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Sapphire

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System Automation of PEMFCs with Prognostics and Health management for Improved...

System Automation of PEMFCs with Prognostics and Health management for Improved Reliability and Economy The SAPPHIRE project will develop an integrated prognostics and health management system (PHM) including a health-adaptive controller to extend the lifetime and increase the reliability of heat and power-producing systems based on... ver más

30/04/2016

SINTEF

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 6 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2016-04-30 No tenemos la información de la convocatoria

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6 Participantes

SINTEF

0.00€ | Lider

ENSMM

N.D. | Participante

UNIVERSITY OF SPLIT FACULTY...

N.D. | Participante

EIFER

N.D. | Participante

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Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The SAPPHIRE project will develop an integrated prognostics and health management system (PHM) including a health-adaptive controller to extend the lifetime and increase the reliability of heat and power-producing systems based on low-temperature proton-exchange membrane fuel cells (LT-PEMFC). The PHM system can actively track the current health and degradation state of the fuel-cell system, and through the health-adaptive control counteract the degradation of cells and balance of plant, and thereby boost the lifetime of the controlled system beyond the current lifetime expectancy. An important part of project is to develop novel prognostics approaches implemented in the PHM for estimation of the remaining useful life (RUL) of the PEMFC. An efficient sensor configuration for control will be chosen using controllability analysis methods, also including indirect sensing/estimation techniques to replace expensive measurement principles. Based on sensor inputs and input from the control system, the PHM algorithms identify the probable failure modes trajectories and estimate the remaining useful life. The consortium’s competence ranges from first principles estimation, to signal processing, regression and data-driven techniques, such as neural networks. This ensures an efficient choice of methods. The project covers a full cycle of research activities, from requirement specification and laboratory experiments, through study of degradation phenomena and selection of prognostic methods, to synthesis of the control system and its testing on the target PEMFC system. A technical-economical analysis will be performed in order to assess the impact of the developed tool in terms of lifetime improvement. The project is expected to produce hardware and software solutions and have a significant scientific output. The implemented solutions resulting from the project will be tested and validated by the research and industrial partners.

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