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Least-Squares Parameter Estimation for Catalyst Layer Agglomerate Models

[+] Author Affiliations
Peter Dobson, Marc Secanell

University of Alberta, Edmonton, AB, Canada

Paper No. FuelCell2010-33324, pp. 795-804; 10 pages
doi:10.1115/FuelCell2010-33324
From:
  • ASME 2010 8th International Conference on Fuel Cell Science, Engineering and Technology
  • ASME 2010 8th International Fuel Cell Science, Engineering and Technology Conference: Volume 1
  • Brooklyn, New York, USA, June 14–16, 2010
  • Conference Sponsors: Advanced Energy Systems Division
  • ISBN: 978-0-7918-4404-5 | eISBN: 978-0-7918-3875-4
  • Copyright © 2010 by ASME

abstract

A framework is presented to estimate the micro-structural parameters of cathode fuel cell electrodes by means of a nonlinear least-squares method. This work represents the first attempt in the literature to characterize the structure of the catalyst layer by numerical parameter estimation using a two-dimensional membrane electrode assembly model with an ionomer-filled agglomerate catalyst layer approximation. The framework is developed by coupling a two-dimensional model to an optimization based least-squares algorithm in DAKOTA. The algorithm, NL2SOL, minimizes the sum-of-squares of the residuals for any number of data points and parameters. Employing the proposed methodology allows for accurate characterization of the electrode structure and quantification the quality of the curve fit. Extension of this methodology allows for parameter estimation as novel materials are incorporated into fuel cell construction. Results indicate that curves can be fit using micro-structural and electrochemical parameters consistent with values published in the literature. However, the quality of the fit deteriorates for large data sets over the entire range of operating conditions.

Copyright © 2010 by ASME

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