A Review on the Long-Term Performance of Proton Exchange Membrane Fuel Cells: From Degradation Modeling to the Effects of Bipolar Plates, Sealings, and Contaminants

Proton-exchange membrane fuel cells (PEMFCs) are regarded as promising alternatives to internal combustion engines (ICEs) to reduce pollution. Recent research on PEMFCs focuses on achieving higher power densities, reducing the refueling time, mitigating the final price, and decreasing the degradations, to facilitate the commercialization of hydrogen mobility. The design of bipolar plates and compression kits, in addition to their coating, can effectively improve performance, increase durability, and support water/thermal management. Past reviews usually focused on the specific aspect, which can hardly provide readers with a complete picture of the key challenges facing and advances in the long-term performance of PEMFCs. This paper aims to deliver a comprehensive source to review, from both experimental, analytical and numerical viewpoints, design challenges, degradation modeling, protective coatings for bipolar plates, and key operational challenges facing and solutions to the stack to prevent contamination. The significant research gaps in the long-term performance of PEMFCs are identified as (1) improved bipolar-plate design and coating, (2) the optimization of the design of sealing and compression kits to reduce mechanical stresses, and (3) stack degradation regarding fuel contamination and dynamic operation

Water management of the proton exchange membrane fuel cells: Optimizing the effect of microstructural properties on the gas diffusion layer liquid removal

The formation of water columns inside the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC), which is harmful phenomenon, can be controlled by the GDL's microstructure and material. Using computational fluid dynamics (CFD), a three-dimensional model is developed to monitor the impacts of the GDL's porosity and permeability on the maximum GDL liquid removal. In this regard, twenty-four different cases are simulated at the GDL contact angle of 110 degrees. Results indicate that higher permeabilities and porosities improve the GDL liquid removal and the performance of the system. Obtaining the simulation data, an artificial neural network (ANN) model is trained at the current density of 0.41 A/ cm(2) and the voltage of 0.6 V to predict the maximum GDL liquid removal in 300000 points and to perform the optimization. The ANN model is trained with four neurons with the respective mean squared error values 6.32422e-6, 1.00637e-5, and 4.12086e-6 for the training, validation, and testing, which approves the accuracy of the model. Using a fitted curve and the ANN model, the optimum values of the porosity and the permeability are computed to be 0.9 and 1.481e-11 (m(2)), respectively, to reach the maximum GDL liquid removal of 0.373 (kg/m(3)s). (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND licenseSCI-STI-JV

Performance evaluation of diesel engines (PEDE) for a diesel-biodiesel fueled CI engine using nano-particles additive

yy Today's researchers have made concerted efforts to benefit from biodiesel and to achieve better combustion due to its higher cetane number in comparison to that of diesel. The major drawback of utilizing biodiesel-diesel blend is the corresponding increase in the NOx emission, which can be solved using water. However, water results in higher HC and CO emissions that can be handled by the addition of metal-based nano-particles such as cerium oxide (CeO2). In this study, 36 different cases of these input parameters (different values of biodiesel, water, and nano-particles) have been examined experimentally, and the results are used to train an artificial neural network (ANN) model to produce 8866 data. Then, these data were utilized to find the maximum brake thermal efficiency while the value of output emissions and brake specification fuel consumption are minimum. In this regard, a new parameter called performance evaluation of diesel engine (PEDE) was introduced to decrease the number of output parameters into one. However, the results of sensitivity analysis on the PEDE indicated that the share of output parameters on this newly defined PEDE are not the same, and it demands modifications. Therefore, the exponents of each output parameter were modified by the application of sensitivity analysis. Finally, a modified PEDE that can predict the performance of diesel engines properly was introduced, and the optimum values were presented. Results indicated that the best performance occurs when the amount of cerium oxide nano-particles is 80 ppm, while the shares of biodiesel and water are 6 percent

Multi-criteria optimization of a renewable hydrogen and freshwater production system using HDH desalination unit and thermoelectric generator

