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CORDIS - Risultati della ricerca dell’UE
CORDIS

NEXT GENERATION BATTERY MANAGEMENT SYSTEM BASED ON DATA RICH DIGITAL TWIN

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

AI model for heat monitoring (si apre in una nuova finestra)

A description of the proposed model architecture will be provided. Qualitative and quantitative comparison with SoA will also be reported.

New methods of resilient of data transmission (si apre in una nuova finestra)

A new approach to develop blockchain services in the form of Network Function Virtualizations that can improve both maintainability and deployability of IoT networks. In addition, it enables sophisticated analysis of IoT transactions, improves security, and increases privacy, thanks to the global network awareness.

Mining model from explanation of AI models (si apre in una nuova finestra)

The algorithm used to mine explanation from the model. A expert evaluation of the explanation is given as well.

Ontology of the battery domain integrating the BMS definition and the concept of failures and maintenance (si apre in una nuova finestra)

A descrption of the built ontlogy and the different retained battery failure. The different used semantic rule of the ontology are described.

AI model for SoX prediction (si apre in una nuova finestra)

A description of the architecture of the used model for predicting the SoX. A comparative results with the State of the Art wil be given.

Plan and Strategy for Dissemination and Communication (si apre in una nuova finestra)

This deliverable will establish the basis for the development of common dissemination & exploitation plan in the project. This deliverable is linked with the task T7.1. Updates at M18 and M39.

Technical report on battery sizing methodologies for optimising first and second lives (si apre in una nuova finestra)

"The ""battery first life"" configuration for current electric vehicle applications is our first point of interest. Second, the report outlines the methodology used to size ""battery second life."" Depending on the application type and energy management strategy, the to-be-developed sizing tools are meant to direct the designer in his decisions."

Benchmark service providers (si apre in una nuova finestra)

Various research will be done to compare data’s security and storage, sustainability, infrastructures, environment and architecture of the different cloud providers in order to identify the solution best suited to our requirements and needs.

Benchmark of multiphysics models of battery systems including cooling (si apre in una nuova finestra)

Report detailing existing multiphysics models of battery systems including cooling. Including aspect of cell modelling and how this is extended to sytem modelling including cooling system.

Training programme (si apre in una nuova finestra)

Report on monthly seminars that will be organized. A summer school will be organized in Tallinn (June 2025)

Use cases for automotive and stationary (si apre in una nuova finestra)

This deliverable will define and present the both use cases : auto & stationnary, which will be used for first life and second life applications of batteries.

Selected DT software for heat monitoring and battery ageing (si apre in una nuova finestra)

A report reviewing existing DT software will be delivered. It will also explain the choice of the selected DT software.

Demonstration of a Hardware Abstraction Layer featuring expanded set of inputs (si apre in una nuova finestra)

Hardware Abstraction framework on an embedded device capable of sensoring battery sensor signals and delivering an abstraction for upper layers resp. network transfer.

Simulated thermal images to train AI (si apre in una nuova finestra)

A simulator for generating synthetic thermal images will be developed. This will enable producing a dataset formed by simulated thermal images that will be in turn used for training AI models.

Pubblicazioni

OntoSoC: An ontology-based approach to battery pack SoC estimation (si apre in una nuova finestra)

Autori: Ala Eddine Hamouni, Franco Giustozzi, Ahmed Samet, Ali Ayadi, Slimane Arbaoui, Tedjani Mesbahi
Pubblicato in: Procedia Computer Science, Numero 225, 2024, ISSN 1877-0509
Editore: Elsevier BV
DOI: 10.1016/j.procs.2023.10.216

Toward Anomaly Representation in Lithium-Ion Batteries: An Ontology-Based Approach (si apre in una nuova finestra)

Autori: Marwa Zitouni, Franco Giustozzi, Ahmed Samet, Tedjani Mesbahi
Pubblicato in: Procedia Computer Science, Numero 246, 2025, ISSN 1877-0509
Editore: Elsevier BV
DOI: 10.1016/j.procs.2024.09.563

AI-enabled thermal monitoring of commercial (PHEV) Li-ion pouch cells with Feature-Adapted Unsupervised Anomaly Detection (si apre in una nuova finestra)

