Latest revision as of 12:36, 12 February 2021

Abstract

The number of battery electric vehicle models available in the market has been increasing, as well as their battery capacity, and these trends are likely to continue in the future as sustainable transportation goals rise in importance, supported by advances in battery chemistry and technology. Given the rapid pace of these advances, the impact of new chemistries, e.g., lithium-manganese rich cathode materials and silicon/graphite anodes, has not yet been thoroughly considered in the literature. This research estimates life cycle greenhouse gas and other air pollutants emissions of battery electric vehicles with different battery chemistries, including the above advances. The analysis methodology, which uses the greenhouse gases, regulated emissions, and energy use in transportation (GREET) life-cycle assessment model, considers 8 battery types, 13 electricity generation mixes with different predominant primary energy sources, and 4 vehicle segments (small, medium, large, and sport utility vehicles), represented by prototype vehicles, with both battery replacement and non-replacement during the life cycle. Outputs are expressed as emissions ratios to the equivalent petrol internal combustion engine vehicle and two-way analysis of variance is used to test results for statistical significance. Results show that newer Li-ion battery technology can yield significant improvements over older battery chemistries, which can be as high as 60% emissions reduction, depending on pollutant type and electricity generation mix. This research was funded by Fundação para a Ciência e a Tecnologia, grant number UID/Multi/00308/2019, INESC-Coimbra R&D project “Alternative Fuel Vehicles”. info:eu-repo/semantics/publishedVersion

Document type: Article

Full document

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.3390/su11082366 under the license https://creativecommons.org/licenses/by

• http://dx.doi.org/10.3390/su11082366 under the license http://creativecommons.org/licenses/by/3.0/

• https://www.mdpi.com/2071-1050/11/8/2366/pdf under the license https://creativecommons.org/licenses/by/4.0

• http://hdl.handle.net/10400.2/8121,

https://doi.org/10.3390/su11082366 under the license cc-by

• https://www.mdpi.com/2071-1050/11/8/2366,

https://doaj.org/toc/2071-1050 under the license http://creativecommons.org/licenses/by/4.0/

• https://www.mdpi.com/2071-1050/11/8/2366,

https://www.mdpi.com/2071-1050/11/8/2366/pdf,

https://repositorioaberto.uab.pt/handle/10400.2/8121,

https://ideas.repec.org/a/gam/jsusta/v11y2019i8p2366-d224585.html,

https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:8:p:2366-:d:224585,

https://academic.microsoft.com/#/detail/2939825882

• https://www.mdpi.com/2071-1050/11/8/2366/pdf,

http://dx.doi.org/10.3390/su11082366

under the license https://creativecommons.org/licenses/by/4.0/