Gast ::
000818642 001__ 818642 000818642 005__ 20250930090624.0 000818642 0247_ $$2datacite_doi$$a10.18154/RWTH-2021-04545 000818642 037__ $$aRWTH-2021-04545 000818642 041__ $$aEnglish 000818642 1001_ $$0P:(DE-82)IDM01459$$aSauer, Dirk Uwe$$b0$$urwth 000818642 245__ $$aTime-series cyclic aging data on 48 commercial NMC/graphite Sanyo/Panasonic UR18650E cylindrical cells 000818642 260__ $$c2021 000818642 3367_ $$2BibTeX$$aMISC 000818642 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1623335500_15124 000818642 3367_ $$026$$2EndNote$$aChart or Table 000818642 3367_ $$2DataCite$$aDataset 000818642 3367_ $$2ORCID$$aDATA_SET 000818642 3367_ $$2DINI$$aResearchData 000818642 520__ $$aThis dataset contains time-series data (time, current, voltage, temperature) of a cyclic aging test of 48 lithium-ion battery cells. In the experiment, 48 cells of the same type were aged with the same profile under equal conditions. Prior to aging, the initial performance was determined by a comprehensive begin-of-life (BOL) test. Aging reference parameter tests (RPT) were conducted in regular intervals to determine the current cell performance. The cells used in this investigation are Sanyo/Pana-sonic UR18650E cylindrical cells which are commercially available and produced in large quantities in an established fabrication process. This type uses a carbon anode and NMC as a cathode material. The dataset consists of two files. The file Rawdata.zip contains individual .csv files with the time series data for every tested cell. The file Content.pdf contains information about the test setup, data, and license. 000818642 591__ $$aGermany 000818642 7870_ $$0RWTH-2021-05565$$aLi, Weihan et.al.$$dNew York, NY [u.a.] : Elsevier, 2021$$iRelatedTo$$tOne-shot battery degradation trajectory prediction with deep learning 000818642 8564_ $$uhttps://git.rwth-aachen.de/isea/battery-degradation-trajectory-prediction 000818642 8564_ $$uhttps://publications.rwth-aachen.de/record/818642/files/RWTHPublications_Forschungsdaten_signed.pdf 000818642 8564_ $$uhttps://publications.rwth-aachen.de/record/818642/files/Content_RWTH-2021-04545.pdf$$yOpenAccess 000818642 8564_ $$uhttps://publications.rwth-aachen.de/record/818642/files/Rawdata.zip$$yOpenAccess 000818642 909CO $$ooai:publications.rwth-aachen.de:818642$$popenaire$$popen_access$$pVDB$$pdriver 000818642 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-82)IDM01459$$aRWTH Aachen$$b0$$kRWTH 000818642 9141_ $$y2021 000818642 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 000818642 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0 000818642 9201_ $$0I:(DE-82)618310_20140620$$k618310$$lLehrstuhl für Elektrochemische Energiewandlung und Speichersystemtechnik$$x0 000818642 961__ $$c2021-06-10T16:40:52.896048$$x2021-05-07T10:09:48.969898$$z2021-06-10T16:40:52.896048 000818642 9801_ $$aFullTexts 000818642 980__ $$adataset 000818642 980__ $$aVDB 000818642 980__ $$aUNRESTRICTED 000818642 980__ $$aI:(DE-82)618310_20140620