Battery Cell Assembly Twin

Informations projet

BatCAT

N° de convention de subvention: 101137725

DOI

10.3030/101137725

Date de signature de la CE 8 Decembre 2023

Date de début 1 Janvier 2024

Date de fin 30 Juin 2027

Financé au titre de

Climate, Energy and Mobility

Coût total

€ 5 106 384,00

Contribution de l’UE

€ 5 106 384,00

5 106 384,00

Coordonné par

NORGES MILJO-OG BIOVITENSKAPLIGE UNIVERSITET
Norway

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Report on uncertainty quantification methodology

This deliverable reports on the results from T3.4. As such, a formal model for uncertainty and reliability is specified. It is shown how that formal model can be used to document the uncertainty of models, simulation results, and experimental data, and applied to uncertainty propagation (over BPMN) and evidence aggregation, feeding into provenance tracking across the data space.

Data landscape and infrastructure related requirements

D4.1 is the deliverable on T4.1 and T4.3. As such, it gives an overview over the data and metadata types handled within BatCAT, including simulation and sensory data. It reports on the knowledge infrastructure requirements in view of supporting BatCAT's use cases, integrating the CaosDB data model, and interoperating with BIG-MAP. This includes the requirements for low-to-high-level mapping.

Cellular neural networks and multicriteria optimization

This deliverable is the output from T5.1 and T5.2. As such, it reports on the developed self-supervised machine-learning predictor that is capable of adjusting its structure and parameters autonomously. The predictor is implemented as a CeNN, with templates from an echo state network, that can be trained for all the data-driven modelling tasks from BatCAT with a high expected estimation per-formance. Moreover, from T5.2, ITWM’s pre-existing MCO methodology and tools are integrated into the BatCAT architecture and deployed as an IIDSS module, including an in-depth documentation and training for developers and users.

Report on multiphysics modelling of battery production

D2.2 reports on T2.2, Multiphysics modelling of Li-ion battery production, and T2.4, Multiphysics modelling of RFB production, summarizing and presenting the output from these two tasks of the project.

Communication and dissemination plan, including an overview of planned training activities

HSKL will deliver the initial version of the communication, dissemination, and training plan by M6. In M15, a revised version is compiled as part of the MS10 milestone.

Experimental campaign plan and taxonomy

The experimental campaign plan details what experiments there are to be done within BatCAT, who will do them, and what materials and objects need to be transferred between partners for this purpose. The experimental campaign plan is developed and updated continuously until M18 - this deliverable is therefore the final version of it. It also includes a taxonomy.

Simulation campaign plan

As the name suggests - a plan detailing what simulations there are to be done in WP2.

Publications

Characteristic Curves of Polar Fluids: (II) The Two-Center Lennard–Jones Plus Quadrupole Fluid

Auteurs: Hans Renneis, Simon Stephan
Publié dans: International Journal of Thermophysics, Numéro 45, 2024, ISSN 0195-928X
Éditeur: Springer Science and Business Media LLC
DOI: 10.1007/S10765-024-03367-7

Molecular Dynamics Study of Adsorption and Wetting of Mixtures of Simple Fluids on Planar Walls

Auteurs: David Fertig, Hans Hasse, Simon Stephan
Publié dans: The Journal of Physical Chemistry C, Numéro 128, 2024, ISSN 1932-7447
Éditeur: American Chemical Society (ACS)
DOI: 10.1021/ACS.JPCC.4C01765

Measurements and Equation of State Modeling of the Density of Five 1-Alcohols (C6–C10) at Pressures of up to 120 MPa

Auteurs: Sebastian Schmitt, Hans Hasse, Simon Stephan
Publié dans: Journal of Chemical & Engineering Data, Numéro 69, 2024, ISSN 0021-9568
Éditeur: American Chemical Society (ACS)
DOI: 10.1021/ACS.JCED.4C00265

Comparative Analysis via CFD Simulation on the Impact of Graphite Anode Morphologies on the Discharge of a Lithium-Ion Battery

Auteurs: Alessio Lombardo Pontillo, Agnese Marcato, Daniele Versaci, Daniele Marchisio, Gianluca Boccardo
Publié dans: Batteries, Numéro 11, 2025, ISSN 2313-0105
Éditeur: MDPI AG
DOI: 10.3390/BATTERIES11070252

Characteristic curves of the stockmayer fluid: Molecular simulation and equation of state modeling

