Abstract
Proton exchange membrane (PEM) electrolysis cells play a vital role in high-purity and sustainable hydrogen production by utilizing the DC power from renewable energy sources and can help minimize harmful greenhouse gasses. The performance of PEM electrolysis cells can be improved significantly by optimizing the operating and design conditions. In the present study, experiments have been conducted to investigate the influences of the operational parameters (cell voltage, temperature, and water flow rate) on the performance of the PEM electrolysis cell with a total surface area of 9 cm2. Design of experiment and Taguchi method were also applied to the experimental system to optimize PEM electrolysis cell operating parameters. Cell voltage, temperature, and water flow rate are the three main control factors that have been varied between 1.6 and 2.4 V, 40–80 °C, and 16.5–30.6 mL/min, respectively. The results were analyzed using analysis of variance (ANOVA) and the signal-to-noise (S/N) ratios by Minitab software for the optimal operational factors. The results show that the best electrolysis cell performance is obtained at a temperature of 80 °C, cell voltage of 2.4 V, and water flow rate of 16.5 mL/min. The maximum current and hydrogen flow rate for the optimal combinations of the input factors were 17.398 A and 152.019 mL/min, respectively. At the highest cell performance, LHV (low heating value) and HHV (high heating value) energy efficiencies were calculated as 59.6% and 70.4%, respectively. The cell voltage has considerably affected the current and hydrogen flow rate with contributions of 91.91% and 90.81%, respectively. The water flow rate has a minimal effect, with contributions of 1.04% and 1.25%, respectively. Our results indicated that the current and hydrogen flow rate reflecting the cell performance increased with increasing the cell voltage, the temperature and decreasing the water flow rate. Therefore, the ideal combination of operating factors is essential to provide the best cell performance and lower operational costs.
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