Rule-based mamdani-type fuzzy modeling of performance proton exchange membrane fuel cell with carbon nano tube

In this study, performance of proton exchange membrane (PEM) fuel cell was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Coating on the anode side of the membrane of PEM fuel cell was accomplished with the spin method by using carbon nanotube (CNT). In the experimental study, current and voltage performances before and after coating have been recorded at 20oC and then are compared to each other. It was determined the increasing of the performance of PEM fuel cell when coated with CNT. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like the coefficient of multiple determination (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used in PEM fuel cell. Performance tests of the system were not done for 30oC 50oC and 70oC. These values were estimated with RMBTF. © SGEM2015.