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Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation

Electric vehicles (EVs) are widely promoted as clean alternatives to conventional vehicles for reducing greenhouse gas (GHG) emissions from ground transportation. However, the battery undergoes a sophisticated degradation process during EV operations and its effects on EV energy consumption and GHG...

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Detalles Bibliográficos
Autores principales: Yang, Fan, Xie, Yuanyuan, Deng, Yelin, Yuan, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013442/
https://www.ncbi.nlm.nih.gov/pubmed/29930259
http://dx.doi.org/10.1038/s41467-018-04826-0
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author Yang, Fan
Xie, Yuanyuan
Deng, Yelin
Yuan, Chris
author_facet Yang, Fan
Xie, Yuanyuan
Deng, Yelin
Yuan, Chris
author_sort Yang, Fan
collection PubMed
description Electric vehicles (EVs) are widely promoted as clean alternatives to conventional vehicles for reducing greenhouse gas (GHG) emissions from ground transportation. However, the battery undergoes a sophisticated degradation process during EV operations and its effects on EV energy consumption and GHG emissions are unknown. Here we show on a typical 24 kWh lithium-manganese-oxide–graphite battery pack that the degradation of EV battery can be mathematically modeled to predict battery life and to study its effects on energy consumption and GHG emissions from EV operations. We found that under US state-level average driving conditions, the battery life is ranging between 5.2 years in Florida and 13.3 years in Alaska under 30% battery degradation limit. The battery degradation will cause a 11.5–16.2% increase in energy consumption and GHG emissions per km driven at 30% capacity loss. This study provides a robust analytical approach and results for supporting policy making in prioritizing EV deployment in the U.S.
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spelling pubmed-60134422018-06-25 Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation Yang, Fan Xie, Yuanyuan Deng, Yelin Yuan, Chris Nat Commun Article Electric vehicles (EVs) are widely promoted as clean alternatives to conventional vehicles for reducing greenhouse gas (GHG) emissions from ground transportation. However, the battery undergoes a sophisticated degradation process during EV operations and its effects on EV energy consumption and GHG emissions are unknown. Here we show on a typical 24 kWh lithium-manganese-oxide–graphite battery pack that the degradation of EV battery can be mathematically modeled to predict battery life and to study its effects on energy consumption and GHG emissions from EV operations. We found that under US state-level average driving conditions, the battery life is ranging between 5.2 years in Florida and 13.3 years in Alaska under 30% battery degradation limit. The battery degradation will cause a 11.5–16.2% increase in energy consumption and GHG emissions per km driven at 30% capacity loss. This study provides a robust analytical approach and results for supporting policy making in prioritizing EV deployment in the U.S. Nature Publishing Group UK 2018-06-21 /pmc/articles/PMC6013442/ /pubmed/29930259 http://dx.doi.org/10.1038/s41467-018-04826-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Fan
Xie, Yuanyuan
Deng, Yelin
Yuan, Chris
Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title_full Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title_fullStr Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title_full_unstemmed Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title_short Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation
title_sort predictive modeling of battery degradation and greenhouse gas emissions from u.s. state-level electric vehicle operation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013442/
https://www.ncbi.nlm.nih.gov/pubmed/29930259
http://dx.doi.org/10.1038/s41467-018-04826-0
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