• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Parameter identification in cyclic voltammetry of alkaline methanol oxidation
 
  • Details
  • Full
Options
2018
Conference Paper
Title

Parameter identification in cyclic voltammetry of alkaline methanol oxidation

Abstract
Alkaline methanol oxidation is an electrochemical process, perspective for the design of efficient high energy density fuel cells. The process involves a large number of elementary reactions, forming a complex reaction graph, and it is described by a system of non-linear differential equations of high order. The purpose of parameter identification is a reconstruction of reaction constants in this model on the basis of available experimental data. Cyclic voltammetry, a measurement of dynamical current-voltage characteristic of the cell, is especially suitable for analysis of electrochemical kinetics. In this paper we present several approaches for parameter identification in cyclic voltammetry of alkaline methanol oxidation. With the aid of global optimization methods and interactive parameter study we find four islands of solutions in parameter space, corresponding to different chemical mechanisms of the process. The main features of solutions are discussed and the reconstructed reaction constants are presented.
Author(s)
Clees, Tanja  orcid-logo
Nikitin, I.
Nikitina, L.
Pott, S.
Krewer, U.
Haisch, T.
Mainwork
8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2018. Proceedings  
Conference
International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH) 2018  
Open Access
DOI
10.5220/0006832002790288
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Keyword(s)
  • complex systems modeling and simulation

  • non-linear optimization

  • parameter identification

  • application in electrochemistry

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024