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Article

Digitalization Platform for Mechanistic Modeling of Battery Cell Production

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Institute of Machine Tools and Production Technology (IWF), Sustainable Manufacturing and Life Cycle Engineering, Technische Universität Braunschweig, Langer Kamp 19b, 38106 Braunschweig, Germany
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Battery LabFactory Braunschweig (BLB), Technische Universität Braunschweig, Langer Kamp 19, 38106 Braunschweig, Germany
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Institute of Energy and Process Systems Engineering (InES), Technische Universität Braunschweig, Franz-Liszt-Straße 35, 38106 Braunschweig, Germany
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Institute for Particle Technology (iPAT), Technische Universität Braunschweig, Franz-Liszt-Straße 35, 38106 Braunschweig, Germany
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Institute of Applied Materials—Electrochemical Technologies, Karlsruhe Institute of Technology, Adenauerring 20b, 76131 Karlsruhe, Germany
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Author to whom correspondence should be addressed.
Academic Editors: Jonathan Sze Choong Low, Mark Mennenga and Carlo Brondi
Sustainability 2022, 14(3), 1530; https://doi.org/10.3390/su14031530
Received: 15 December 2021 / Revised: 12 January 2022 / Accepted: 25 January 2022 / Published: 28 January 2022
The application of batteries in electric vehicles and stationary energy-storage systems is widely seen as a promising enabler for a sustainable mobility and for the energy sector. Although significant improvements have been achieved in the last decade in terms of higher battery performance and lower production costs, there remains high potential to be tapped, especially along the battery production chain. However, the battery production process is highly complex due to numerous process–structure and structure–performance relationships along the process chain, many of which are not yet fully understood. In order to move away from expensive trial-and-error operations of production lines, a methodology is needed to provide knowledge-based decision support to improve the quality and throughput of battery production. In the present work, a framework is presented that combines a process chain model and a battery cell model to quantitatively predict the impact of processes on the final battery cell performance. The framework enables coupling of diverse mechanistic models for the individual processes and the battery cell in a generic container platform, ultimately providing a digital representation of a battery electrode and cell production line that allows optimal production settings to be identified in silico. The framework can be implemented as part of a cyber-physical production system to provide decision support and ultimately control of the production line, thus increasing the efficiency of the entire battery cell production process. View Full-Text
Keywords: digitalization platform; process modeling; battery cell modeling; battery electrode structure; simulation; global sensitivity analysis; lithium-ion battery digitalization platform; process modeling; battery cell modeling; battery electrode structure; simulation; global sensitivity analysis; lithium-ion battery
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MDPI and ACS Style

Thomitzek, M.; Schmidt, O.; Ventura Silva, G.; Karaki, H.; Lippke, M.; Krewer, U.; Schröder, D.; Kwade, A.; Herrmann, C. Digitalization Platform for Mechanistic Modeling of Battery Cell Production. Sustainability 2022, 14, 1530. https://doi.org/10.3390/su14031530

AMA Style

Thomitzek M, Schmidt O, Ventura Silva G, Karaki H, Lippke M, Krewer U, Schröder D, Kwade A, Herrmann C. Digitalization Platform for Mechanistic Modeling of Battery Cell Production. Sustainability. 2022; 14(3):1530. https://doi.org/10.3390/su14031530

Chicago/Turabian Style

Thomitzek, Matthias, Oke Schmidt, Gabriela Ventura Silva, Hassan Karaki, Mark Lippke, Ulrike Krewer, Daniel Schröder, Arno Kwade, and Christoph Herrmann. 2022. "Digitalization Platform for Mechanistic Modeling of Battery Cell Production" Sustainability 14, no. 3: 1530. https://doi.org/10.3390/su14031530

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