Auteurs: Jens Staubach, Simon Stephan
Publié dans: Fluid Phase Equilibria, Numéro 592, 2025, ISSN 0378-3812
Éditeur: Elsevier BV
DOI: 10.1016/J.FLUID.2024.114314

Characteristic Curves of Polar Fluids: (I) The Two-Center Lennard–Jones Plus Dipole Fluid

International Journal of Hydrogen Energy

Auteurs: Eric Langner; Hamidreza Dehghani; Mohamed El Hachemi; Elias Belouettar–Mathis; Ahmed Makradi; Thomas Wallmersperger; Sylvain Gouttebroze; Heinz Preisig; Casper Welzel Andersen; Qian Shao; Heng Hu; Salim Belouettar
Publié dans: International Journal of Hydrogen Energy, 2024, ISSN 0360-3199
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/J.IJHYDENE.2024.10.424

Helmholtz energy models for dipole interactions: Review and comprehensive assessment

Auteurs: Jens Staubach, Hans Hasse, Simon Stephan
Publié dans: Fluid Phase Equilibria, Numéro 585, 2024, ISSN 0378-3812
Éditeur: Elsevier BV
DOI: 10.1016/J.FLUID.2024.114168

Mass transfer at vapor-liquid interfaces of H<sub>2</sub>O + CO<sub>2</sub> mixtures studied by molecular dynamics simulation

Auteurs: Simon Stephan, Vilde Bråten, Hans Hasse
Publié dans: Journal of Non-Equilibrium Thermodynamics, Numéro 49, 2024, ISSN 0340-0204
Éditeur: Walter de Gruyter GmbH
DOI: 10.1515/JNET-2024-0010

Journal of Chemical Physics

Auteurs: Tristan Weik; Dennis Alt; Simon Stephan
Publié dans: Journal of Chemical Physics, 2025, ISSN 0021-9606
Éditeur: American Institute of Physics
DOI: 10.1063/5.0280979

Phase-field modeling and computational design of structurally stable NMC materials

Auteurs: Eduardo Roque, Javier Segurado, Francisco Montero-Chacón
Publié dans: Materials & Design, Numéro 248, 2024, ISSN 0264-1275
Éditeur: Elsevier BV
DOI: 10.1016/J.MATDES.2024.113464

Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories

Auteurs: Iman Peivaste, Salim Belouettar, Francesco Mercuri, Nicholas Fantuzzi, Hamidreza Dehghani, Razie Izadi, Halliru Ibrahim, Jakub Lengiewicz, Maël Belouettar-Mathis, Kouider Bendine, Ahmed Makradi, Martin Horsch, Peter Klein, Mohamed El Hachemi, Heinz A. Preisig, Yacine Rezgui, Natalia Konchakova, Ali Daouadji
Publié dans: Composite Structures, Numéro 372, 2025, ISSN 0263-8223
Éditeur: Elsevier BV
DOI: 10.1016/J.COMPSTRUCT.2025.119419

Entropy scaling for diffusion coefficients in fluid mixtures

Auteurs: Sebastian Schmitt, Hans Hasse, Simon Stephan
Publié dans: Nature Communications, Numéro 16, 2025, ISSN 2041-1723
Éditeur: Springer Science and Business Media LLC
DOI: 10.1038/S41467-025-57780-Z

Materials knowledge and data representation with a European ontology ecosystem

Auteurs: Goldbeck, Gerhard
Publié dans: PSDI Materials Community Workshop 2025, 2025
Éditeur: Zenodo
DOI: 10.5281/ZENODO.17076306

On the trail to exascale & knowledge transfer: From the atomistic to the mesoscopic world in preparation for redox flow batteries modelling

Auteurs: Ilian Todorov; Michael Seaton; Benjamin Speake; Silvia Chiacchiera; Vlad Sokhan; Martin Thomas Horsch; Chin Weng Yong
Publié dans: BG-SIAM 2024, 2024
DOI: 10.5281/ZENODO.17099506

Battery manufacturing knowledge infrastructure requirements for multicriteria optimization based decision support in design of simulation

Auteurs: Martin Thomas Horsch¹˒²*, Dmytro Romanov¹, Eirik Valseth¹˒³, Salim Belouettar⁴, Luis Eduardo Córdova López¹, Johanna Glutting⁵, Mathijs A. Janssen¹, Peter Klein⁶, Andreas Linhart⁷, Michael A. Seaton², Elin D. Sødahl¹, Noel Vizcaino², Stephan Werth⁵, Simon
Publié dans: 2024
Éditeur: CEUR-WS
DOI: 10.5281/ZENODO.13132899

