Two-Layered Real-Time Optimization of a Solid Oxide Fuel Cell Stack

The optimal operation of a solid oxide fuel cell stack is addressed in this paper. Real-time optimization, performed at a slow time scale via constraint adaptation, is used to account for uncertainty and degradation effects, while model-predictive control is performed at a faster time scale to reject process disturbances and to safely adapt the system to the specified output constraints following changes in cell power demand. To ensure that these constraints are strictly honored, a novel adaptation algorithm that uses the built-in constraint handling of quadratic programming is implemented within the model-predictive controller. An additional feature of this algorithm - its ability to adapt the feasibility region in view of uncertainty - is shown as well. Simulation results illustrate the efficacy of this approach in the solid oxide fuel cell system.

Kothare, Mayuresh
Tade, Moses
Van de Wouwer, Alain
Smets, Ilse
Published in:
Proceedings of the 9th Int. Symposium on Dynamics and Control of Process Systems, 839-844
Presented at:
9th International Symposium on Dynamics and Control of Process Systems, Leuven, Belgium, July, 5-7, 2010

 Record created 2009-12-16, last modified 2018-01-28

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