Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23523
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dc.contributor.authorWang, J-
dc.contributor.authorShen, B-
dc.contributor.authorWang, Z-
dc.contributor.authorAlsaadi, FE-
dc.contributor.authorAlharbi, KH-
dc.date.accessioned2021-11-15T15:23:53Z-
dc.date.available2021-01-01-
dc.date.available2021-11-15T15:23:53Z-
dc.date.issued2021-01-10-
dc.identifier.citationWang, J., Shen, B., Wang, Z., Alsaadi, F.E. and Alharbi, K.H. (2021) 'State-of-charge estimation for Li-ion batteries with uncertain parameters and uncorrelated/correlated noises: a recursive approach', International Journal of Systems Science, 52 (8), pp. 1675 - 1691. doi: 10.1080/00207721.2020.1868614.en_US
dc.identifier.issn0020-7721-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/23523-
dc.description.sponsorshipDeanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant no. (RG-7-135-41); Program of Shanghai Academic/Technology Research Leader [grant number 20XD1420100]; Natural Science Foundation of Shanghai of China [grant number 18ZR1401500].en_US
dc.format.extent1675 - 1691-
dc.format.mediumPrint-Electronic-
dc.language.isoenen_US
dc.publisherInforma UK Limited, Taylor & Francis Groupen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Systems Science on 10 Jan 2021, available online: https://www.tandfonline.com/doi/full/10.1080/00207721.2020.1868614.-
dc.subjectcorrelated noisesen_US
dc.subjectenergy and power systemsen_US
dc.subjectLi-ion batteryen_US
dc.subjectrecursive estimationen_US
dc.subjectstate-of-charge (SOC) estimationen_US
dc.subjectuncertain parametersen_US
dc.titleState-of-charge estimation for Li-ion batteries with uncertain parameters and uncorrelated/correlated noises: a recursive approachen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/00207721.2020.1868614-
dc.relation.isPartOfInternational Journal of Systems Science-
pubs.issue8-
pubs.publication-statusPublished-
pubs.volume52-
dc.identifier.eissn1464-5319-
Appears in Collections:Dept of Computer Science Research Papers

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