This article presents the exergoeconomic evaluation of a new geothermal-based integrated system, which produces hydrogen and freshwater. The proton exchange membrane electrolyzer (PEME) and humidifier-dehumidifier (HDH) units are responsible for hydrogen and freshwater production, respectively. Kalina cycle and thermoelectric generator (TEG) provide the needed electricity to run the PEME. As both TEG and HDH work with low-temperature waste heat of the Kalina cycle and geothermal water, two different configurations for the suggested system are proposed, and evaluated by the exergoeconomic analysis. Levelized cost of evaluation (LCoE) also compares the suggested configurations with fossil fuel power plants, while the effects of various critical parameters of the system are evaluated in the parametric study. Since there are uncertainties about decision parameters, single- and multi-objective optimizations with properly defined objectives are performed to achieve the best performance in each operating mode. Optimization studies revealed that the optimal mode is superior in terms of exergy efficiency, freshwater cost, and hydrogen cost with the values of 22.49%, 2.94 $/m(3) and 7.37$/kg, respectively

A New Evaluation Criterion for Optimizing the Mechanical Properties of Toughened Polypropylene/Silica Nanocomposites

This study aims to experiment with the mechanical properties of polypropylene (PP)/thermoplastic elastomer/nano-silica/compatibilizer nanocomposite using the melt mixing method. The addition of polyolefin elastomers has proved to be an approachable solution for low impact strength of PP, while it would also reduce the Young's modulus and tensile strength. That is why reinforcement would be applied to this combination to enhance the elastic modulus. The mechanical properties of the prepared composites were devised to train an artificial neural network to predict these properties of the system in 6256 unknown points. Therefore, the sensitivity analysis was performed and the share of each input parameter on the respective output values was calculated. Additionally, a novel parameter called nanocomposite evaluation criterion (NEC) is introduced to analyze the suitability of the nanocomposites considering the mechanical properties. Accordingly, the formulation with optimal mechanical properties of toughness, elongation at break, tensile strength, Young's modulus, and impact strength was obtained

Poisoning Effects of Cerium Oxide (CeO2) on the Performance of Proton Exchange Membrane Fuel Cells (PEMFCs)

In this study, the poisoning effects of cerium oxide (CeO2) as the contaminant on the performance of proton exchange membrane fuel cells (PEMFCs) are evaluated. An experimental setup was developed to analyze the performance characteristic (I-V) curves in contaminated and non-contaminated conditions. Focused ion-beam scanning electron microscopy (FIB-SEM) cross-section images were obtained as an input for the energy dispersive X-ray (EDX) analysis. The results of the EDX analysis verified the presence of CeO2 in the contaminated membrane electrode assembly (MEA), in addition to fluorine and sulfur. EDX analysis also revealed that as a result of CeO2 contamination, sulfur and fluorine would be distributed all around the MEA, instead of being only in the membrane. The results illustrate that hydrofluoric acid (HF), sulfuric acid (H2SO4), and fluorinated polymer fragments are released, which enhance the crossover of the reactant gases through the membrane, hence reducing the cell’s performance. The I-V characteristic curves proved that the non-contaminated PEMFC setup had double the performance of the contaminated PEMFC

Thermoelectric Generator as the Waste Heat Recovery Unit of Proton Exchange Membrane Fuel Cell: A Numerical Study

The proton exchange membrane fuel cell (PEMFC) is a prominent environmentally friendly alternative candidate to internal combustion engines in automotive applications. The recovery of the waste heat of light-duty diesel engines has been investigated recently, which is similarly relevant for PEMFCs. Thermoelectric generators (TEG) applied on the stack’s walls have been already proposed and tested as a cooling method for small scale applications of the PEMFC. For the medium scale usages of the PEMFC stack, TEG technology may be further used to recover heat lost through the cooling water required for stack thermal management, which was the focus of the present study. Using an agglomerate model for the PEMFC and a computational fluid dynamic (CFD) thermal model for the TEG heat exchanger unit, the operation and performance of the PEMFC stack and heat recovery unit were simulated, respectively. After validation, results indicated that the transferred heat from the PEMFC to the cooling channel increased the temperature of the coolant from room temperature to 330.5 K at the current density of 0.8 A/cm2. CFD analysis revealed that 37.7 W of the heated wasted by the PEMFC stack could be recovered by the currently available TEG material and geometry

