Distinctiveness of acoustic signals from multiple lithium-ion batteries

DOI

In support of published work.Data to be processed with open access code created by Elias Galiounas.Code repository contains instructions: https://github.com/EliasGaliounas/SonicBattContentsInvestigating whether state-of-charge estimation for a population of 7 batteries is possible using acoustic signals.The raw dataset is provided.Animations included: Acoustic signals obtained from multiple batteries during cycling. Includes time domain, frequency domain, and spectrograms.Trained machine learning models are provided.All data must be processed using the dedicated code repository created for this work, otherwise it is impossible to make sense of it.Battery chemistry: LiCoO2/Gr. Commercial, pouch cells.

Identifier
DOI https://doi.org/10.5522/04/26843797.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/48817564
Related Identifier HasPart https://ndownloader.figshare.com/files/48817573
Related Identifier HasPart https://ndownloader.figshare.com/files/48817609
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/26843797
Provenance
Creator Galiounas, Elias; Jervis, Rhodri; Robinson, James
Publisher University College London UCL
Contributor Figshare
Publication Year 2024
Rights https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Acoustics; Engineering Sciences; Mechanical and industrial Engineering; Mechanics and Constructive Mechanical Engineering