Search

Carbon fiber paper (CFP) is one of the most widely used gas diffusion layer materials for proton exchange membrane fuel cells (PEMFC) due to its excellent properties such as high conductivity, high strength, high air permeability and corrosion resistance. In this study, CFP was prepared using the phenolic resin (PF) in-pulp addition method. The effect of PF content on the properties of hot-pressed paper (HPP) and CFP was investigated. The results showed that when the dosage of polyethylene oxide (PEO) was 1.5 wt%, the flocculation effect of PEO on PF was basically complete, and the water filterability and retention of carbon fiber pulp were relatively optimal. After HPP was carbonized into CFP, the hydrophobicity, average pore size, porosity, and air permeability increased, while the resistivity and tensile strength decreased. With the increase of PF content, the tensile strength of CFP gradually increased, while the average pore size, porosity, air permeability and resistivity decreased. When the PF content was 250 wt%, the average pore size of CFP was 36.5 μm, the water contact angle was 127°, the porosity was 69.7%, the air permeability was 7.81 × 103 mL mm/(cm2·h·mmHg), the resistivity was 21.1 mΩ cm, and the tensile strength was 15.7 MPa. In addition, the CFP prepared using PF in-pulp addition method had a relativity uniform pore size distribution and high air permeability. Therefore, this work shows that the CFP prepared using this technique exhibits excellent comprehensive performance, and enables the manufacturing of CFP to be more efficient, low-cost, and environmentally friendly. [Display omitted] • Carbon fiber paper was prepared efficiently using the phenolic resin in-pulp addition method. • Polyethylene oxide exhibits strong adsorption ability on phenolic resin in carbon fiber pulp. • The melting temperature of phenolic resin is a critical point in the preparation process of carbon fiber paper. • Carbon fiber paper possesses a relatively uniform pore size distribution and high air permeability. [ABSTRACT FROM AUTHOR]

Carbon paper as a macroporous substrate of gas diffusion layer in proton exchange membrane fuel cells directly impacts the output performance of cells. In this study, we present a straightforward strategy to improve the overall performance of carbon paper by mixing short/long (6mm/10 mm) chopped carbon fibers at an optimal concentration of phenolic resin. The results show that incorporating longer carbon fibers can increase the porosity, conductivity, gas flux, and mechanical properties of carbon paper. The membrane electrode assembly achieved a peak power density of 1182.61 mW cm−2 at 60% RH using carbon paper with a long carbon fiber content of 40 wt% and an impregnation concentration of 10 wt%. This outperforms commercially available carbon paper. Based on electrochemical impedance spectroscopy results, it was confirmed that our carbon paper had a lower mass transfer resistance of only 32.17 mΩ cm−2 under conditions of 2 A cm−2 and 60% RH. This was due to its sparser three−dimensional network-like pore structure which was created by mixing different lengths (6mm/10 mm) of carbon fibers. This work provides new insights into preparing high−performance carbon papers. • The nature of carbon paper is regulated by mixing short/long (6mm/10 mm) CFs ratio. • The long carbon fiber contents of 20–40 wt% present better physical properties. • The optimal carbon papers can mitigate mass transfer resistance. • MEA composed of the optimal CP shows a higher power density than commercial CP. [ABSTRACT FROM AUTHOR]

The plasma treatment method, which is a simple and ecologically benign procedure, is used to treat the gas diffusion layer (GDL) surface for proton exchange membrane fuel cell (PEMFC) application. The surface plasma treatment greatly aids in the uniform in situ growth of platinum (Pt) nanowires on the GDL surface to fabricate gas diffusion electrodes (GDEs). Helium (He) and nitrogen (N 2) are used, and the outcomes from utilising each gas independently are compared at four different durations between 30 s, 60 s, 90 s, and 120 s. Membrane Electrode Assemblies (MEAs) are fabricated with the as-prepared GDEs and tested in H 2 /air PEMFC single cells. The testing results show the nitrogen plasma applied to the GDE surface for 60 s produces the best power performance with a current density of 1372.7 mA/cm2 at 0.6V. [Display omitted] • The surface of the gas diffusion layer (GDL) was activated using the plasma treatment method. • Carbon papers, whose surface was activated by He and N2 in plasma, were immersed in the prepared Pt solution. • Pt nanowires were allowed to grow on carbon papers. • Membrane Electrode Assemblies (MEAs) were created using as-prepared GDEs as the cathode and purchased GDL as the anode. • As a result of testing the created MEAs, it was seen that the GDL surface activated using N 2 plasma gave better results. [ABSTRACT FROM AUTHOR]