Two novel cogeneration charging stations for electric vehicles: Energy, exergy, economic, environment, and dynamic characterizations

This paper suggests two novel designs for the electric vehicle charging stations using LiMn2O4 Lithium-ion battery and based on a Solid Oxide Fuel Cell (SOFC) and absorption refrigeration cycle (ARC) technologies to provide electricity and cooling, respectively. The study is supported by the energy, exergy, exergoeconomic, dynamic, and life-cycle assessments. In both scenarios, results of the thermodynamic analysis revealed that the system can provide 294.73 kWh power and 117.79 kWh cooling capacity at the fuel utilization (FU) of 0.85 and SOFC current density of 0.75 A/cm2. After performing the life-cycle and exergoeconomic characterizations, artificial neural network (ANN) modeling was used to predict the performance of the system in 161,001 different values of the SOFC current density and FU. Using the developed ANN models, the Performance Evaluation Parameter (PEP) was defined to optimize the system considering energetic, exergetic, economic, and environ-mental aspects. Results indicated that PEP will have the highest value of 4.26 at the SOFC current density of 0.753 A/cm2 and the FU of 0.787 to reach the global warming (GW) of 1.48 (kg CO2 eq)/Wh, cost of 0.247 ($/kWh), output power of 338.75 kW, cooling capacity of 151 kW, energy efficiency of 75.0 %, and exergy efficiency of 51.68 %.SCI-STI-JV

Electric vehicle charging station using fuel cell technology: Two different scenarios and thermodynamic analysis

This study evaluates two different scenarios of an integrated system to generate electricity for a charging station using proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC). To improve the efficiency, the exhaust heat of these two fuel cells are recovered by two different bottoming power cycles of Kalina Cycle (KC) and Organic Rankine Cycle (ORC). The system is designed for a 100 kW charging station capable to charge five cars simultaneously, assuming a standard car used in daily life with a battery capacity of 36 kWh and a range of 220 km. Thermodynamic analysis of the system is performed in different current densities from 0.5 A/cm(2) to 0.8 A/cm(2). In the first scenario, results indicated that the overall energy efficiency of the system is 58.47% at 0.5 A/cm(2) and 49% at 0.8 A/cm(2), while that of the second scenario is 43.21% at 0.5 A/cm(2) and 35% at 0.8 A/cm(2). To improve the dynamic response of the system, a high capacity battery and a supercapacitor were integrated to the fuel cell system. It was found that a hybrid combination of the battery and supercapacitor improve the performance of the system. (C) 2021 The Author(s). Published by Elsevier Ltd

Organic Rankine Cycle as the Waste Heat Recovery Unit of Solid Oxide Fuel Cell: A Novel System Design for the Electric Vehicle Charging Stations Using Batteries as a Backup/Storage Unit

The novelty of this study is to suggest a novel design for electric vehicle charging stations using fuel cell technology. The proposed system benefits from the Organic Rankine Cycle (ORC) to utilize the exhaust energy of the Solid Oxide Fuel Cell (SOFC) stacks in addition to the Lithium-Ion battery to improve the efficiency by partial-load operation of the stacks at night. The study is supported by the thermodynamic analysis to obtain the characteristics of the system in each state point. To analyze the operation of the system during the partial-load operation, the dynamic performance of the system was developed during the day. Furthermore, the environmental impacts of the system were evaluated considering eighteen parameters using a life-cycle assessment (LCA). LCA results also revealed the effects of different fuels and working fluids for the SOFC stacks and ORC, respectively. Results show that the combination of SOFC and ORC units can generate 264.02 kWh with the respective overall energy and exergy efficiencies of 48.96% and 48.51%. The suggested 264.02 kWh contributes to global warming (kg CO2 eq) by 5.17 × 105, 8.36 × 104, 2.5 × 105, 1.98 × 105, and 6.79 × 104 using methane, bio-methanol, natural gas, biogas, and hydrogen as the fuel of the SOFC stacks