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Parameter & State Estimation of a Proton-Exchange-Membrane Fuel Cell using a Sequential Quadratic Programming Approach
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..
Publication Information: Industrial & Engineering Chemistry Research,
Vol. 36, pp 4264-4272, 1997.
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