Integrating fuzzy modelling and war strategy optimization for identifying optimal operating factors of direct ethanol fuel cell

Operating factors, including temperature, pressure, alcohol concentration, and reactant flow rate, significantly impact how much energy is produced by direct alcohol fuel cells. The cell's performance may go down or up depending on how these factors vary. For instance, greater alcohol temperatures and concentrations can speed up reactions and boost fuel cell efficiency, whereas lower alcohol temperatures and concentrations can have the opposite effect. Consequently, optimizing the operating circumstances is essential to getting the most energy possible out of direct alcohol fuel cells. Therefore, the primary goal is to develop a solid fuzzy model to simulate direct ethanol fuel cells (DMFC). Three process variables-ethanol flow rate, ethanol concentration, and temperature-are considered to increase the power density of DEFC. First, a fuzzy model of the DEFC was developed using experimental data. The best operating conditions to increase power density are then determined using war strategy optimization (WSO). Thanks to fuzzy, the RMSE decreased from 0.529 using RSM to 0.0292 using fuzzy (decreased by 94.5 %), compared to 0.529 using RSM. By around 11.7 %, the squared-R for prediction increases from 0.88 (using RSM) to 0.9831 (using fuzzy). The fuzzy model's low RMSE and high R-square values show the successful modelling phase. Compared to measured data and RSM, integrating fuzzy and WSO increased DEFC's power density by 5 % and 7.26 %, respectively. The ideal ethanol flow rates, concentrations, and temperatures are 9.4 ml/min, 0.25 M, and 74C, respectively.