Modeling of the Effects of Cyclic Voltammetry (CV) Using Fuzzy Logic with Different Membership Functions for Proton Exchange Membrane Fuel Cell (PEM) with Polyvinyl Alcohol/Nano Silver (PVA/Ag)

In this study, the effects of cyclic voltammetry (CV) has been modeled with Rule-based mamdani-type fuzzy (RBMTF), by using experimental data for proton exchange membrane fuel cell with PVA/AG. In the system developed, RBMTF apply input parameters are CV, scan rate and time, output parameters are current density and voltage. 12300 values for experimental study also obtained with RBMTF. Membership functions (MFs) are the building blocks of fuzzy set theory, i.e., fuzziness in a fuzzy set is determined by its MF. Accordingly, the shapes of MFs are important for a particular problem since they effect on a fuzzy inference system. They may have different shapes like triangular, trapezoidal, Gaussian, etc. When the results obtained from RBMTF and statistical analyses of experimental data have been compared, it has been determined that the two groups of data are coherent, and that there is not a significant difference between them. As a result, this study indicates that RBMTF with different membership functions can be safely used for CV.