Comparison of Stochastic and Interval-Based Modeling Approaches for the Online Optimization of the Fuel Efficiency of SOFC Systems (Vortrag)

Aus Kompetenzportal
Wechseln zu: Navigation, Suche
Comparison of Stochastic and Interval-Based Modeling Approaches for the Online Optimization of the Fuel Efficiency of SOFC Systems (Vortrag)
Autor Andreas Rauh, Ekaterina Auer
Tagung/Veranstaltung 9th International Conference on Systems and Control (ICSC)
Ort Caen, France
vom 24. November 2021 bis 26. November 2021
Review
Titel Proceedings 2021 9th International Conference on Systems and Control (ICSC), 2021, pp. 536-541,

doi: 10.1109/ICSC50472.2021.9666656

Autor Proceedings
Verlag IEEE
Erscheinungsjahr 2021

The dynamic operation of high-temperature fuel cells under temporally varying electric loads requires models for the electric stack power that depend on the supplied fuel mass flow, the electric current, the temperature of the supplied reaction media, and the stack temperature. This information is required to optimize the fuel consumption when tracking time-varying power profiles under the constraint of preventing fuel starvation. For that reason, the stack current needs to stay below the one that defines the maximum power point. However, due to the numerous influence factors, this point is only imperfectly known so that an online estimation with a corresponding quantification of the accuracy is necessary. In this paper, stochastic and interval-based modeling procedures are compared for an online control optimization on the basis of an experimentally validated dynamic SOFC model. The interval-based modeling combines nonlinear autoregressive models with a set-valued uncertainty quantification in a novel way.