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Lithium-ion battery aging dataset based on electric vehicle real-driving profiles
This paper describes the experimental dataset of lithium-ion battery cells subjected to a typical electric vehicle discharge profile and periodically characterized through diagnostic tests. Data were collected at the Stanford Energy Control Laboratory, at Stanford University. The INR21700-M50T batte...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892076/ https://www.ncbi.nlm.nih.gov/pubmed/35252504 http://dx.doi.org/10.1016/j.dib.2022.107995 |
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author | Pozzato, Gabriele Allam, Anirudh Onori, Simona |
author_facet | Pozzato, Gabriele Allam, Anirudh Onori, Simona |
author_sort | Pozzato, Gabriele |
collection | PubMed |
description | This paper describes the experimental dataset of lithium-ion battery cells subjected to a typical electric vehicle discharge profile and periodically characterized through diagnostic tests. Data were collected at the Stanford Energy Control Laboratory, at Stanford University. The INR21700-M50T battery cells with graphite/silicon anode and Nickel-Manganese-Cobalt cathode were tested over a period of 23 months according to the Urban Dynamometer Driving Schedule (UDDS) discharge driving profile and the Constant Current (CC)-Constant Voltage (CV) charging protocol designed at different charging rates – ranging from C/4 to 3C. Ten (10) cells are tested in a temperature-controlled environment (23 [Formula: see text] C). A periodic assessment of battery degradation during life testing is accomplished via Reference Performance Tests (RPTs) comprising of capacity, Hybrid Pulse Power Characterization (HPPC), and Electrochemical Impedance Spectroscopy (EIS) tests. The dataset allows for the characterization of battery aging under real-driving scenarios, enabling the development of models and management strategies in electric vehicle applications. |
format | Online Article Text |
id | pubmed-8892076 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88920762022-03-04 Lithium-ion battery aging dataset based on electric vehicle real-driving profiles Pozzato, Gabriele Allam, Anirudh Onori, Simona Data Brief Data Article This paper describes the experimental dataset of lithium-ion battery cells subjected to a typical electric vehicle discharge profile and periodically characterized through diagnostic tests. Data were collected at the Stanford Energy Control Laboratory, at Stanford University. The INR21700-M50T battery cells with graphite/silicon anode and Nickel-Manganese-Cobalt cathode were tested over a period of 23 months according to the Urban Dynamometer Driving Schedule (UDDS) discharge driving profile and the Constant Current (CC)-Constant Voltage (CV) charging protocol designed at different charging rates – ranging from C/4 to 3C. Ten (10) cells are tested in a temperature-controlled environment (23 [Formula: see text] C). A periodic assessment of battery degradation during life testing is accomplished via Reference Performance Tests (RPTs) comprising of capacity, Hybrid Pulse Power Characterization (HPPC), and Electrochemical Impedance Spectroscopy (EIS) tests. The dataset allows for the characterization of battery aging under real-driving scenarios, enabling the development of models and management strategies in electric vehicle applications. Elsevier 2022-02-25 /pmc/articles/PMC8892076/ /pubmed/35252504 http://dx.doi.org/10.1016/j.dib.2022.107995 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Pozzato, Gabriele Allam, Anirudh Onori, Simona Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title | Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title_full | Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title_fullStr | Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title_full_unstemmed | Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title_short | Lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
title_sort | lithium-ion battery aging dataset based on electric vehicle real-driving profiles |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892076/ https://www.ncbi.nlm.nih.gov/pubmed/35252504 http://dx.doi.org/10.1016/j.dib.2022.107995 |
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