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Lithium-ion battery data and where to find it

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Sep 2021 United Kingdom Publisher:Elsevier BVJournal:Energy and AI, volume 5, page 100,081 (issn: 2666-5468,

Authors: Gonçalo dos Reis; Calum Strange; Mohit Yadav; Shawn Li;

doi: 10.1016/j.egyai.2021.100081

handle: 20.500.11820/c9e402fe-d1c5-4547-b870-ae46d672d8ba

Lithium-ion battery data and where to find it

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Abstract

Lithium-ion batteries are fuelling the advancing renewable-energy based world. At the core of transformational developments in battery design, modelling and management is data. In this work, the datasets associated with lithium batteries in the public domain are summarised. We review the data by mode of experimental testing, giving particular attention to test variables and data provided. Alongside highlighted tools and platforms, over 30 datasets are reviewed.

Country

United Kingdom

Related Organizations

Indian Institute of Technology Kanpur
India
Indian Institute of Technology Kanpur
India
University of Edinburgh
United Kingdom

Keywords

Battery tests, Lithium battery, TK1-9971, QA76.75-76.765, Machine learning, Public data, Electrical engineering. Electronics. Nuclear engineering, Computer software, Battery data

3 Research products, page 1 of 1

1 Data sources, page 1 of 1

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	221
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 0.1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
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