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Parameter Estimation of a Proton-Exchange Membrane Fuel
Cell using Voltage-Current Data
Authors:
Glen
Suares¹ and Karlene A. Hoo²
¹Department of Chemical
Engineering, University of South Carolina
²Department of Chemical
Engineering, Texas Tech University
ABSTRACT
All mathematical models contain parameters that must be determined for the model to represent accurately the behavior of the
system. The parameter estimation problem is usually solved as an unconstrained optimization
problem independent of the model equations. However, by integrating the parameter estimation problem with the generation of the model's state profiles,
constraints can be embedded directly into the optimizer, and an infeasible path solution approach can be used. Nonlinear programming is the ideal
framework for formulating constrained optimization problems. The model is introduced
into this framework as constraints using orthogonal collocation on finite elements. The
resulting nonlinear programming problem is then solved using sequential quadratic
programming. This approach is demonstrated on a mathematical model of a proton-exchange-membrane fuel cell in which four parameters are estimated
and nine state profiles are determined from model generated data.
Publication Information: Chemical Engineering Science, Vol. 55, pp
2237-2247, 2000.
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