ReFlexBat - Adjustable coating unit for flexible coating of battery electrodes
- Contact:
- Project Group:
Florian Denk – wbk Institute of Production Science
Dr.-Ing. Philip Scharfer – Thin Film Technology (TFT)
Dr. Constanze Hasterok – Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
- Funding:
InZePro Cluster (Bundesministeriums für Bildung und Forschung)
- Partner:
Institute of Production Science (wbk)
Thin Film Technology (TFT)
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
- Startdate:
01.03.2021
- Enddate:
31.08.2024
Objectives and Results
The aim is to achieve fast and autonomous adjustment of the process parameters and thus reduce waste. The newly developed coating module thus enables sustainable cell production, especially in small and medium series, and represents an important element for the production of a "green battery". The process knowledge of the system operator is also to be formalised and transferred to the control system so that coating in accordance with the quality requirements can be achieved even under new production conditions without additional preliminary tests, lengthy start-up processes or manual intervention.
Contents and Approach
Contents and Approach In a holistic approach, the "ReFlexBat" project aims to develop a highly flexible, self-regulating coating unit based on generally applicable findings and methods, which reacts automatically to variable process conditions, e.g. changes in the electrode formulation or wet film geometry, and can coat high-quality battery electrodes in a reproducible, format-flexible manner. This significantly shortens the start-up time of the coating step. When changing batches, for example, the coating module can switch between electrodes of different widths or paste compositions quickly and flexibly without the need for manual adjustment. The selected approaches ensure immediate scalability, which will lead to a sustainable strengthening of the innovation pipeline as part of the "Forschungsfabrik Batterie" umbrella concept. The project is being implemented using innovative system technology combined with data-driven modelling and state-of-the-art machine learning (ML) algorithms.
Project Volume
1,4 Mio. €
Further Information