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Polarization curve of standard test of Nafion 112 membrane at RHC 50%, membrane compression 5% and Nafion Percent 20%, 25%, (a) pressure 5 psig (b) 15 psig (c) 25 psig.

Polarization curve of standard test of Nafion 112 membrane at RHC 50%, membrane compression 5% and Nafion Percent 20%, 25%, (a) pressure 5 psig (b) 15 psig (c) 25 psig.

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Reported data in this paper are about Nafion 112 membrane standard tests and MEA activation tests of PEM fuel cell in various operation condition. Dataset include two general electrochemical analysis method, Polarization and Impedance curves. In this dataset, effect of different pressure of H2/O2 gas, different voltages and various humidity conditi...

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... While previous research by Hamidi et al. [58] placed the foundation for investigating the performance of the Nafion 112 membrane in low-temperature FCs, there is still a research gap regarding the utilization of advanced techniques to optimize the power density of the FC. The current study aims to address this gap by employing ANFIS and the Salp swarm algorithm (SSA) to enhance the performance of the FC. ...
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The adoption of Proton Exchange Membrane (PEM) fuel cells (FCs) is of great significance in diverse industries, as they provide high efficiency and environmental advantages, enabling the transition to sustainable and clean energy solutions. This study aims to enhance the output power of PEM-FCs by employing the Adaptive Neuro-Fuzzy Inference System (ANFIS) and modern optimization algorithms. Initially, an ANFIS model is developed based on empirical data to simulate the output power density of the PEM-FC, considering factors such as pressure, relative humidity, and membrane compression. The Salp swarm algorithm (SSA) is subsequently utilized to determine the optimal values of the input control parameters. The three input control parameters of the PEM-FC are treated as decision variables during the optimization process, with the objective to maximize the output power density. During the modeling phase, the training and testing data exhibit root mean square error (RMSE) values of 0.0003 and 24.5, respectively. The coefficient of determination values for training and testing are 1.0 and 0.9598, respectively, indicating the successfulness of the modeling process. The reliability of SSA is further validated by comparing its outcomes with those obtained from particle swarm optimization (PSO), evolutionary optimization (EO), and grey wolf optimizer (GWO). Among these methods, SSA achieves the highest average power density of 716.63 mW/cm2, followed by GWO at 709.95 mW/cm2. The lowest average power density of 695.27 mW/cm2 is obtained using PSO.
... In Equation (1) Based on the motor power, the series DC motor was selected as the vehicle's drive motor. The proposed design of the HEV has at least two power sources, a fuel cell (FC) system as a power source [24,25], and an AGM (absorbent glass mat) battery package [14]. The drive batteries are 48 V with a capacity of 80 Ah (3.84 kWh). ...
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The paper proposes a Hybrid Electric Vehicle (HEV) design based on the installation of a fuel cell (FC) module in the existing Daewoo Tico electric vehicle to increase its range in urban areas. Installing an FC module supplied by a 2 kg hydrogen tank would not significantly increase the mass of the electric vehicle, and the charging time of the hydrogen tank is lower than the battery charging time. For design analysis, a model was created in the MATLAB/Simulink software package. The model simulates vehicle range at different HEV speeds for Absorbent Glass Mat (AGM) and Proton Exchange Membrane Fuel Cell (PEMFC) power sources. The greatest anticipated benefit derived from the model analysis relates to velocities ranging from 20 km/h to 30 km/h, although the optimal HEV velocity in an urban area is in the range of 30 km/h to 40 km/h. The results indicate that this conversion of Electric Vehicle (EV) to HEV would bring a benefit of 87.4% in terms of vehicle range in urban areas. Therefore, the result of the conversion in this case is a vehicle with sub-optimal characteristics, which are nevertheless very close to optimal.
... Dataset is reported in ECSIM organization GitHub account [4]. ECSIM organizarion is a research team that investigate on power sources by experimental equipment to provide valid usable data [5] and make useful software for improvement of research and development in power sources. This dataset is licensed under a Creative Commons Attribution 4.0 International License. ...
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p>Dataset includes Direct Borohydride Fuel Cell (DBFC) impedance and polarization test in anode with Pd/C, Pt/C and Pd decorated Ni–Co/rGO catalysts. In fact, different concentration of Sodium Borohydride (SBH), applied voltages and various anode catalysts loading with explanation of experimental details of electrochemical analysis are considered in data. Voltage, power density and resistance of DBFC change as a function of weight percent of SBH (%), applied voltage and amount of anode catalyst loading that are evaluated by polarization and impedance curves with using appropriate equivalent circuit of fuel cell. Can be stated that interpretation of electrochemical behavior changes by the data of related cell is inevitable, which can be useful in simulation, power source investigation and depth analysis in DB fuel cell researches. </p