Fuel Fells (FCs) are becoming more and more attractive for real world applications, their performance meet the strong constraints imposed by regulations and international policies aiming at reducing the carbon footprint of power systems. Despite the noticeable improvements attained in the last decade, still the competitiveness with respect to conventional solutions is yet to be achieved for FCs efficiency, reliability, availability and durability. The implementation on FC Systems of suitable control, diagnostic and prognostic algorithms can improve those performance, making FC more efficient and competitive. The project covers the areas of Proton Exchange Membrane FC (PEMFC) backup and Solid Oxide FC (SOFC) µ-CHP systems that are among the most mature stationary FC solutions available on the market today.
The project aims at developing, integrating, engineering and testing a comprehensive and generalized Monitoring, Diagnostic, Prognostic and Control (MDPC) tool capable of improving efficiency, reliability and durability of SOFC and PEM systems for stationary applications. The MDPC tool features Electrochemical Impedance Spectroscopy-based stack monitoring for fault diagnosis and lifetime estimation, Balance of Plant diagnostics, supervisory RTO control and mitigation strategies. The tool relies on advanced dedicated HW and will be embedded in the Fuel Cell Systems (FCSs) for on-line validation in relevant operational environment.
Therefore, the RUBY tool will reach at the end of the project the TRL 7. It is foreseen that the tool will be ready for engineering scaling up of production, together with certification for embedding within commercial FCS.
To successfully fulfil the aims of RUBY, the following four main technical objectives were set:
1. Improve FCS performance and durability by implementing an advanced and integrated algorithm that combines monitoring, diagnosis, prognosis, control and mitigation actions for both SOFC and PEM systems.
2. Design and engineer the HW required for MDPC algorithms application, with attention to sensors reduction issues and the specific constraints imposed by stack technologies and systems applications towards industrial scalability.
3. Perform dedicated experimental campaigns for stacks and system characterization and MDPC tool prototype validation embedded on FCSs running in operational environment.
4. Develop an advanced FCS management strategy (supervisory level), with functionalities integrated with remote monitoring, for future smart-grid interaction and predictive maintenance application.