Optimization of gas diffusion layer thickness for proton exchange membrane fuel cells under steady-state and load-varying conditions

This work proposes a design principle of the optimal thickness for cathode gas diffusion layers (GDLs) of proton exchange membrane fuel cells (PEMFCs) based on a balance of cell performances under both steady-state and load-varying conditions. Using a three-dimensional and two-phase model, the effects of cathode GDL thickness (50, 100, 200, and 400 mu m) on steady-state performances and transient response characteristics are studied. The results show that under steady-state conditions, an extremely thin cathode GDL would lead to non-uniform oxygen and liquid water distributions, whereas an especially thick cathode GDL would increase oxygen transport resistance. Thus, there is an optimal cathode GDL thickness, yielding the best steady-state performance. A current overshoot phenomenon, arising from high local oxygen concentrations at cathode catalyst layers (CLs), is observed when the load voltage decreases abruptly. Thinner cathode GDLs would weaken the overshoot and shorten the recovery time of current density. Conversely, low local oxygen concentrations at cathode CLs caused by high liquid water saturation levels lead to a current undershoot phenomenon when the load voltage increases abruptly. Thinner cathode GDLs would strengthen the undershoot but shorten the recovery time of current density. The optimal choice of cathode GDL thickness should weigh up the steady-state and the transient performance. Based on this principle, the optimal cathode GDL thickness is selected as 100 mu m.

Automated summary

This study proposes a design principle for the optimal thickness of cathode gas diffusion layers (GDLs) in proton exchange membrane fuel cells (PEMFCs), and investigates the effects of different thicknesses on cell performance under steady-state and transient conditions. The results indicate that there is an optimal thickness that yields the best performance in both steady-state and transient scenarios.