Multi-Objective Function Optimization for PEM Fuel Cell System

Abstract

There are numerous design and operating variables that affect the overall performance of a PEM fuel cell system. Many optimization techniques for the PEM fuel cell system have been reported in the literature. However, most of the reported work considered either efficiency or cost as the objective function. But it is known that fuel cell efficiency and cost affect one another. Thus, it has become imperative to consider both efficiency and cost in order to achieve optimal PEM fuel cell system design. In this, paper, a multi-objective problem to optimize the efficiency and cost of a PEM fuel cell system is formulated. The operating variables considered are: stack temperature, current density, system pressure, hydrogen and air flow rates. An optimum operating condition that will produce 5.76 kW at a cost of 521.9298 US$/kW and an efficiency of 52.2 % was obtained.

A Study of Anode-Supported Solid Oxide Fuel Cell Modeling and Optimization Using Neural Network and Multi-Armed Bandit Algorithm

“…[11] Many studies have been conducted to optimize the design variables of fuel cells. Of the optimization theories, genetic algorithm (GA) has been mostly used to find the optimal parameters of the fuel cells [18][19][20][21]. The GA has a mechanism to avoid local optimal, but there are many variables that need to be determined, so the result is very dependent on the variables.…”