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    COMPARISON BETWEEN THE EFFECTS OF DIFFERENT TYPES OF MEMBERSHIP FUNCTIONS ON FUZZY LOGIC FOR HYDROXY DRY CELL PERFORMANCE
    (STEF92 TECHNOLOGY LTD, 2016) Isiktas, Abdullah; Dincer, Keyser; Ata, Sadik
    In this study, hydroxy (HHO) dry cell performances in terms of voltage, current and temperature were modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Input parameters plate combination and time; output parameters voltage, current, temperature were described by RBMTF if-the rules. Current, voltage and temperature were measured for the different membership functions. Numerical parameters of input and output variables were fuzzificated as linguistic variables: very very low (L-1), very low (L-2), low (L-3), negative medium (L-4), medium (L-5), positive medium (L-6), high (L-7), very high (L-8) and very very high (L-9) linguistic classes. With the linguistic variables used, rules were obtained for this system. 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. The only condition a MF must really satisfy is that it must vary between 0 and 1. This paper presents the performance comparison of fuzzy logic with three different types of membership function.
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    Fuzzy logic modeling of performance proton exchange membrane fuel cell with spin method coated with carbon nanotube
    (PERGAMON-ELSEVIER SCIENCE LTD, 2017) Ata, Sadik; Dincer, Keyser
    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). This fuel cell performances at 20 degrees C, 40 degrees C, 60 degrees C were investigated experimentally and the best performance was determined and benefiting from experimental data, modeled with RBMTF method. Input parameters are; temperature (T), time (s), voltage density (V/cm(2)) and current density (A/cm(2)); output parameter power density (W/cm(2)) were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L-1), Very Low (L-2), Low (L-3), Negative Medium (L-4), Medium (L-5), Positive Medium (L-6), High (L-7), Very High (L-8) and Very Very High (L-9) linguistic classes. With the linguistic variables used, 81 rules were obtained for this system. The comparison between experimental data and RBMTF is done by using statistical methods. The coefficient of multiple determination (R-2) for power density of uncoated PEM and with CNT (20 degrees C) is 98.88%, power density of 20 degrees C, 40 degrees C and 60 degrees C temperatures is 97.12%. 80 values were obtained by RBMTF technique at 20 degrees C for uncoated PEM and with CNT. During discharge for 20 degrees C uncoated PEM for experimental power density maximum 0.021 Watt/cm(2) and uncoated PEM for fuzzy model maximum 0.0205 Watt/cm(2). 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 intermediate values which were estimated with RMBTF. 78 values at 30 degrees C and 50 degrees C which are not obtained from experimental work for power density are predicted by fuzzy logic method. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
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    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)
    (TRANS TECH PUBLICATIONS LTD, 2017) Ersoyoglu, Ali Serhat; Ata, Sadik; Dincer, Kevser; Onal, Gurol; Yilmaz, Yusuf
    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.