PEM Researches Intelligent Start-up Control for More Flexible Battery Cell Production

In the "InTeAn" project, the chair "Production Engineering of E-Mobility Components" (PEM) chair of RWTH Aachen University and two other major research institutions are working on an intelligent start-up control system for the cost-reduced and flexible production of future battery cells. The joint project is part of the federally funded competence cluster "Intelligent Battery Cell Production" (InZePro).

Fewer rejects lead to lower production costs

If it is possible to reduce the scrap generated in the production process, the corresponding increase in raw material and resource efficiency will lead directly to a reduction in battery production costs. Intelligent process control can positively influence currently existing manufacturing technologies. As a result, both production personnel and manufacturing machines spend less time on defective rejects. In addition, it can be assumed that the future production of lithium-ion batteries will involve the processing of new or different materials on a single system. As a result of the material change, the machines must be regularly shut down and then restarted. In the production of small batches, such machine start-up phases occur very frequently, which harbor great potential for optimization in terms of the duration until a stable process producing good parts is achieved.

New cell formats require more flexible production parameters

In addition to the expected material diversity, new large-format cells also lead to a necessary flexibility of the production parameters. For this reason, the "InTeAn" project is pursuing the goal of developing a production line that enables process capability for different battery concepts. By using data-driven methods for modeling and the design of experiments on the production lines, the process is to be actively elucidated, influenced in terms of control technology, optimized and prepared in a way that can be understood by humans. In addition, an improved operating model or an optimal start-up methodology is to be designed that enables self-learning plant control based on artificial intelligence methods. As a result, startup scrap is to be reduced by ten percent. The project team is focusing on the production of special formats. Building on extensive process monitoring, machine learning methods are also to be used to investigate and gradually adjust possible parameters of the process stages.



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The project

  • "InTeAn": Intelligent start-up control for cost-reduced and flexible production of future battery cells

Research objectives

  • Development of a production line with process capability for different battery concepts
  • Design of an improved operating model and optimal start-up methodology to enable self-learning plant control

Research and project partners

PEM of RWTH Aachen University (project coordinator)
wbk Institute of Production Science (Karlsruhe Institute of Technology)
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB)


  • 03/01/2021 through 02/29/2024

Project sponsor

Projektträger Jülich (PtJ)

Funding code

  • 03XP0357A


Federal Ministry of Education and Research (BMBF)