What is it about?
This paper provides a comprehensive, systematic review of computational tools and methodologies used for the Life Cycle Assessment (LCA) of electric vehicle (EV) traction battery systems. By analyzing 79 battery-focused studies and 23 computational tool-focused publications, the review examines how current software architectures, database integrations, and uncertainty analyses handle the high variability of battery technologies. It categorizes the state of the art into key areas (reviews, cradle-to-grave LCA, manufacturing/use phase, and recycling) and details how computational frameworks can bridge the gap between complex engineering data and early-stage sustainable product design.
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Why is it important?
The rapid expansion of electric vehicles highlights the need to understand and mitigate the environmental footprint of traction batteries, from energy-intensive raw material extraction to end-of-life recycling. Traditional Life Cycle Assessments often yield highly inconsistent results due to varying parameters like cell chemistries, pack design, regional electricity mixes, and methodological choices. Integrating environmental evaluations into the engineering process is challenging due to data gaps and complexity. This review is critical because it identifies the requirements for computational LCA tools to overcome these barriers. It shows how software can integrate multidisciplinary data, manage spatial and temporal uncertainties, and empower designers to make eco-friendly decisions early in the development cycle.
Perspectives
Electric vehicles are a key part of our green future, but their heavy battery packs come with their own environmental footprints, from mining rare metals to disposal. Scientists use a method called "Life Cycle Assessment" (LCA) to calculate these impacts, but different studies often give completely different answers, making it hard for engineers to design cleaner batteries. This paper reviews the computer software and tools used to calculate these environmental impacts. It looks at how these tools can be made more user-friendly, helping designers easily test how changing a battery's materials, weight, or recycling method affects its overall footprint. Ultimately, the paper acts as a guide to building better software so that engineers can easily design the most sustainable batteries possible.
Maurizio Guadagno
Universita degli Studi di Firenze
Read the Original
This page is a summary of: A Review of Computational Methods and Tools for Life Cycle Assessment of Traction Battery Systems, February 2025, MDPI AG,
DOI: 10.3390/engproc2025085010.
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