Proton Exchange Membrane Fuel Cell Stack Design Optimization Using an Improved Jaya Algorithm

Abstract

Fuel cell stack configuration optimization is known to be a problem that, in addition to presenting engineering challenges, is computationally hard. This paper presents an improved computational heuristic for solving the problem. The problem addressed in this paper is one of constrained optimization, where the goal is to seek optimal (or near-optimal) values of (i) the number of proton exchange membrane fuel cells (PEMFCs) to be connected in series to form a group, (ii) the number of such groups to be connected in parallel, and (iii) the cell area, such that the PEMFC assembly delivers the rated voltage at the rated power while the cost of building the assembly is as low as possible. Simulation results show that the proposed method outperforms four of the best-known methods in the literature. The improvement in performance afforded by the proposed algorithm is validated with statistical tests of significance.

Keywords

• proton exchange membrane (PEM) fuel cell
• maximum power point
• optimization
• machine learning
• simulation
• heuristic