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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 109
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Paper 3

Performance of Simplified Interval Models for Simulation and Control of Solid Oxide Fuel Cells

E. Auer1, L. Senkel2, S. Kiel3 and A. Rauh2

1Department of Electrical Engineering and Computer Science, University of Technology, Business and Design, Wismar, Germany
2Chair of Mechatronics, University of Rostock, Germany
3ACCSO GmbH, Cologne, Germany

Full Bibliographic Reference for this paper
E. Auer, L. Senkel, S. Kiel, A. Rauh, "Performance of Simplified Interval Models for Simulation and Control of Solid Oxide Fuel Cells", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 3, 2015. doi:10.4203/ccp.109.3
Keywords: interval arithmetic, solid oxide fuel cells, UniVerMeC, global optimisation.

Summary
In this paper, we introduce simplified models for the thermal subsystem of solid oxide fuel cells, which are considered to consist of two preheaters and one finite volume element to describe the temperature of the stack. The simplifying assumption, which allows us to obtain analytical solutions to the underlying system of differential equations, is to consider the heat capacities of the gases as zero-order polynomials in temperature. We compare the performance of such models and their ability to reflect the reality with the corresponding characteristics of models in which the heat capacities are approximated by quadratic polynomials. For this purpose, the framework UniVerMeC is used, which allows us to employ different kinds of arithmetics including the interval one. This latter possibility ensures a high level of reliability of the simulations and of the subsequent validation. Besides, it helps to take into account bounded uncertainty in measurements.

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