InteKal – Intelligent calendering

In the German competence cluster for intelligent battery cell production (InZePro), the leading research institutions in the field of lithium-ion battery cell production are joining forces to build up and expand knowledge regarding production processes and cross-process interdependencies. The objective is to increase the productivity and the output of cell production through the comprehensive optimization of entire production systems. Methods and solutions from the fields of Industry 4.0 and artificial intelligence (AI) are being applied.

The InteKal project - Intelligent calendering - is pursuing the goal of application-oriented production for the calendering of battery electrodes and the efficient determination of the required process parameters. The aim is to achieve a decrease in scrap and a reduction in process time, which ultimately translates into a reduction in manufacturing costs. The targeted project goal is to enable the calendering systems to process battery electrodes agilely and autonomously by means of an adaptive process control. For this purpose, the production systems are equipped with sensors and the structures for efficient data acquisition and processing are developed. At the same time, real-time capable models are established, which not only enable more efficient processing, but also define the requirements and boundary conditions for each subsequent process step at the same time. This results in a holistic approach, enabling an increase in efficiency for the entire production chain through intelligent calendering.

Within the scope of the project, a calendering system will be developed and set up at the iwb and equipped with sensors for defect detection and measuring systems for the coating thickness. This provides the foundation for the development of in-line data acquisition and analysis for the feedback into an innovative process control system. The focus of the research activities at the iwb is the development of a digital machine twin and the construction of AI-supported models, which are combined with a closed-loop control. The latter represents a closed control system which adjusts the roll gap of the calendering machine. The aim is to initiate a systematic and detailed investigation of the system behavior and, in particular, to enable in-line measurement of the coating thickness of the electrode web.

Acknowledgement

The project is funded by the German Federal Ministry of Education and Research (BMBF) under project number 03XP0348B and  supervised by the Project Management Organization Projektträger Jülich (PTJ). We thank the BMBF and the PTJ for funding the project and the excellent and trustful cooperation.

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