3D-ordered catalyst electrodes have been recognized as one effective strategy to reach high current density operation for proton exchange membrane fuel cell (PEMFC) applications. Gas diffusion electrodes (GDEs) with platinum nanowire arrays in-situ grown on gas diffusion layer (GDL) surface is an important contribution in this area, but the performance is highly dependent on the GDL surface properties. In this study, the GDLs available in the market are systematically investigated, with a focus on the influence of the GDL surface properties on the in-situ growth of Pt nanowire arrays to fabricate GDEs as cathodes for PEMFCs. The experimental results indicate that mesopores especially micropores play a key role. They enable a hydrophilic surface for the isopropanol pretreated GDL, facilitating the in-situ growth of Pt nanowires to form a uniform array with a large electrochemical surface area (ECSA), finally leading to a high-power density. With Freudenberg H24CX483 carbon paper GDL, the highest power density of 0.9 W cm−2 is achieved. The understanding achieved here could be further used to develop novel GDLs for fabricating the next generation of electrodes for large current density operations. [Display omitted] • The surface wet ability of GDLs plays a critical role to fabricate Pt nanowire array electrodes. • Mesopores especially micropores leading to hydrophilic surface after isopropanol treatment. • Uniformly distributed nanowire arrays enable large ECSA finally a high power density. • Freudenberg H24CX483 carbon paper GDL shows the best property for this application. [ABSTRACT FROM AUTHOR]

Fuel cell electric buses (FCBs) have proven to be a technically viable solution for transportation, owing to various advantages, such as reliability, simplicity, better energy efficiency, and quietness of operation. However, large-scale adoption of FCBs is hindered by the lack of extensive and structured infrastructure and the high cost of clean hydrogen. Many studies agree that one of the significant contributors to the lack of competitiveness of green hydrogen is the cost of electricity for its production, followed by transportation costs. On the one hand, to reduce the investment cost of the electrolyzer, high operating hours should be achieved; on the other, as the number of operating hours decreases, the impact of the electricity costs declines. This paper presents an innovative algorithm for a scalable hydrogen refuelling station (HRS) capable of successfully matching and identifying the most cost-efficient levelized cost of hydrogen (LCOH) produced via electrolysis and connected to the grid, based on the HRS components' cost curves and the hourly average electricity price profile. The objective is to identify the least-cost range of LCOH by considering both the electric energy and the investment costs associated with a hydrogen demand given by different FCB sizes and electrolyzer rated powers. In addition, sensitivity analyses have been conducted to quantify the technology cost margins, and a cost comparison between the refuelling of an FCB fleet and the recharging infrastructure required for an equivalent fleet of Battery Electric Buse (BEB) has been performed. An LCOH of around 10.5 €/kg varying from 12 €/kg (2 FCB) to 10.2 €/kg (30 FCB) has been found for the best-optimized configurations. The final major conclusion of this paper is that FCB technology is currently not economically competitive. Still, a cost contraction of the electric energy price and the electrolyzer capital investment would lead to a 50% decrease in the LCOH. Furthermore, increasing renewable energies into the grid may shift the electricity cost curve, resulting in higher prices when the BEB recharging demand is more significant. This impact, in addition to the peak power load and longer recharging times, might contribute to bridging the gap with FCBs. • Techno-economic model for the sizing of an HRS with grid-connected electrolyzer. • The widespread diffusion of H2 technology in mobility needs both reliability and cost-effectiveness. • Investigation of various electrolysers rated powers and fuel cell buses fleet size. • An action on both CAPEX and OPEX would lead to potential cost margins improvement. • It is found that the best configuration that balances the CAPEX and OPEX coincides with an LCOH ranging from 12 to 10 €/kg. [ABSTRACT FROM AUTHOR]

