PEM Develops Intelligent Forming Systems for Lithium-Ion Batteries

Cell formation Copyright: © PEM RWTH Aachen University

The chair "Production Engineering of E-Mobility Components" (PEM) of RWTH Aachen University is developing intelligent forming systems for the optimization and diagnosis of battery cell properties in the joint project "InForm". Together with three other nationally leading institutes, PEM is pursuing the goal of using artificial intelligence and digitization to accelerate the production of lithium-ion batteries as well as to reduce process costs and increase quality.

Forming customized batteries

The goal is to be achieved with the help of two intelligent optimization circuits. The project partners intend to use artificial intelligence and physicochemical models to actively intervene in the formation process in order to achieve positive long-term effects and ensure a safe process. In this way, it will be shown that it is possible to form customized batteries with shorter process times, for example with a view to improved electrical properties or service life, and to develop demand-oriented forming procedures in an accelerated manner.

Time-consuming and cost-intensive

Customized batteries with automated quality assessment are considered the key to intelligent and highly productive formation for competitive battery production. "Forming" is the term used to describe the final production step that plays a decisive role in determining the subsequent performance, safety and longevity of the lithium-ion battery. During this process, the assembled battery cell is charged and discharged for the first time. This programmed formation cycle is run through once or several times. During this process, the SEI layer, which is crucial for the subsequent performance characteristics of the cell, is formed on the electrodes. The cell then matures for several days or weeks. Only then can it be finally determined whether the cell has the desired quality in terms of its performance data. However, the forming process is extremely time-consuming, and the investment costs for the "forming towers" as corresponding storage capacities are very high.

Quality determination at the earliest possible stage

Until now, the success of cell assembly and formation can only be assessed after the "end of line" test following formation or even after maturation. In the "InForm" project, however, quality is to be determined beforehand with the aid of online measurement technology and artificial intelligence that records cell parameters during forming. In this way, rejects should occur much earlier in the process, which in turn saves costs and time. In addition to electrochemical impedance spectroscopy (EIS), an ultrasound method is also planned to be used for this purpose. Ultrasonic measurement on battery cells is currently still at an early stage of research and could therefore provide important impetus.

The project is part of the federally funded competence cluster "Intelligent Battery Cell Production" (InZePro).



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The project

"InForm": Functional integration of formation and quality assessment of lithium-ion batteries using model-based methods and artificial intelligence

Research objectives

  • Design of intelligent battery formation systems
  • Acceleration, process cost reduction and quality improvement of lithium-ion batteries based on artificial intelligence and digitization in production
  • Development of two intelligent optimization circuits

Research and project partners

Helmholtz Institute Ulm (HIU) for Electrochemical Energy Storage (Karlsruhe Institute of Technology) (project coordinator)
PEM of RWTH Aachen University
Center for Solar Energy and Hydrogen Research Baden-Württemberg (ZSW)
Institute for High Voltage Technology and Power Systems (elenia) (TU Braunschweig)


  • 03/01/2021 through 02/29/2024

Project management

Projektträger Jülich (PtJ)

Funding code

  • 03XP0363B


Federal Ministry of Education and Research (BMBF)