to-cradle Cumulative Energy Demand for large-format prismatic cells, using primary machinery data on gigafactory scale. The European energy demand forecast until 2070 is conducted using a novel circular economy simulation model, considering recycling, second use and the use phase of EVs and stationary energy storage (SES) applications. We show that the local European energy demand to establish a domestic battery cell production and to be self-sufficient by 2050 will rise to 250 TWh annually. Including the use phase of EVs and SES, a total of 450-500 TWh will be needed within Europe starting in 2040, offset by savings of approx. 90 TWh from reduced fossil fuel upstream energy. The comprehensive analysis provides a quantitative framework for understanding the energy flows associated with large-scale battery cell production in Europe. We highlight processes with significant reduction potential, while also identifying factors that could increase energy demand in the future.