Multi-objective optimization of a polymer electrolyte fuel cell membrane electrode assembly

Abstract

A multi-objective multi-variable gradient-based fuel cell optimization framework is presented in order to optimize fuel cell membrane electrode assembly fabrication. The optimization target is to simultaneously maximize the cell current density at a given voltage and minimize its production costs. The design variables are electrode composition parameters such as platinum loading and porosity. To develop this framework, a two-dimensional through-the-channel single-phase membrane electrode assembly model is implemented and coupled to an optimization algorithm. In order to solve the optimization problem in a reasonable time, a gradient-based optimization method in conjunction with analytical sensitivities of the electrode model with respect to design parameters such as amount of electrolyte are used. Results show the trade-offs between performance and cost and illustrate that large gains in performance and reductions in production costs are possible. They also highlight the problems associated with formulating the optimization problem without taking into account production costs.