Projects: DEMOBASE: DEsign and MOdelling for improved BAttery Safety and Efficiency

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Number of items: 2.

2022

Volltext
Bordes, A. ; Danilov, D. L. ; Desprez, P. ; Lecocq, A. ; Marlair, G. ; Truchot, B. ; Dahmani, M. ; Siret, C. ; Laurent, S. ; Herreyre, S. ; Dominget, A. ; Hamelin, L. ; Rigobert, G. ; Benjamin, S. ; Legrand, N. ; Belerrajoul, M. ; Maurer, W. ; Chen, Z. ; Raijmakers, L. H. J. ; Li, D. ; Zhou, J. ; Notten, P. H. L. ; Perlo, P. ; Biasiotto, M. ; Introzzi, R. ; Petit, M. ; Martin, J. ; Bernard, J. ; Koffel, S. ; Lorentz, Vincent ; Durling, E. ; Kolari, S. ; Wang, Z. ; Massazza, M. ; Lamontarana, S.:
A holistic contribution to fast innovation in electric vehicles : An overview of the DEMOBASE research project.
In: eTransportation. Vol. 11 (2022) . - 100144.
DOI: https://doi.org/10.1016/j.etran.2021.100144

2019

Volltext
Bockrath, S. ; Rosskopf, A. ; Koffel, S. ; Waldhör, Stefan ; Srivastava, K. ; Lorentz, Vincent:
State of Charge Estimation using Recurrent Neural Networks with Long Short-Term Memory for Lithium-Ion Batteries.
2019
Event: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society , Oct. 14–17, 2019 , Lisbon, Portugal.
(Conference item: Conference , Speech with paper )
DOI: https://doi.org/10.1109/IECON.2019.8926815

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