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A novel time series forecasting model for capacity degradation path prediction of lithium-ion battery pack.

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Title: A novel time series forecasting model for capacity degradation path prediction of lithium-ion battery pack.
Authors: Chen, Xiang1, Yang, Yingjie2, Sun, Jie3, jie.sun@njxzc.edu.cn, Deng, Yelin1, yelin.deng@suda.edu.cn, Yuan, Yinnan1
Source: Journal of Supercomputing; May2024, Vol. 80 Issue 8, p10959-10984, 26p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 177062472
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A novel time series forecasting model for capacity degradation path prediction of lithium-ion battery pack.
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  Data: <searchLink fieldCode="AU" term="%22Chen%2C+Xiang%22">Chen, Xiang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Yang%2C+Yingjie%22">Yang, Yingjie</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Sun%2C+Jie%22">Sun, Jie</searchLink><relatesTo>3</relatesTo>, <i>jie.sun@njxzc.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Deng%2C+Yelin%22">Deng, Yelin</searchLink><relatesTo>1</relatesTo>, <i>yelin.deng@suda.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Yuan%2C+Yinnan%22">Yuan, Yinnan</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>; May2024, Vol. 80 Issue 8, p10959-10984, 26p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=177062472
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s11227-023-05859-z
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      – Code: eng
        Text: English
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        PageCount: 26
        StartPage: 10959
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      – TitleFull: A novel time series forecasting model for capacity degradation path prediction of lithium-ion battery pack.
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            NameFull: Chen, Xiang
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            NameFull: Yang, Yingjie
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            NameFull: Sun, Jie
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            NameFull: Deng, Yelin
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            – D: 15
              M: 05
              Text: May2024
              Type: published
              Y: 2024
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              Value: 80
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