Analysis and optimization of current collecting systems in PEM fuel cells

Peiwen Li,Hong Liu,Jeong-Pill Ki

doi:10.1186/2251-6832-3-2

Peiwen Li, Hong Liu + Show 1 more

Open Access

https://doi.org/10.1186/2251-6832-3-2

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Abstract

This paper presents analytical and experimental studies on optimization of the gas delivery and current collection system in a proton exchange membrane (PEM) fuel cell for the objective of reducing ohmic loss, thereby achieving higher power density. Specifically, the dimensions of current collection ribs as well as the rib distribution were optimized to get a maximized power density in a fuel cell. In the modeling process, the power output from a fixed area of membrane is calculated through analysis of an electrical circuit simulating the current from electrochemical reaction flowing to the current collectors. Current collectors of two-dimensional ribs and three-dimensional pillars were considered. Analyses found that three-dimensional pillars allow higher power density in a PEM fuel cell. Considering the mass transfer enhancement effect, three-dimensional pillars as current collectors in gas flow field may be a good choice if the fuel cell operates at low current density and there is no liquid water blocking the flow channels. The analyses did not consider the existence of liquid water, meaning the current density is not very high. The study concluded that decreasing the size of both the current collector and its control area yields a significant benefit to a higher power density. A preliminary experimental test in a PEM fuel cell has verified the conclusion of the analytical work.

Highlights

Photovoltaic (PV) power has proven to be one of the promising renewable energies in the recent years
A nonlinear autoregressive with exogenous inputs model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This type of models relates the current value of output to both past values of the same output and current and past values of externally inputs that influence the output of interest
In this study we used a combinations of three in-situ measured parameters: the global horizontal solar irradiation (Irr) and the temperature of PV modules (Tc) as exogenous inputs U, and the PV power (P) as variable of interest Y

Summary

Introduction

Photovoltaic (PV) power has proven to be one of the promising renewable energies in the recent years. This field has witnessed a significant increase in the value of investments; the production capacity reached 227 GW in 2015 compared to 5.1 GW in 2005. In the traditional grid management, the grid operator must maintain the balance between supply and demand at all times to avoid security grid problems and economic losses. From grid management point of view, solar generation variability caused generally by clouds can make it more difficult for the grid operator to predict how much additional electric generation will be required to ensure the balance between supply and demand. Renewable power forecasting imposes itself as a key solution to efficiently handle renewable energy in power grid and must be properly accounted for in the complex decision-making processes required to balance supply and demand in the power system

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