Sensitivity analysis of fuel cell operating conditions based on LOESS-Sobol method

Decoupling the influence of operating factors such as temperature, humidity, and back pressure is essential for improving fuel cell efficiency. This study employs a regression model combining Locally Weighted Scatterplot Smoothing (LOESS) with the Sobol index method to analyze the effects of two major parameter categories: temperature and humidity, and stoichiometry and back pressure, on fuel cell output voltage. Using limited experimental data, it uncovers complex interactions and sensitivities among these factors. The results indicate that the stack temperature has the greatest impact, accounting for 60%, with minimal influence from the changes in the current density. Cathode humidity impacts output voltage by about 10%, while anode humidity accounts for approximately 5%. Significant interactions between temperature and both anode and cathode humidity contribute around 9% each. Among stoichiometries, cathode stoichiometry has the largest impact, exceeding 50% at low current density and growing to over 70% as current increases. Back pressure and anode stoichiometry each have an impact of around 10%, with minimal mutual influence. This study highlights the extent to how different operating parameters influence fuel cell performance, offering valuable insights for optimizing fuel cell operating conditions.