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CORDIS - EU research results
CORDIS

DIGITAL SOLUTIONS FOR ACCELERATED BATTERY TESTING

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Report on computational framework for non-invasive parameterisation (opens in new window)

Report on algorithms for Bayesian inference combined with physics-based models for non-invasive parametrization of battery cells. This is linked to task 5.1 and will be used in subsequent work in the project.

Initial plan for dissemination and exploitation including communication activities (opens in new window)

Initial plan for dissemination, exploitation and communication activities. This will be followed and reviewed at regular intervals. This deliverable is associated with task 1.4.

Innovation and exploitation plan (opens in new window)

Plan for innovation and exploitation specific to creating impact in industry. This deliverable is associated with task 1.4.

Battery pack upscaling and use-case report (opens in new window)

Report on upscaling of the cell level digital twins to battery pack level for specific use-cases. This is linked to task 7.1 and will be used in subsequent work packages.

Project handbook and risk management table. (opens in new window)

Handbook with guidelines for project participants plus table of risks to project completion and mitigation measures.This will be distributed to project participants to ensure smooth running of the project and consistent standards from all partners. This deliverable is associated with task 1.2.

Revised data management plan (opens in new window)

Updated plan for how to handle data generated in the project. This will be made available to all participants to ensure consistent standards throughout the project.This deliverable is associated with task 1.3.

Data management plan (opens in new window)

Plan for how to handle data generated in the project. This will be made available to all participants to ensure consistent standards throughout the project. This forms part of task 1.3.

Reduced order cell models for lifetime assessment (opens in new window)

Simplified simulation models for accelerated lifetime assessment. This is linked to taks 6.1 and will be used throughout the project.

Digital twin framework (opens in new window)

Open source framework for battery cell digital twin. This is associated with task 3.1 and will be used throughout the project.

Ageing and safety testing framework (opens in new window)

Framework for reducing the cell number and test duration for ageing and safety test. This is linked to task 4.2 and will be used in subsequent work packages.

Virtual testing models (opens in new window)

Prototype models with parameterization tools. This is linked to task 3.2 and will be used in subsequent work packages.

Application ontologies (opens in new window)

Application ontologies and data models for battery testing. This deliverable is associated with task 2.1 and will be used in subsequent tasks in the WP.

Publications

DigiBatt Data management plan (opens in new window)

Author(s): SINTEF Industry, SINTEF Digital
Published in: 2024
DOI: 10.5281/ZENODO.13918133

Development of computational framework for non-invasive parameterization of physics-based models (opens in new window)

Author(s): Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR); SINTEF Industry; Forschungszentrum Jülich
Published in: 2025
DOI: 10.5281/ZENODO.15336745

Digital Twin Framework (opens in new window)

Author(s): SINTEF Industry
Published in: 2025
DOI: 10.5281/ZENODO.15336705

DigiBatt Project Handbook and Risk Management Table (opens in new window)

Author(s): SINTEF Industry, SINTEF Digital
Published in: 2024
Publisher: Zenodo
DOI: 10.5281/ZENODO.13918328

Application Ontologies (opens in new window)

Author(s): SINTEF Industry; Virtual Vehicle (Austria)
Published in: 2024
DOI: 10.5281/ZENODO.15336642

DigiBatt Initial plan for dissemination and exploitation including communication activities (opens in new window)

Author(s): SINTEF Industry,SINTEF Digital
Published in: 2024
DOI: 10.5281/ZENODO.13918301

Physics‐Based Inverse Modeling of Battery Degradation with Bayesian Methods (opens in new window)

Author(s): Micha C. J. Philipp, Yannick Kuhn, Arnulf Latz, Birger Horstmann
Published in: ChemSusChem, Issue 18, 2025, ISSN 1864-5631
Publisher: Wiley
DOI: 10.1002/CSSC.202402336

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