Intelligent, Safe and secure connected Electrical Mobility solutions: Towards European Green Deal and Seamless Mobility

Informazioni relative al progetto

EcoMobility

ID dell’accordo di sovvenzione: 101112306

DOI

10.3030/101112306

Data della firma CE 19 Maggio 2023

Data di avvio 1 Maggio 2023

Data di completamento 30 Aprile 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 36 287 225,00

Contributo UE

€ 10 760 581,18

Coordinato da

TTTECH AUTO GERMANY GMBH
Germany

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

Documents, reports (3)

Market study

Market study relevant to the project

EcoMobility initial stakeholders’ identification

Report on initial stakeholders’ identification

Report 1 on communication and dissemination

Report on communication and dissemination activities in year 1.

Pubblicazioni

Conference proceedings (6)

Task Scheduling in Multi-Cloud Environments: A Graph Partitioning Approach Enhanced by Nested Genetic Algorithms

Autori: Josepaul Paulachan, Daniel Onwuchekwa, Roman Obermaisser
Pubblicato in: 2024 11th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), 2024
Editore: IEEE
DOI: 10.1109/IOTSMS62296.2024.10710257

Deep Reinforcement Learning for path planning of Autonomous Underwater Vehicles

Autori: Artemis Stefanidou, Elena Politi, Christos Chronis, George Dimitrakopoulos & Iraklis Varlamis
Pubblicato in: 2024
Editore: 18th International Conference on Control, Automation, Robotics and Vision (ICARCV)

Technology Acceptance Modelling for Investigating the Uptake of Electric, Connected, Autonomous, and Shared Mobility Technologies

Autori: Konstantina Karathansopoulou, Despoina Mitsiogianni, Eleni Tsaousi, George Dimitrakopoulos, Dimitris Georgiadis
Pubblicato in: Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems, 2025
Editore: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0013235500003941

AI and connectivity for sustainable and efficient transportation – the EcoMobility approach

Autori: Luca Bongiovanni Ideas&Motion s.r.l.; Italy [e-mail] Marco Mamei Univ. of Modena and Reggio Emilia, Italy [e-mail] Bruno Dilecce 4S Sistemi Sicuri e Sostenibili S.r.l [e-mail] Paolo Burgio Univ.of M
Pubblicato in: 2024
Editore: 2024 Smart Systems Integration Conference and Exhibition (SSI)

Incremental Scheduling Using Genetic Algorithm

Autori: Omar Hekal, Daniel Onwuchekwa, Roman Obermaisser
Pubblicato in: 2024 International Symposium ELMAR, 2024
Editore: IEEE
DOI: 10.1109/ELMAR62909.2024.10694420

A Practical Survey on Static Task Scheduling Optimization Approaches for Heterogeneous Architectures

Autori: Jonas Hollmann, Matthias Lüders, Jakob Arndt, Ioannis Kyriakopoulos, Holger Blume
Pubblicato in: 2024
Editore: HeteroPAR 2024

Peer reviewed articles (4)

TinyML models for SoH estimation of lithium-ion batteries based on Electrochemical Impedance Spectroscopy

Autori: Spyridon Giazitzis, Abdisamad Ahmed Isse, Nicola Blasuttigh, Alessandro Massi Pavan, Davide M. Raimondo, Susheel Badha, Filippo Rosetti, Emanuele Ogliari
Pubblicato in: Journal of Power Sources, Numero 653, 2025, ISSN 0378-7753
Editore: Elsevier BV
DOI: 10.1016/J.JPOWSOUR.2025.237568

Analyzing cell-to-cell heterogeneities and cell configurations in parallel-connected battery modules using physics-based modeling

Autori: Simone Fasolato, Anirudh Allam, Simona Onori, Davide M. Raimondo
Pubblicato in: Journal of Energy Storage, Numero 129, 2025, ISSN 2352-152X
Editore: Elsevier BV
DOI: 10.1016/J.EST.2025.116942

A dataset for large prismatic lithium-ion battery cells (CALB L148N58A): Comprehensive characterization and real-world driving cycles

Autori: Simone Fasolato, Nicola Blasuttigh, Giacomo Galuppini, Davide M. Raimondo
Pubblicato in: Data in Brief, Numero 58, 2025, ISSN 2352-3409
Editore: Elsevier BV
DOI: 10.1016/J.DIB.2025.111301

Adaptive Deep Reinforcement Learning for Efficient 3D Navigation of Autonomous Underwater Vehicles

Autori: Elena Politi, Artemis Stefanidou, Christos Chronis, George Dimitrakopoulos, and Iraklis Varlamis
Pubblicato in: IEEE Access, Numero 12, 2024, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2024.3508031