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Scenarios and modeling

BAMASI

BAttery MAterials SImulation



The BAMASI (BAttery MAterials SImulation) tool is designed to analyse the consumption of (critical) raw materials used in batteries and vehicles 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 ►.

The input and output datase are available in the Zenodo repository ► named BAMASI tool, applied to the CLEVER energy transition scenario and a reference scenario.

Key features and methodology

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.

 

Applications and benefits

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.