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Record Nr. |
UNINA9910831500403321 |
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Autore |
von Bülow Friedrich |
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Titolo |
A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries [[electronic resource] /] / by Friedrich von Bülow |
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Pubbl/distr/stampa |
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Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Vieweg, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (0 pages) |
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Collana |
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AutoUni – Schriftenreihe, , 2512-1154 ; ; 170 |
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Disciplina |
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Soggetti |
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Automotive engineering |
Vehicles |
Automobile industry and trade |
Electric power production |
Automotive Engineering |
Vehicle Engineering |
Automotive Industry |
Electrical Power Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Towards State of Health Forecasting of Lithium-Ion Batteries -- Structure Literature Survey of Related Work -- Battery Cell State of Health Forecasting -- Transfer of Battery Cell State of Health Forecasting -- Battery System State of Health Forecasting -- Concept for a Technical Implementation. |
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Sommario/riassunto |
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Given the limitations of state-of-the-art methods, this book presents a state of health (SOH) forecasting method that is suitable for lithium-ion battery (LIB) systems in real-world battery electric vehicle operation. Its histogram-based features can capture the higher operational variability compared to constant and controlled laboratory operation. Also, the transferability of a trained machine learning model to new LIB cell types and new operational domains is investigated. The presented SOH forecasting method can be provided as a cloud service via a web or smartphone app to fleet managers. Forecasting the SOH enables fleet managers of battery electric vehicle fleets to forecast and plan vehicle |
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