Datenbasierte Fertigungsoptimierung von Batteriezellen auf Basis von End-of-line Daten durch massiven Einsatz von Machine Learning-Algorithmen und inline Analytik (DAFODIL)
Basic data for this project
Type of project: Participation in federally funded joint project
Duration at the University of Münster: 01/09/2021 - 31/08/2025
Description
Keywords: Batteriezellen; Sensorik; Machine Learning
Funding identifier: 03XP0389F
Funder / funding scheme:
- Federal Ministry of Research, Technology and Space (BMFTR)
Project management at the University of Münster
| Börner, Markus | |
| Niehoff, Philip | |
| Winter, Martin |
Applicants from the University of Münster
| Winter, Martin |
Project partners outside the University of Münster
- RWTH Aachen University (RWTH)Germany
- Siemens AGGermany
- Safion GmbHGermany
- Customcells Tübingen GmbHGermany
- SURAGUS GmbHGermany