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Propagation of uncertainties on a digital twin of a multi-energy system based on multi-physical models

Technological challenge: Energy efficiency for smart buildings, electrical mobility and industrial processes (learn more)

Department: Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratory: Laboratoire Modélisation multi-échelle et suivi Performance

Start Date: 01-10-2022

Location: Grenoble

CEA Code: SL-DRT-22-0683

Contact: pascal.schott@cea.fr

In the context of the acceleration of hydrogen deployment and its use in complex systems, This thesis topic will allow to advance the international community on the impact of uncertainties on the steering and control laws of digital twins of hybrid systems built with multi-physical fuel cell and battery models. In particular, the robustness of the control laws (and the range of validity of the models) will be evaluated in relation to the variations of the parameters related to the uncertainties and the aging of the components. Taking into account the propagation of uncertainties on model parameters on the degradation speeds of batteries and batteries will be a key axis. A second axis will be the study in simulation using the digital twins of the failure modes of the battery and battery systems. The work will rely on two digital twins being developed in-house CEA: i/a hybrid fuel cell and battery vehicle in a very dynamic and high power application field; ii/a high temperature electrolysis H2 production system coupled to the power grid for stationary applications The URANIE opensource platform will be used for uncertainty propagation studies. Several uncertainty propagation methods (Monte Carlo methods) will be tested.

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