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Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM.

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Title: Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM.
Authors: Wang, Pengcheng1, Liu, Lu1,2, Yu, Qun2,3, Hou, Dongdong3,4, Li, Enjie1,2, Yu, Haijun2,4, Liu, Shumin3,4, Qin, Lizhen4, Zhu, Yunhai3, zhuyh@sdas.org
Source: Batteries; Jan2026, Vol. 12 Issue 1, p12, 28p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191261093
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM.
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  Data: <searchLink fieldCode="JN" term="%22Batteries%22">Batteries</searchLink>; Jan2026, Vol. 12 Issue 1, p12, 28p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191261093
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      – Type: doi
        Value: 10.3390/batteries12010012
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      – Code: eng
        Text: English
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        PageCount: 28
        StartPage: 12
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      – TitleFull: Prediction of the Remaining Useful Life of Lithium-Ion Batteries Based on the Optimized TTAO-VMD-BiLSTM.
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              Text: Jan2026
              Type: published
              Y: 2026
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              Value: 12
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