The proton exchange membrane fuel cell (PEMFC) air supply system is a complex nonlinear system with strong coupling of air flow and pressure. To avoid oxygen starvation and unstable output performance during rapid load changes, the oxygen excess ratio (OER) and air pressure need to be controlled effectively. To cope with the nonlinearity, coupling and uncertainty of the PEMFC air system, this paper puts forward a coordinated controller regulating OER and air pressure based on the input-output linearization and sliding mode methods. Firstly, a control-oriented third-order model is proposed to describe the dynamic behavior of the air supply system. Secondly, this paper decouples the flow and pressure of the PEMFC air system by using an input-output linearization method to obtain two independent linear subsystems. Moreover, a sliding mode method, effectively coping with the uncertainty of the system model, is designed to regulate the OER and air pressure of the PEMFC, which enhances the robustness of the control system. The overall simulation outcomes show that the proposed controller regulates OER and cathode pressure with smaller root mean square error (RMSE) and mean absolute percentage error (MAPE) compared with the combined proportional integral (PI) and feedforward controller. • A modified model oriented to control of air supply system is proposed. • Input-output linearization and sliding mode are used to develop coordinated control strategies. • The outcomes illustrate that the air supply affects the output performance of the fuel cell. • Control performance in the presence of model uncertainty is verified. [ABSTRACT FROM AUTHOR]

Locomotive engines serve as the powering heart of rail transportation which is widely used for massive cargo over long distances. The traditional locomotive engines have depended on the internal combustion engine for decades, operated using fossil fuels that negatively impact the environment. Since more and more commodities are transported by trains, the prime engines need to be improved where the fuels are expected to enhance the engine's performance and alleviate the environmental impact. This paper presents a comparison of three developed locomotive engines with different configurations, such as an internal combustion engine combined with a gas turbine and molten carbonate fuel cell (ICE-GT-MCFC), a gas turbine combined with a solid oxide fuel cell and onboard hydrogen production using aluminum electrolysis cell (GT-SOFC), and a GT combined with sold oxide and proton exchange membrane fuel cells (GT–SOFC–PEMFC). The paper then identifies one hybridized engine, which is GT–SOFC–PEMFC, according to its low weight and better performance to conduct an optimization study to enhance its efficiency, reduce the cost, and lower the environmental impact. The present optimization study is undertaken through a multi-objective particle swarm optimization, involving thermodynamic, exergoeconomic, and exergoenvironmental analyses. The optimized GT–SOFC–PEMFC locomotive engine is improved in power from 5.9 MW to 7.3 MW and improved in performance to 49.1% energetic efficiency and 47.0% exergetic efficiency. Additionally, the optimized GT–SOFC–PEMFC engine has less specific fuel and product cost of 24.9 $/GJ and 34.7 $/GJ, respectively, and less specific exergetic environmental impact of fuel and product of 13.2 Pt/GJ and 16.2 Pt/GJ, respectively. Also, the relative cost difference and relative environmental impact difference are significantly reduced by more than 20% to 39.4% and 22.8%, respectively. The operational conditions of the optimized GT–SOFC–PEMFC engine are improved to achieve better efficiency and better cost effectiveness in a more environmentally-benign manner. • Comparison between three hybridized combined locomotive engines is established. • Optimized GT–SOFC–PEMFC engine has 7.3 MW power and 49% energetic efficiency. • Specific exergetic product cost declined to 51 $/GJ for fuel and 35 $/GJ. • Specific exergetic environmental impact for fuel and product becomes 13 and 16 Pt/GJ. • The relative environmental impact difference becomes 22.8% instead of 44.3%. [ABSTRACT FROM AUTHOR]

Clean energy devices have a great ability to change the world because they strengthen the economy and preserve society. The continuous improvement and progress in nanomaterials and nanotechnology have a great role in human life. The increasing prevalence of PEM fuel cells makes them one of the most viable sustainable energy sources. Nanostructured materials synthesis methodologies have introduced a breakthrough and found to overcome the obstacles for PEMFC commercialization. Amongst them, wet chemical approaches are rapidly expanding and beneficial for the fabrication of nanoparticles since they contribute toward the attainment of a range of essential nanoparticle characteristics like sizes, morphologies, structures, and phases. Wet chemical manufacturing enables fine-tuning of reaction parameters to generate the desired nanomaterials. This review article focuses on the latest improvements in wet chemical methods to better regulate the quality of nanomaterials. This paper examines how wet chemical approaches (hydrothermal synthesis, spray pyrolysis, sol-gel processing, and co-precipitate synthesis, among others) can contribute to the scalable manufacturing of nanoparticles to uphold rising industrial requirements. And how wet chemical methods have a significant influence on power generation systems (Fuel cells) along with their pros and cons. This review carefully analyzes and summarizes synthetic methods and optimized factors in order to prepare nanoparticles and carefully analyzes the reported data. In this paper, the electrochemical analysis, morphological evaluation, compositional analysis, and performance testing of materials produced using wet chemical techniques have been investigated. Recent signs of progress and innovative techniques used to overcome the complexities of synthetic nanoparticle processing. This article is a holistic approach including social, economic, and ecological aspects in the wet chemical process and will certainly help in the fabrication, and application of nanoparticles for PEM Fuel cells. [Display omitted] • Introduction to the status of materials synthesis in energy generating devices. • Overview of wet chemistry Approaches for PEMFC. • Impact of synthesis parameters on properties of materials. • Pros and Cons of wet chemistry techniques for material synthesis. [ABSTRACT FROM AUTHOR]

