The efficient and economic design of PEM fuel cell systems by multi-objective optimization

A multi-objective optimisation model for a general polymer electrolyte membrane fuel cell system

“…Also, the compressor and motor efficiencies vary with the size of the compressor and the fraction of full load at which it is operated at. However, it is assumed that the compressor and motor efficiencies are constant, similar to the approach adopted by others [6,34]. Table 1 presents the expressions for the physical parameters used in the model, whilst Table 2 gives the values of the constant parameters.…”

“…Unlike a combustion engine, a fuel cell does not need to achieve a large temperature differential to achieve the same efficiency because its efficiency is determined by the Gibbs free energy [4]. The fuel cell system efficiency requirement for both stationary and transportation applications is at least 40% [5,6].…”

“…Moreover, some of the papers have performed single-objective optimisation for a specific part of the PEM fuel cell system such as the membrane electrode assembly (MEA) [19], the electrode [20], the bipolar plate and diffusion layer [21], the cathode and air distributor [22], and the catalyst layer [23,24]. However, the results of these studies might be misleading because the interaction or coupling between the multiple objectives has not been considered [6]. In addition, the potentially conflicting nature of the objectives makes the determination of the optimal solution more challenging.…”

“…This resulted in a one-variable, single-objective optimisation problem, which was then solved at different values of the parameter. Na and Gou [6] optimised the efficiency and cost of a 50 kW PEM fuel cell system for transportation, using the system pressure, the hydrogen and air stoichiometric ratios, and the current density as the design variables. The Pareto set that they obtained using MATLAB's fminimax function, however, was influenced by the choice of the initial values of the design variables used in the solver, indicating the non-globality of the solution.…”

“…The objective is to determine a set of trade-off optimal solutions, called the non-dominated or Pareto set, that maximises the efficiency and minimises the size of the system with respect to the current density, the cell voltage, the system pressure, the hydrogen and air stoichiometric ratios, and the relative humidities of fuel and air. To date, papers on multi-objective optimisation of PEM fuel cells have considered models that are specific to the application described in the paper [3,6,25,27]. Our model is more general and, thus, will be suitable for a wide range of applications.…”