Autori: Abdelrahman Shabayek, Arunkumar Rathinam, Matthieu Ruthven, Djamila Aouada, Tazdin Amietszajew
Pubblicato in: Journal of Power Sources, Numero 629, 2025, ISSN 0378-7753
Editore: Elsevier BV
DOI: 10.1016/j.jpowsour.2024.235982

Data-driven strategy for state of health prediction and anomaly detection in lithium-ion batteries (si apre in una nuova finestra)

Autori: Slimane Arbaoui, Ahmed Samet, Ali Ayadi, Tedjani Mesbahi, Romuald Boné
Pubblicato in: Energy and AI, Numero 17, 2024, ISSN 2666-5468
Editore: Elsevier BV
DOI: 10.1016/j.egyai.2024.100413

Lecture Notes in Computer Science (si apre in una nuova finestra)

Autori: Amel Hidouri, Slimane Arbaoui, Ahmed Samet, Ali Ayadi, Tedjani Mesbahi, Romuald Boné, François de Bertrand de Beuvron
Pubblicato in: Lecture Notes in Computer Science, Computational Science – ICCS 2024, 2024, ISSN 0302-9743
Editore: Springer Verlag
DOI: 10.1007/978-3-031-63783-4_14

Dual-model approach for one-shot lithium-ion battery state of health sequence prediction (si apre in una nuova finestra)

Autori: Slimane Arbaoui, Ahmed Samet, Ali Ayadi, Tedjani Mesbahi, Romuald Boné
Pubblicato in: Array, Numero 24, 2024, ISSN 2590-0056
Editore: Elsevier BV
DOI: 10.1016/j.array.2024.100367

Parameter Estimation for a Generic Na-ion Battery Model Using The Curve Fitting Approach (si apre in una nuova finestra)

Autori: Lakhdar Mamouri, Thomas Pavot, Tedjani Mesbahi
Pubblicato in: 2024 IEEE Vehicle Power and Propulsion Conference (VPPC), 2025
Editore: IEEE
DOI: 10.1109/VPPC63154.2024.10755187

Hysteresis in Sodium-ion Batteries: Temperature and Relaxation Time Effects (si apre in una nuova finestra)

Autori: Sary Yehia, Lakhdar Mamouri, Nagham El Ghossein, Tedjani Mesbahi
Pubblicato in: 2024 IEEE Vehicle Power and Propulsion Conference (VPPC), 2025
Editore: IEEE
DOI: 10.1109/VPPC63154.2024.10755409

Design of an Alternative Hardware Abstraction Layer for Embedded Systems with Time-Controlled Hardware Access (si apre in una nuova finestra)

Autori: Gabriel Simmann, Vinay Veeranna, Reiner Kriesten
Pubblicato in: SAE Technical Paper Series, Numero 1, 2024
Editore: SAE International
DOI: 10.4271/2024-01-2989

Accurate Recommendation of EV Charging Stations Driven by Availability Status Prediction (si apre in una nuova finestra)

Autori: Meriem Manai, Bassem Sellami, Sadok Ben Yahia
Pubblicato in: Proceedings of the 19th International Conference on Software Technologies, 2024
Editore: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0012752600003753

Digital Battery Passport as an Enabler of Environmental Impact Assessment in Electric Vehicle Applications (si apre in una nuova finestra)

Autori: Cyrine Soufi, Tedjani Mesbahi, Ahmed Samet
Pubblicato in: 2023 IEEE Vehicle Power and Propulsion Conference (VPPC), 2024
Editore: IEEE
DOI: 10.1109/VPPC60535.2023.10403389

Lecture Notes in Computer Science (si apre in una nuova finestra)

Autori: Amel Hidouri, Slimane Arbaoui, Ahmed Samet, Ali Ayadi, Tedjani Mesbahi, Romuald Boné, François de Bertrand de Beuvron
Pubblicato in: Lecture Notes in Computer Science, Computational Science – ICCS 2024, 2024, ISSN 0302-9743
Editore: Springer Verlag
DOI: 10.1007/978-3-031-63783-4_14

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