Unitized regenerative proton exchange membrane fuel cell (URPEMFC) as a self-sufficient hydrogen energy system offers a unique proposition for achieving a net zero emissions future. The system combines the operation of water. Due to the design parameters and operating conditions of URPEMFC, the potential cycling from the mode switching, high temperature, humidified environment and the long exposure of metallic components to hydrogen are the primary factors causing degradation to the system. Consequently, the conventional graphite bipolar plate (BP) suffers heavily under such an environment while giving rise to alternative metallic base materials, such as titanium, stainless steel, and aluminum. Various surface treatment and coating methods are currently under investigation to provide the required corrosion resistance while maintaining feasible manufacturing process and cost. This paper presents an overview into the degradation phenomena of URPEMFC that contributes to the corrosion of BP that is affecting the performance and future commercialization of the system. The operating condition of the system is summarized in terms of fuel cells and water electrolyzers respectively, along with the integration of both operations as a system. Next, the paper outlines the degradation phenomena observed on BP and the behavior of various materials under such conditions. The performances of various base and coating materials have been compiled as have characterization methods that are useful in measuring corrosion resistance. This paper aims to provide a better understanding on the overall degradation of BP in URPEMFC and overview of various material choices to identify the optimal corrosion mitigation solution. [Display omitted] • Breakdown of the URPEMFC operating parameters from the respective operation modes. • System design approaches allowing integration of fuel cell and electrolyzer modes. • Identification of the main degradation mechanism on the BP. • Tabulated data of various base materials and coatings performance. • Discussion of current experimental and modeling methods for corrosion resistance characterization. [ABSTRACT FROM AUTHOR]

Guaranteeing rapid management of oxygen excess ratio (OER) for proton exchange membrane fuel cells (PEMFC) under load variations is a challenge with practical significance. To improve the controller response of PEMFC air supply system, a fixed time fault-tolerant control strategy is proposed in this paper. A fixed convergence time of PEMFC air supply control system is quantified and guaranteed by the proposed method and the control response can be accelerated by reducing the setting time. The contributions of this paper is fourfold. Firstly, the manifold leakage fault is estimated by fixed time fault observer, which can improve the real-time fault tracking performance of the control system. Secondly, a hierarchical fixed time sliding mode controller is proposed to regulate the OER rapidly. Furthermore, a novel adaptive term is employed to reduce the effects of the chattering from fault observer in the outer loop. Finally, the effectiveness of the proposed method is verified on a real-time PEMFC simulation platform. Experimental results on a Hardware-in-the-loop (HIL) platform show that the proposed fixed time fault tolerant control strategy has the characteristics of fast response and high robustness. [Display omitted] • Fixed time fault observer is employed to monitor the manifold leakage. • Fixed time control framework guarantees a quantified stabilization time of OER. • An adaptive term reduces the chattering effects of the fault observer. • The FTC method is validated on a high-fidelity HIL platform. [ABSTRACT FROM AUTHOR]

