Disaggregating prospective macroeconomic scenarios to quantify xEV battery raw materials needs

Although many energy transition scenarios(Bourgeois et al. 2023; EC. 2021) are proposed for the European Union (EU-27) region a robust approach to quantify the raw materials (RM) needs for such transitions to happen is still lacking, despite their critical role. Whereas mainly grey literature or institutional reports propose quantification (Gregoir and van Acker 2022; IEA 2021; Carrara et al. 2023) the broad scope or underlying hypothesis rarely allows for grasping details for the EU-27 mobility sector. We will propose a FAIR(Findable, accessible, interoperable, reusable) framework to quantify the RM (i.e. at least Li, Co, Ni, Mn, Graphite) needed for xEV, for energy storage technologies (ESS), of mobility and freight from existing macroeconomic scenarios.
When investigating demand for ESS, xEV could represent up to 80% (IEA 2021) of the storage demand but as electrochemical storage is composed of a disparate set of chemistries or technologies(MIT 2022), what are the possible RM demands? Reckoning the need to secure our critical RM supply, the EU has initiated several policies, including the Battery Regulation Act and the Critical Raw Material Act(EC 2023a; 2023b), all of them targeting specific materials. As relative goals (e.g., collection or recycling rate, in %; % of EU processing capacity per raw materials) have been set, there is also a need for a methodology to infer absolute values for RM needs for xEV.
This research plans to gather historical data and prospective hypotheses to draw RM demand pathways for passenger mobility and freight. Using the current EU mobility pattern and prospective scenario, we plan to produce a dataset, a disaggregation methodology (i.e., along with hypothesis) and software to quantify the RM necessary to achieve the transition proposed for the mobility and freight sector. From published scenarios giving values such as energy consumption or activity (i.e. in passenger kilometre or ton kilometre), the current state of the fleet and the targeted evolution is input, the model will compute the fleet which fits the best to the values given in the macro-economic scenario. Additionally, hypotheses on battery size and chemistry share of ESS will allow to quantify the raw material needed.
The result of this research should provide the material necessary to understand the industrial capacity needed to underpin the value chain of energy storage, from the manufacturer to the recycler. It will allow future assessment of the security of supply, the benefits of circular economy strategies and the impacts of key parameters on RM circularity and demands.