Perfecting battery cell production

Quick and inexpensive, flexible and with high product quality: These are the requirements to be met by future manufacture of battery cells. The Cluster of Competence for Intelligent Battery Cell Production (InZePro) is coordinated by Karlsruhe Institute of Technology (KIT). It is aimed at holistically optimizing production systems and making them more flexible in terms of quantity, format, material, and technology. For this purpose, cross-process, data-driven optimization approaches and Industry 4.0 solutions are developed.

To meet current requirements, battery cells will have to be produced in Germany in an economically efficient way in small, medium, and large series for various applications and markets. Moreover, innovative approaches are needed to enhance productivity and reduce production costs. This is the initial situation of the Cluster of Competence for Intelligent Battery Cell Production (InZePro) that is funded by the Federal Ministry of Education and Research (BMBF) with a total of about EUR 44 million.

Meanwhile, the InZePro research projects have achieved first results focusing  on agile plant technology, digitalization of certain production steps and the entire production system, as well as on virtual production systems and the use of AI in production, writes KIT in a press release.

Guideline for Digitalization and Industry 4.0

To digitalize battery cell production, toolboxes have been developed for machine and plant technology, process engineering, planning, control and logistics, and quality management. They can be used to evaluate and further develop already existing technical and organizational Industry 4.0 approaches to battery cell production. The ultimate goal is to accelerate systematic implementation of digitalization and Industry 4.0 in battery cell production. This will rapidly and efficiently increase future competitiveness of battery cell production. In the last project stage, the results will be summarized and published in a guideline.

Digital Twin and Machine Learning

A digital twin was presented to study and evaluate various future scenarios and their impacts on a flexible battery production system  In this case, the digital twin is a type of simulation parallel to operation, which is made for planning and control purposes.

In addition, a tracking and tracing concept with various technologies for marking electrodes has been developed. In this way, battery components can be traced back over the complete process chain. In various projects, data structuring and machine learning methods have been conceived. For instance, plants are equipped to recognize workflows and patterns in the production process and to independently respond to errors.

Quality Assurance

The results are reviewed by an expert group that accompanies the projects and ensures close collaboration of research and industry. “Thanks to our active collaboration within the projects, we cover all process steps of lithium-ion battery cell production. This will help manufacturing companies in e.g. automotive industry, to increase productivity even in times of a volatile order situation and high product variance, to reduce costs, and increase product quality,” says Professor Jürgen Fleischer, Head of wbk Institute of Production Science at KIT and Chairman of the InZePro Cluster.

About 200 researchers from 28 German research institutions are involved in the InZePro Cluster of Competence. These are four institutes of KIT, four institutes of TU Braunschweig, three institutes of RWTH Aachen University, two institutes of the Technical University of Munich, University of Bayreuth, University of Applied Sciences in Landshut, Technical University of Aschaffenburg, Helmholtz Institute Ulm, the Center for Solar Energy and Hydrogen Research Baden-Württemberg, and ten institutes of Fraunhofer Society. Funding of the Cluster is scheduled to end in 2023.

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