Optimizing Proton Exchange Membrane Fuel Cell Performance Through Flow Field Design Analysis

Fuel cells are an emerging energy technology that offers an alternative to traditional combustion-based power generation systems. They generate electricity through an electrochemical process that converts the chemical energy stored in fuels, such as hydrogen and methane, into electricity, with water and heat as byproducts.

Applications for fuel cells today range from stationary power generation to transportation. Despite their advantages, fuel cells face several challenges that limit their widespread adoption. One of the main challenges is the cost of fuel cell systems, which remains relatively high compared to traditional power generation systems. Additionally, fuel cells require high-purity fuels and specific operating conditions, which can be difficult and expensive to achieve. Another challenge is the lack of infrastructure for storing and distributing hydrogen, which limits the use of fuel cells in transportation applications [1, 2].

Fuel cells are an emerging energy technology that offers several advantages over conventional power generation systems. They generate electricity through an electrochemical process that converts the chemical energy stored in fuels such as hydrogen and methane into electricity [3]. Fuel cells are highly efficient and produce fewer greenhouse gas emissions than traditional power plants, making them an attractive option for addressing [4]. The fundamental design of the proton exchange membrane (PEM) fuel cell involves placing two electrodes on either side of an electrolyte. Hydrogen and oxygen cross over each electrode, producing electricity, heat, and water through a chemical reaction. The fuel cell supplies hydrogen fuel to its anode (negative terminal). The fuel cell's cathode (positive terminal) receives oxygen. A chemical process divides hydrogen into an electron and a proton. Each route to the cathode is unique. When used effectively, electrons can create energy for a load without going through the electrolyte. The proton travels through the electrolyte before rejoining the electron at the cathode. The electron, proton, and oxygen combine to make water, which is a harmless byproduct. Figure 1 depicts this procedure [5].

In general, fuel cells are defined primarily by the kind of electrolyte used and the difference in start time, which ranges from one second for PEM fuel cells to 10 minutes for solid oxide fuel cells.

This study investigated the impact of flow field design on the performance of PEM fuel cells using theoretical simulations. The contributions of this work are as follows:

$\bullet$ Pressure Drop Management: The results revealed that the E2 model outperforms other designs in managing pressure drop, with the lowest pressure drop at the anode side (7 Pa). This indicates its potential for improving fuel cell efficiency by minimizing energy losses due to pressure gradients.

$\bullet$ Cathode Pressure Performance: The A1 and A2 models were found to produce the highest pressures at the cathode, which aligns with expectations given the chemical reactions occurring in this region. This insight is crucial for designing flow fields that optimize pressure conditions for enhanced fuel cell performance.

$\bullet$ Current Density Optimization: Analysis of polarization curves identified the A2 model as delivering the highest current density, particularly at high pressures of up to 1200 Pa. This highlights the importance of pressure management in maximizing fuel cell output.

$\bullet$ Best Overall Design: Among the designs studied, the E2 model emerged as the most effective, proving upper-pressure distribution and efficient management of reactants and products.

The following are recommended as future work and extensions of the research.

$\bullet$ Long-term Performance: Investigating the long-term durability and performance of the E2 model under varying operating conditions.

$\bullet$ Advanced Flow Field Designs: Further exploration of alternative flow field designs or modifications to the E2 model could yield even greater improvements in fuel cell efficiency and performance.