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

  • 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.

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Document Type:Article
Author:Tanja Clees, Bernhard Klaassen, Igor Nikitin, Lialia Nikitina, Sabine Pott, Ulrike Krewer, Theresa Haisch, Fabian Kubannek
Parent Title (English):International Journal on Advances in Systems and Measurements
Number of pages:13
First Page:94
Last Page:106
Date of first publication:2020/06/30
Copyright:2020, © Copyright by authors, Published under agreement with IARIA. Abstracting is permitted with credit to the source.
Funding:The work has been partially supported by the German Federal Ministry for Economic Affairs and Energy, grant BMWI-0324019A, project MathEnergy and by the German Bundesland North Rhine-Westphalia, the European Regional Development Fund, grant Nr. EFRE-0800063, project ES-FLEX-INFRA.
Keyword:advanced applications; mathematical chemistry; modeling of complex systems; observational data and simulations
Departments, institutes and facilities:Fachbereich Ingenieurwissenschaften und Kommunikation
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Dewey Decimal Classification (DDC):6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Entry in this database:2023/01/03