H2020
Europeo
ExpectedOutcome:Projects are expected to contribute to all of the following outcomes:
The understanding of digital twins as systems with automated data acquisition, connected digital models and value-adding applications.The capacity to go beyond single process consideration with potential perspective on the process chain.The implementation and the transfer of digital twins into existing and future battery cell production plants.Safety and security, scalability, explainability, computational speed as well as contributions to sustainability of battery cell production.Optimise product quality, improving the resource efficiency and, consequently, the production time and cost of battery cells in the manufacturing process at the targeted scale.
Scope:The battery production chain consists of diverse multi-disciplinary, rather novel processes with numerous influencing factors and interdependencies. Digital twins, as a core element of the accelerating digitisation in manufacturing, bear the potential to improve planning and operation of current and future battery production system. With their connection of advanced digital models and most up-to-date data, decision suppor...
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ExpectedOutcome:Projects are expected to contribute to all of the following outcomes:
The understanding of digital twins as systems with automated data acquisition, connected digital models and value-adding applications.The capacity to go beyond single process consideration with potential perspective on the process chain.The implementation and the transfer of digital twins into existing and future battery cell production plants.Safety and security, scalability, explainability, computational speed as well as contributions to sustainability of battery cell production.Optimise product quality, improving the resource efficiency and, consequently, the production time and cost of battery cells in the manufacturing process at the targeted scale.
Scope:The battery production chain consists of diverse multi-disciplinary, rather novel processes with numerous influencing factors and interdependencies. Digital twins, as a core element of the accelerating digitisation in manufacturing, bear the potential to improve planning and operation of current and future battery production system. With their connection of advanced digital models and most up-to-date data, decision support or even autonomous control of battery production processes and process chains is enabled. First applications can be found in research and partly also in industrial practice – however, those still tend to be rather specific, covering just selected aspects of digital twins (e.g. just specific models) and are often hardly transferable between production stages and between different battery configurations in terms of the underlying IT architectures and models. Proposals are expected to address all following points:
Developing digital twins of battery cell manufacturing routes at pilot line level that incorporate appropriate models but also their connection to real manufacturing plants, e.g. to support process development and operation, battery cells optimisation, accelerate the set-up of effective manufacturing processes for the next generation battery cells or to demonstrate the capability for predictive maintenance.Design robust digital tools integrating multi-physics, data-driven models and hybrid modelling.Flexible Digital Twins capable to evolve to different battery chemistries, new disruptive materials as well as new manufacturing processes (the model would be chemistry neutral so easily adaptable to new disruptive materials and chemistries).Verify the transferability from pilot to production plant level.Propose applications that will enable to overcome single process considerations towards process chain perspectives.Implementation of the sensorisation of the manufacturing plant and automatisation of the data acquisition.Ensuring greater interoperability, by implementing available data standards[1], e. g., Modelling-Data (MODA) and Characterisation Data (CHADA), as well as, a common semantic framework, like The European Materials Modelling Ontology (EMMO) and the battery interface ontology (BattINFO).Promote the control and decision making of the manufacturing chain.Aspects like safety and security, explainability of models as well as contributions to sustainability of battery production will be addressed. This call topic addresses the need of increasing the level of autonomy to the whole battery cell value chain (with special emphasis in the manufacturing). Plans for the exploitation and dissemination of results for proposals submitted under this topic should include a strong business case and sound exploitation strategy, as outlined in the introduction to this Destination. The exploitation plans should include preliminary plans for scalability, commercialisation, and deployment (feasibility study, business plan).
This topic is building upon the BATTERY 2030+ Roadmap[2] and will build upon the shared data infrastructure, standards and protocols developed within this initiative, and in particular the BIG-MAP[3] project. Projects are expected to collaborate and contribute to the activities of the Coordination and Support Action defined under the topic HORIZON-CL5-2022-D2-01-08. The proposal will cover the contribution and collaboration to the Coordination and Support Action.”
This topic implements the co-programmed European Partnership on Batteries (Batt4EU). As such, projects resulting from this topic will be expected to report on the results to the European Partnership on Batteries (Batt4EU) in support of the monitoring of its KPIs.
Specific Topic Conditions:Activities are expected to achieve TRL 4-5 by the end of the project – see General Annex B.
[1]See https://emmc.eu
[2]https://battery2030.eu/research/roadmap/
[3]https://www.big-map.eu/
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La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
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Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar como minimo un 100%.
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