BATTwin Reaches Key Milestones in Digital Twin Development for Battery Cell Manufacturing
HUN-REN SZTAKI, Work Package 3 (WP3) leader of the CINEA-funded BATTwin project (grant agreement No. 101137954), is pleased to announce the successful completion of three major deliverables under WP3!
This milestone represent a significant step forward in the development of a comprehensive Digital Twin framework for li-ion battery cell manufacturing and the conclusion of the joint effort of the colleagues of Sivas University, University of Oldenburg, University of Warwick and HUN-REN SZTAKI.
More on BATTwin
BATTwin aims to develop a novel Multilevel Digital Twin platform towards Zero-Defect Manufacturing in battery production, that will reduce defect rates in battery production lines. The solution integrates four pillars, namely
- a multi-sensor data acquisition and management layer, supported by data semantics through a Digital Battery Passport data model,
- process-level digital twins, modelling the critical stages of electrode manufacturing, cell assembly and conditioning through multi-physics, data-driven and hybrid approaches,
- system-level digital twins, based on simulation and analytical modelling,
- user-centric, goal-driven digital twin workflows, increasing the explainability of digital twins and driving the user in system design and control.
The approach is to be tested in two industrial pilots producing different battery chemistries and geometries, validating the flexibility and scalability of the approach towards Zero Defect European Gigafactories.
More on WP 3 and Key Deliverables
WP3 aims to establish an integrated, multi-physics process level Digital Twin framework for li-ion battery manufacturing, taking into account material and molecular dynamics as well as electrochemical models, process models, physics-based, AI models, and reduced-order models.
In this context, deliverable 3.1 establishes a high-level modelling foundation covering the full battery cell production chain, from material preparation to final testing. It brings together multiple modelling approaches into a unified framework capable of representing complex manufacturing processes and supporting future optimization and control strategies.
To support the latter, deliverable 3.2 introduces a flexible and adaptive modelling approach that enables improved alignment between virtual and physical production environments, for more efficient design, validation, and commissioning of key processes, choosing the modelling of the stacking machine as an illustration.
Lastly, deliverable 3.3 completes the WP3 scope by enabling integration across models and systems. It defines, thus, the architecture and protocols required to connect Digital Twins with a centralized data management platform, paving the way for scalable analytics, informed decision-making, and enhanced process coordination.
Together, these results mark an important advancement toward a modular, data-driven, and industry-ready Digital Twin ecosystem.
The BATTwin consortium will build on this progress in the next phases of the project, focusing on validation, optimization, the specific user-oriented digital twin workflow construction and finally real-world deployment.
For more information, please visit the project official website.
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Project Coordinator
Marcello COLLEDANI,
Professor, Department of Mechanical Engineering, Politecnico di Milano,
WP 3 Lead
Gergely HORVÁTH PhD,
Research fellow, Research Laboratory on Engineering & Management Intelligence, SZTAKI
Exploitation, Communication and Dissemination
Dr Bojan Boskovic
Chief Executive Officer, Cambridge Nanomaterials Technology Ltd.
Claudia Lung
International Projects Leader, Upcell Alliance
Email: claudia.lung@upcell.org
