Published November 6, 2025 | Version 2023
Software Open

BAMASI (BAttery MAterials SImulation) tool for road transport critical raw materials modelling, applied to the EU CLEVER energy transition scenario and the French négaWatt scenario

  • 1. négaWatt Association
  • 2. Association négaWatt

Contributors

  • 1. négaWatt Association
  • 2. Association négaWatt

Description

The BAMASI (Battery MAterials SImulation) tool is designed to analyse the consumption of (critical) raw materials used in batteries and vehi- cles in the road transport sector, such as lithium, cobalt, nickel and copper, in various energy transition scenarios, particularly low energy demand scenarios integrating sufficiency asumptions by 2050. Financed and co-developed with ADEME (the French public environmental agency), it has been used in modelling the European CLEVER scenario, the French négaWatt scenario and various studies on raw materials for ADEME but also for NGOs Fern and Rain Forest Norway.

BAMASI provides information on how different energy transition and mobility pathways influence material requirements by combining:

  1. A transparent, open-source calculation methodology
  2. Ease of use via an Excel interface and the computing power and modularity of Python 
  3. Multiple data output options

Unlike traditional stock models (e.g. those used by the IEA or previously by ADEME), BAMASI defines the lifetime of vehicles in kilometres rather than years. This approach better reflects mobility sufficiency assumptions, according to which the distances travelled annually will decrease by 2050.

To ensure realism, a post-model check ensures that the age of vehicles does not exceed a certain limit in years. In prospective scenarios such as CLEVER, BAMASI tool also takes into account the premature end of life of fossil fuel vehicles necessary to meet climate goals on carbon neutrality by converting the full vehicle fleet to electric or biogas by 2050.

Thanks to these innovations, BAMASI provides a robust tool for comparing low energy demand scenarios and reference scenarios, thereby supporting research and decision-making in the areas of sustainable mobility and material resource supply risks.

Files

BAMASI v2023 - CLEVER scenario.zip

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Additional details

Software

Programming language
Python
Development Status
Active