Home // International Journal On Advances in Systems and Measurements, volume 13, numbers 1 and 2, 2020 // View article

Parameter Identification and Model Reduction in the Design of Alkaline Methanol Fuel Cells

Authors:
Tanja Clees
Bernhard Klaassen
Igor Nikitin
Lialia Nikitina
Sabine Pott
Ulrike Krewer
Theresa Haisch
Fabian Kubannek

Keywords: modeling of complex systems; observational data and simulations; advanced applications; mathematical chemistry

Abstract:
Alkaline methanol oxidation is an important electrochemical process in the design of efficient fuel cells. Typically, a system of ordinary differential equations is used to model the kinetics of this process. The fitting of the parameters of the underlying mathematical model is performed on the basis of different types of experiments, characterizing the fuel cell. In this paper, we describe generic methods for creation of a mathematical model of electrochemical kinetics from a given reaction network, as well as for identification of parameters of this model. We also describe methods for model reduction, based on a combination of steady-state and dynamical descriptions of the process. The methods are tested on a range of experiments, including different concentrations of the reagents and different voltage range.

Pages: 94 to 106

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: June 30, 2020

Published in: journal

ISSN: 1942-261x