To tackle the carbon emission problem, the exploitation of renewable energy resources (RESs) with zero emissions has gained much importance. In this context, hydrogen has become an important resource to involve itself in distributed energy resources (DERs) to generate electricity, energize vehicles, and heat our living areas. The utilization of hydrogen technologies is indispensable due to their procurement, environmental friendliness, and high efficiency for DERs. A challenging area in the field of hydrogen energy technologies is extracting efficient power and integration to DERs. This paper investigates how to model and operate a proton exchange membrane fuel cell (PEMFC) stack in a DER application to establish a living lab facility for educational and research purposes by covering Power-to-X (P2X). The PEMFC model of the studied system is designed in a MATLAB/Simulink environment and implemented in an experimental testbed. Thus, a fuel cell (FC) unit as a complementary source is preferred to be used near a photovoltaic (PV) array, a small-scale wind turbine (WT), and a lead acid battery energy storage system (BESS) by creating a P2X concept to form a living lab platform. Beyond the model, regarding the experimental part, a PV array, a WT, and a BESS are combined with a PEMFC module that is rated output of 1200 W. Expect for all systems, the FC part is emphasized in this study. Also, a dynamic model of the mentioned PEMFC is proposed and verified. • Importance of hydrogen energy is focused on its advantages, future role, potential, and challenges. • FC unit as a complementary source is evaluated by creating a P2X concept. • This platform is designed to meet the energy needs of research-education, diversify the supply, increase energy independence. • Energy procurement is supplied via green energy during a lesson, which is noteworthy and instructive. • Feasibility of combined PV/WT/BESS/PEMFC system is investigated. [ABSTRACT FROM AUTHOR]

Due to the widespread use of multi-generation systems utilizing renewable energy sources and the growing global demand for such systems from both economic and environmental considerations, numerous researchers have focused on the design and evaluation of their performance. To this end, this research presents a biomass-based multi-generation system with an innovative and practical design that can generate electricity, heat, and hydrogen. This system includes a modified gas turbine cycle, a supercritical CO 2 (SCO 2) cycle, a transcritical CO 2 (TCO 2) cycle, a proton exchange membrane (PEM) electrolyzer, and a PEM fuel cell unit. This study aims to evaluate the impact of various biomass sources (paper, wood, paddy husk, and municipal solid waste) on the system performance. The proposed system has been analyzed using the first and second laws of thermodynamics. This system uses the maximum capacity to produce power, heat and hydrogen. A fuel cell unit has been used to consume hydrogen and generate more electricity. In the basic mode, the system has energy and exergy efficiencies of 47.89% and 32.26%, respectively, and can produce 2.74 kg/h of hydrogen. The biomass fuel consumption rate within the system is 0.055 kg/s. The overall exergy destruction of the system amounts to 1240 kW, with the biomass boiler and the condenser being the components that experience the greatest exergy destruction, registering values of 535.5 kW and 432.3 kW, respectively. Notably, employing municipal waste as biomass increases the system's exergy efficiency to 33.16%. • To investigate a biomass-driven system for producing power, hydrogen, and heating. • To evaluate the impact of various biomass sources on the system performance. • To use PEME for hydrogen and PEMFC for power and heat production. [ABSTRACT FROM AUTHOR]

In recent years, Electric Vehicles (EVs) powered by a Proton Exchange Membrane Fuel Cell (PEMFC) which has high energy density and efficiency have become an attractive solution for the automotive industry. However, since the power density of the PEMFC is not high enough for different road conditions such as accelerating and going uphill, a supercapacitor (SC) is preferred as the auxiliary energy source for high power density in EVs. Thus, in this paper, a hybrid power system consisting of the Fuel Cell (FC) and SC for a Four-Wheel Drive Electric Vehicle (4WDEV) is proposed. Since energy requirement of the EV depends on the travel route, an effective Energy Management System can be designed by using a Geographic Information System (GIS). According to the road trajectory, the power requirement of the EV is estimated and thus, energy consumption is reduced. The proposed system is validated by using the Matlab Simscape Toolbox. • A hybrid power system consisting of a PEM Fuel Cell and SC for a 4WDEV is proposed. • An effective energy management system is designed using a GIS based on road route. • The high power demand of the EV is met from the SC in the sloping roads. • The energy consumption and the stresses of the power converters are reduced. [ABSTRACT FROM AUTHOR]

