PARAMETER AND STATE ESTIMATION OF A PROTON-EXCHANGE MEMBRANE FUEL-CELL USING SEQUENTIAL QUADRATIC-PROGRAMMING

All mathematical models contain parameters that must be determined for the model to represent accurately the behavior of the system. The par ameter estimation problem is usually solved as an unconstrained optimi zation problem independent of the model equations. However, by integra ting the parameter estimation problem with the generation of the model 's state profiles, constraints can be embedded directly into the optim izer, and an infeasible path solution approach can be used. Nonlinear programming is the ideal framework for formulating constrained optimiz ation problems. The model is introduced into this framework as constra ints using orthogonal collocation on finite elements. The resulting no nlinear programming problem is then solved using sequential quadratic programming. We demonstrate this approach on a mathematical model of a proton-exchange-membrane fuel cell in which four parameters are estim ated and nine states' profiles are determined.