Fuel Cells

Parameter Estimation of a Proton-Exchange Membrane Fuel Cell using Voltage-Current Data

Authors: Glen Suares† and Karlene A. Hoo*
† Department of Chemical Engineering, University of South Carolina
* Department 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.

Corresponding Author: Karlene A. Hoo

 

Parameter & State Estimation of a Proton-Exchange-Membrane Fuel Cell using a Sequential Quadratic Programming Approach

Authors: Glen Suares† and Karlene A. Hoo*
† Department of Chemical Engineering, University of South Carolina
* Department 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.

Corresponding Author: Karlene A. Hoo