In this paper, composite proton exchange membranes (PEMs) based on functionalized graphene oxide (NGO) and carboxylated sulfonated poly aryl ether ketone sulfone (C-SPAEKS) were successfully synthesized. Functionalized graphene oxide was synthesized using graphene oxide as a substrate, and then diethylenetriamine (DETA) was chemically bound to the graphene oxide. The 1H NMR, FT-IR and XPS were used to characterize the NGO and composite membranes. The results show that the composite membranes have good proton conductivity, dimensional stability and electrochemical performance. The swelling rate of all the composite membranes was less than 18%, which indicates that they have good dimensional stability. Compared to C-SPAEKS membrane (34.8 mS cm-1 at 20 °C, 109.8 mS cm-1 at 90 °C), the proton conductivities of C-SPAEKS/GO-0.75 membrane (52.4 mS cm-1 at 20 °C, 171.1 mS cm-1 at 90 °C) were significantly improved. Meanwhile, the C-SPAEKS/NGO-0.75 achieved peak power density of 407.77 mW cm-2 at high OCV of 0.9576 V. Such a result is much superior to the C-SPAEKS membrane (0.8973 V, 190.72 mW cm-2) and the Nafion 117 (0.99 V, 302 mW cm-2), and demonstrated good single-fuel cell performance. In summary, it can be well concluded that functionalized GO as filler makes an significant contribution in improving the overall performance of the composite membranes. • Functionalized GO containing amino group was synthesized. • An efficient and orderly proton transport channel was constructed. • The hybrid PEMs showed good proton conductivity (171.1 mS cm-1, at 90 °C). • The hybrid PEMs showed good single cell performance (407.77 mW cm-2, 80 °C, 100% RH). • Acid-base combination could improve proton conductivity effectively. [ABSTRACT FROM AUTHOR]

In order to solve the problems of uneven component diffusion, weak mass transfer capability and flow field flooding in the conventional flow field of proton exchange membrane fuel cell (PEMFC), and to improve the cell output power. In this paper, a novel folded porous cathode flow field is proposed. A numerical model of three-dimensional multiphase flow is established for comparative study, which reveals the relationship between the component flow characteristics and mass transfer performance of PEMFC. The folding rib structure of the novel flow field triggers gas vortices in the channel and generates secondary flow, improves the mass transfer capability of reactants between the channel and the GDL, and alleviates the drainage problem of the porous layer under the rib. The angle, length and number of folding at the rib of the flow field were mainly changed, and the mass fraction difference coefficient (CV Mi) was used to compare the uniformity of the distribution of the components of the flow field, and the optimal flow field structure was obtained as FP6-7, which increased the current density by 44.9% compared with the traditional linear flow field. For the first time, the secondary flow evaluation criterion absolute vortex flux number J ABS n was introduced to evaluate the mass transfer performance. The influence of fluid flow characteristics on the mass transfer performance is revealed. • The folded porous (FP) flow field improves the mass transfer capacity. • The current density of PEMFC based on FP6-7 flow field was increased by 44.9%. • The mass fraction difference coefficient (CV Mi) was used to evaluate the uniformity of water-air distribution in the flow field. • The absolute vortex flux (J ABS n ) is used for the first time to evaluate the mass transfer characteristics. • The relationship between the flow characteristics of components and the mass transfer capacity in the flow field is revealed. [ABSTRACT FROM AUTHOR]

Oxygen starvation in proton exchange membrane fuel cells (PEMFCs) could lead to uneven internal current distribution, which is unfavorable to the fuel cell performance and lifetime. As oxygen starvation could occur locally, investigating the internal dynamic characteristics of PEMFC is critical to understanding the performance degradation mechanism. In this paper, the self-designed segmented cell of 396 segments is used to measure the dynamic current distributions of the automotive PEMFC with active area of 406 cm2 during oxygen starvation operation by decreasing air flow rate. As the air stoichiometry decreases from 2.4 to 0.8, the cell voltage drops gradually to 0.005 V and the internal current distribution becomes extremely nonuniform. The local current density increases to 1.64 A/cm2 at the air inlet and decreases to 0.25 A/cm2 at air outlet under the load current density of 0.6 A/cm2, which is dominated by the localized oxygen starvation around air outlet. When air flow rate is decreased to 0, the cell voltage reverses with a negative value of −0.042 V and the current distribution uniformity recovers. Under the negative cell voltage condition without air supply, the current distribution is determined by the membrane water content rather than the oxygen concentration. It is also found that larger step variation of air flow rate leads to a more significant overshoot of local current at air inlet and undershoot at air outlet. The different mechanisms for the internal current evolution of PEMFC is analyzed under Rich-Oxygen, Lack-Oxygen and No-Oxygen conditions, which are beneficial to improve air supply control strategy and the fuel cell design. • Dynamic internal performance of PEMFC under oxygen starvation is studied. • Segmented cell with 396 segments is used to measure the dynamic current distributions. • Uneven oxygen distribution worsens the uniformity of the current distribution significantly. • Under No-Oxygen condition cell voltage reverses with recovered internal current uniformity. • Step variation of air flow rate leads to overshoot and undershoot of local currents. [ABSTRACT FROM AUTHOR]