Combining Autoencoder and Cellular Neural Networks for Enhanced Direct Multi-Step Forecasting of Short and Long-Term Multivariate Time Series in Battery Health Monitoring: A Preliminary Feasibility Analysis

Auteurs: Mohamed El Bahnasawi, Martin Gebser, Witesyavwirwa Vianney Kambale, Mohamed Salem, Jean Chamberlain Chedjou, Kyandoghere Kyamakya
Publié dans: 2024 International Conference on Applied Mathematics &amp; Computer Science (ICAMCS), 2024
Éditeur: IEEE
DOI: 10.1109/ICAMCS62774.2024.00031

Mesoscopic Water Model Polarisation: Knowledge in extending apolar CG water models to meet the needs for simulations of highly-ionic electrolyte solutions in Redox Flow Batteries

Auteurs: Seaton, Michael; Todorov, Ilian; Speake, Benjamin
Publié dans: EMMC International Workshop 2025, 2025
Éditeur: zenodo
DOI: 10.5281/ZENODO.17098106

Knowledge representation of battery manufacturing supported by an integrated ontology system

Auteurs: Gerhard Goldbeck, Martin T Horsch, Silvia Chiacchiera. Martin Petit
Publié dans: EMMC International Workshop 2025, 2025
Éditeur: Zenodo
DOI: 10.5281/ZENODO.15198392

Symbolic-AI-Fusion Deep Learning (SAIF-DL): Encoding Knowledge into Training with Answer Set Programming Loss Penalties by a Novel Loss Function Approach

Auteurs: Fadi Al Machot, Martin Thomas Horsch, Habib Ullah
Publié dans: Lecture Notes in Networks and Systems, Designing the Conceptual Landscape for a XAIR Validation Infrastructure, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-89274-5_4

A Brief Conceptual Comparative Analysis of ASP Reasoners and Multi-Agent Reasoners for Predictive Maintenance and Failure Prediction in Battery Systems

Auteurs: M El Bahnasawi, M Gebser, K Kyamakya
Publié dans: Book of Abstracts Workshop on AI for Sustainable Energy Systems and Green AI, 2025
Éditeur: TUGraz OPEN Library
DOI: 10.3217/978-3-99161-045-8

Building Trustworthy AI: Transparent AI Systems via Language Models, Ontologies, and Logical Reasoning (TranspNet)

Scope of Physics-Based Simulation Artefacts

Auteurs: Martin Thomas Horsch, Fadi Al Machot, Jadran Vrabec
Publié dans: Lecture Notes in Networks and Systems, Designing the Conceptual Landscape for a XAIR Validation Infrastructure, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.48550/ARXIV.2412.06077

Conceptualizing Validation Systems for Explainable AI: A Design Approach

Auteurs: Paraskevi Fasouli, Mohamed El Bahnasawi, Martin Gebser, Kyandoghere Kyamakya
Publié dans: Lecture Notes in Networks and Systems, Designing the Conceptual Landscape for a XAIR Validation Infrastructure, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-89274-5_2

Balancing Performance and Transparency: Explainable AI for Battery Health Monitoring

Auteurs: Mohamed El Bahnasawi, Mohamed Abdellatif, Mohamed Salem, Paraskevi Fasouli, Martin Gebser, Kyandoghere Kyamakya
Publié dans: Lecture Notes in Networks and Systems, Designing the Conceptual Landscape for a XAIR Validation Infrastructure, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-89274-5_8

Designing the Conceptual Landscape for a XAIR Validation Infrastructure

Publié dans: Lecture Notes in Networks and Systems, 2025, ISBN 978-3-031-89273-8
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-89274-5_2

MBCO: The Materials-Based Business Case Ontology from BPMN-EMMO Integration

Auteurs: Christophe Feltus, Peter Klein, Natalia Konchakova, Damien Nicolas, Carlos Kavka, Martin T. Horsch, Heinz A. Preisig, Djamel Khadraoui, Salim Belouettar
Publié dans: Lecture Notes in Business Information Processing, Information Technology for Management: Solving Social and Business Problems Through IT, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-61657-0_2

Designing the Conceptual Landscape for a XAIR Validation Infrastructure

Auteurs: Fadi Al Machot, Martin Thomas Horsch, Sebastian Scholze
Publié dans: Lecture Notes in Networks and Systems, Numéro 1375, 2025, ISSN 2367-3370
Éditeur: Springer

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