Summary
The EU roadmap towards a climate-neutral economy by 2050 sets ambitious decarbonisation targets that shall be achieved by a massive deployment of renewable energy sources. Energy storage improves grid flexibility and allows higher penetration levels of renewable energy sources to create a decarbonised and more electrified society by means of leveraging second-life batteries. Battery management plays an essential role by ensuring an efficient and safe battery operation. However, current battery management systems (BMS) typically rely on semi-empirical battery models (such as equivalent-circuit models) and on a limited amount of measured data.
Therefore, ENERGETIC project aims to develop the next generation BMS for optimizing batteries’ systems utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful and safer operations. ENERGETIC project contributes to the field of translational enhanced sensing technologies, exploiting multiple Artificial Intelligence models, supported by Edge and Cloud computing. ENERGETIC’s vision not only encompasses monitoring and prognosis the remaining useful life of a Li-ion battery with a digital twin, but also encompasses diagnosis by scrutinising the reasons for degradation through investigating the explainable AI models. This involves development of new technologies of sensing, combination and validation of multiphysics and data driven models, information fusion through Artificial Intelligence, Real time testing and smart Digital Twin development. Based on a solid and interdisciplinary consortium of partners, the ENERGETIC R&D project develops innovative physics and data-based approaches both at the software and hardware levels to ensure an optimised and safe utilisation of the battery system during all modes of operation.
Therefore, ENERGETIC project aims to develop the next generation BMS for optimizing batteries’ systems utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful and safer operations. ENERGETIC project contributes to the field of translational enhanced sensing technologies, exploiting multiple Artificial Intelligence models, supported by Edge and Cloud computing. ENERGETIC’s vision not only encompasses monitoring and prognosis the remaining useful life of a Li-ion battery with a digital twin, but also encompasses diagnosis by scrutinising the reasons for degradation through investigating the explainable AI models. This involves development of new technologies of sensing, combination and validation of multiphysics and data driven models, information fusion through Artificial Intelligence, Real time testing and smart Digital Twin development. Based on a solid and interdisciplinary consortium of partners, the ENERGETIC R&D project develops innovative physics and data-based approaches both at the software and hardware levels to ensure an optimised and safe utilisation of the battery system during all modes of operation.
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| Web resources: | https://cordis.europa.eu/project/id/101103667 |
| Start date: | 01-06-2023 |
| End date: | 31-08-2026 |
| Total budget - Public funding: | 4 170 167,50 Euro - 4 170 167,00 Euro |
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Original description
The EU roadmap towards a climate-neutral economy by 2050 sets ambitious decarbonisation targets that shall be achieved by a massive deployment of renewable energy sources. Energy storage improves grid flexibility and allows higher penetration levels of renewable energy sources to create a decarbonised and more electrified society by means of leveraging second-life batteries. Battery management plays an essential role by ensuring an efficient and safe battery operation. However, current battery management systems (BMS) typically rely on semi-empirical battery models (such as equivalent-circuit models) and on a limited amount of measured data.Therefore, ENERGETIC project aims to develop the next generation BMS for optimizing batteries’ systems utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful and safer operations. ENERGETIC project contributes to the field of translational enhanced sensing technologies, exploiting multiple Artificial Intelligence models, supported by Edge and Cloud computing. ENERGETIC’s vision not only encompasses monitoring and prognosis the remaining useful life of a Li-ion battery with a digital twin, but also encompasses diagnosis by scrutinising the reasons for degradation through investigating the explainable AI models. This involves development of new technologies of sensing, combination and validation of multiphysics and data driven models, information fusion through Artificial Intelligence, Real time testing and smart Digital Twin development. Based on a solid and interdisciplinary consortium of partners, the ENERGETIC R&D project develops innovative physics and data-based approaches both at the software and hardware levels to ensure an optimised and safe utilisation of the battery system during all modes of operation.
Status
SIGNEDCall topic
HORIZON-CL5-2022-D2-01-09Update Date
31-07-2023
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Organisations
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| INSTITUT NATIONAL DES SCIENCES APPLIQUEES, STRASBOURG (Coördinator)
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| ALTRAN PROTOTYPES AUTOMOBILES
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| COMMUNAUTE D' UNIVERSITES ET ETABLISSEMENTS UNIVERSITE BOURGOGNE - FRANCHE - COMTE
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| Coventry University
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| ELECTRICITE DE FRANCE (EDF)
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| FORSEE POWER
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| GBA ZABALA CONSEIL EN INNOVATION SA
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| HOCHSCHULE KARLSRUHE
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| POWERUP
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| TAJFUN HIL DRUSTVO SA OGRANICENOM ODGOVORNOSCU ZA ISTRAZIVANJE, PROIZVODNJU, TRGOVINU I USLUGE NOVI ...
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| TalTech - Tallinn University of Technology
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| UNIVERSITE DE TECHNOLOGIE DE BELFORT - MONTBELIARD
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| UNIVERSITE DU LUXEMBOURG
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| UNIVERSITY OF BATH (UBAH)