Hochschulschrift
A data-driven fleet service: state of health forecasting of lithium-ion batteries
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISBN
-
9783658431877
3658431873
- Dimensions
-
21 cm
- Extent
-
xxxii, 227 Seiten
- Language
-
Englisch
- Notes
-
Illustrationen
Bergische Universität Wuppertal, Dissertation, 2023
- Bibliographic citation
-
AutoUni-Schriftenreihe / Auto-Uni Wolfsburg ; volume 170
- Keyword
-
Batteriefahrzeug
Lithium-Ionen-Akkumulator
Structural Health Monitoring
- Event
-
Veröffentlichung
- (where)
-
Wiesbaden, Germany
- (who)
-
Springer Vieweg
- (when)
-
[2024]
- Creator
- Contributor
- Table of contents
- Rights
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Last update
-
11.06.2025, 1:43 PM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Bülow, Friedrich von
- Springer Fachmedien Wiesbaden
- Springer Vieweg
Time of origin
- [2024]
Other Objects (12)
Data-driven systematic parameter identification of an electrochemical model for lithium-ion batteries with artificial intelligence
Lithium-Ion Batteries: basics and applications
New Materials for Lithium-Ion Batteries
New materials for lithium-ion batteries
Conversion/alloying anodes for lithium-ion batteries
Chemo-mechanical Modeling of Lithium-Ion Batteries
Nonlinear Frequency Response Analysis of Lithium-Ion Batteries
Degradation Mechanisms in NMC-Based Lithium-Ion Batteries
Simple Spec-Based Modelling of Lithium-Ion Batteries
Spruce Hard Carbon Anodes for Lithium-Ion Batteries
Realizing high-performance silicon-based lithium-ion batteries
Microscopic Investigations of Degradation in Lithium-Ion Batteries
Data-driven systematic parameter identification of an electrochemical model for lithium-ion batteries with artificial intelligence
Lithium-Ion Batteries: basics and applications
New Materials for Lithium-Ion Batteries
New materials for lithium-ion batteries
Conversion/alloying anodes for lithium-ion batteries
Chemo-mechanical Modeling of Lithium-Ion Batteries
Nonlinear Frequency Response Analysis of Lithium-Ion Batteries
Degradation Mechanisms in NMC-Based Lithium-Ion Batteries
Simple Spec-Based Modelling of Lithium-Ion Batteries
Spruce Hard Carbon Anodes for Lithium-Ion Batteries
Realizing high-performance silicon-based lithium-ion batteries
Microscopic Investigations of Degradation in Lithium-Ion Batteries
Data-driven systematic parameter identification of an electrochemical model for lithium-ion batteries with artificial intelligence
Lithium-Ion Batteries: basics and applications
New Materials for Lithium-Ion Batteries
New materials for lithium-ion batteries
Conversion/alloying anodes for lithium-ion batteries
Chemo-mechanical Modeling of Lithium-Ion Batteries
Nonlinear Frequency Response Analysis of Lithium-Ion Batteries
Degradation Mechanisms in NMC-Based Lithium-Ion Batteries
Simple Spec-Based Modelling of Lithium-Ion Batteries
Spruce Hard Carbon Anodes for Lithium-Ion Batteries
Realizing high-performance silicon-based lithium-ion batteries