Accurate and swift estimation of the future performance degradation of Proton Exchange Membrane Fuel Cells (PEMFCs) is crucial for the health management of PEMFC. However, most existing studies primarily concentrate on uncovering the inherent patterns of performance degradation parameters, neglecting the fundamental relationships and pattern variations between performance degradation and other characteristic parameters (such as flow rate, temperature, and pressure). This paper seeks to address this research gap. To that end, we delve into feature parameters, extracting underlying patterns of feature evolution to construct a feature exploration-based framework for predicting PEMFC performance degradation. Initially, Time-Varying Filtered Empirical Mode Decomposition (TVF-EMD) is employed to decompose each feature variable, isolating the core information of the features. Furthermore, to reduce the computational burden caused by redundant features, Uniform Manifold Approximation and Projection (UMAP) is used to perform dimensionality reduction on the decomposed feature subsequences, ensuring the efficiency and representativeness of the extracted features. Finally, to overcome the shortcomings of long short-term memory networks (LSTM) in terms of convergence and the effective use of time series information, we introduce an innovative Mogrifier LSTM (M-LSTM) model to enhance the accuracy of PEMFC performance degradation predictions. The experimental and validation results demonstrate that the extraction of feature parameters significantly enhances the predictive precision of the baseline model. Relative to the compared models, there was an improvement of at least 16.859% in Root Mean Square Error (RMSE), a minimum increase of 23.333% in Mean Absolute Error (MAE), and a boost of no less than 0.913% in the coefficient of determination (R 2 ). Simultaneously, the proposed predictive framework demonstrates good stability and accuracy in predicting PEMFC performance degradation. • Developed a novel feature processing framework for predicting the performance degradation of PEMFC. • Employed TVF-EMD in conjunction with UMAP to extract evolving trends and cyclical patterns of feature parameters. • Introduced an innovative M-LSTM network to enhance the interaction between historical information and current inputs. • Feature processing framework improves single-model performance degradation predictions [ABSTRACT FROM AUTHOR]

The growing use of hydrogen as an energy carrier in the context of a renewed energy landscape is showing very promising potential. Most notably, polymer electrolyte membrane fuel cells (PEMFCs) are at the heart of the energy revolution and provide an efficient alternative to fossil fuels. The need for accurate modeling to analyze and develop the performance of PEMFCs has prompted many researchers to make major efforts in this area. This paper proposes a new approach based on an enhanced version of the bio-inspired metaheuristic salp swarm algorithm (ESSA) to identify the unknown parameters of the PEMFC model. This innovative approach was implemented by the combination of the merits of four approaches, namely the opposition-based learning, the new category of salps, referred to as exploration salps, the crossover and mutation operators, and the survival of the fittest mechanism. The newly introduced mechanisms succeed to overcome the problem of low population diversity of the SSA algorithm, accelerate its speed of convergence, strengthen the salp exploration capabilities, and improve its convergence accuracy. The performance of this technique has been tested and validated experimentally on the voltage–current characteristic on two commercial PEMFC stacks, such as 250 W and BCS500 W. The found results are compared to those of the original SSA and six recently published competitive metaheuristic algorithms simulated in various conditions as well as nine other well-cited methods from the literature. The performance comparison involved the calculation of the sum of squared errors (SSE), Standard Deviation (STD), computational speed, and statistical measurements. In this context, the best SSE and STD values obtained for Case I range 2 were 0.60132 and 1.0597 E − 14 , while those of Case II were 0.01167 and 1.1127E−15, respectively. Based on the results, the ESSA-based approach demonstrates superior performance in determining PEMFC parameters from experimental measurements, offering enhanced stability, faster convergence speed, and greater accuracy. This method thus emerges as a highly promising avenue for PEMFC parameter estimation, providing a valuable tool for optimizing fuel cell performance and design. • Modeling and parameter extraction methods for PEMFC models are investigated. • A new ESSA is proposed to tackle the parameterization problem of PEMFC. • ESSA uses OBL, exploration salps, crossover and mutation operators, and survival of the fittest mechanism. • Experimental tests show ESSA's best accuracy, convergence speed, and stability for 250 W and BCS500 W PEMFC. • ESSA is useful to develop precise simulators, and master PEMFC design and control. [ABSTRACT FROM AUTHOR]

Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system. • HMS methods for FC diagnosis are introduced and classified into three main categories. • New scheme is introduced categorising HMS methods by approach and characteristics. • Matrix evaluation is introduced rating HMS methods for individual FC application. • Method properties affect classification results requiring evaluation for each use case. • For FCs, feature extraction, reduction and fault classification methods are chosen. [ABSTRACT FROM AUTHOR]

Due to the coupling of multiple physical fields inside proton exchange membrane fuel cell (PEMFC) and the complex and changeable external application scenarios, the faults of PEMFC system greatly affects its engineering application. The paper proposes an ensemble learning-based fault diagnosis method for PEMFC systems, utilizing five distinct algorithms to develop an integrated ensemble classifier for fault detection. The original sample dataset collected from fuel cells undergoes a process of deep feature extraction to obtain a composite feature sample dataset, which is then inputted into an ensemble classifier to establish a fault diagnosis model. The experimental data of four kinds of faults of 80 W fuel cell test bench, EC fuel cell system and 50 W water-cooled fuel cell test bench are analyzed by using this classification model. The results show that the accuracy and generalization of the ensemble learning algorithm for different fault diagnosis of PEMFC system in different application environments are verified. • Adopt multiple classification algorithms for fault modeling and diagnosis. • Good applicability to different faults is shown in different test scenarios. • Compared with a single algorithm, it has higher fault identification accuracy. [ABSTRACT FROM AUTHOR]

Fuel cell behavior is characterized by important electric and kinetic parameters such as charge transfer coefficient, exchange current density and ohmic resistance. The quantitative estimate of these parameters by a semi-empirical approach without resorting to the sophisticated and costly methods like AC Impedance spectroscopy is presented in this paper. A fuel cell model that describes voltage-current density behavior is utilized to acquire the fuel cell parameters by using two different kinds of fitting procedures. A set of equations suitable for fitting various regions of voltage-current density variation are proposed and the criteria used to assess the quality of fit is uniformly applied to all the fitting procedures. The importance of leakage current as a parameter is also discussed by presenting improved form of fuel cell model. The model is fitted on the DC Impedance (Polarization) curve experimental data obtained for liquid feed passive Direct Methanol Fuel Cell (DMFC) at different methanol feed concentration and the operating torque. After establishing the applicability of the model and the proposed fitting procedure, a detailed sensitivity analysis is conducted to demonstrate the reliability of the model. The sensitivity analysis, along with an independent parameter sensitivity method is used to study the impact of individual model parameters on fitting criteria. The results showed higher sensitivity ratio (SR) for the model equation as compared to the sensitivity analysis for a given assumed value of charge transfer coefficient. Also, the fitted curve on experimental data shows nearly same Sum of Squared Residue (SSR) for two kinds of fitting procedures. The 95% confidence intervals for all the fuel cell parameters were presented and analyzed. The ohmic resistance and exchange current density obtained by improved form of model equation were validated by the experimental data in the literature. The deviation and dispersion behavior of important parameters of charge transfer coefficient and ohmic resistance are thoroughly studied for various kinds of variation types, percentage of points and the type of method. Finally, the trends of the sensitivity factor based on the value of model parameter were analyzed. The importance of the present model in obtaining valuable information regarding the fuel cell behavior under different operating conditions is presented. [Display omitted] • A simple semi-empirical method for estimation of kinetic and electric parameters of the fuel cell is developed. • Normal equations and well-defined objective function have been used for fitting. • Experimental I–V curve is used for fitting and EIS-ohmic resistance is utilized for validation. • Sensitivity analysis accompanied with parameter sensitivity method are used to establish the validity of the model and fitting procedure. • Estimation of important fuel cell parameters without resort to sophisticated AC Impedance techniques is a novel feature. [ABSTRACT FROM AUTHOR]

Timely and effective fault diagnosis is crucial to guarantee the reliability and durability of proton exchange membrane fuel cell (PEMFC). Segmented cell technology has been proven to be a powerful tool for exploring the internal characteristics of fuel cells, yet it is seldom applied for fault diagnosis. This paper proposes a data-driven fault diagnosis method that combines segmented cell and deep learning technology for PEMFC water management fault diagnosis. The dynamic characteristics of the current distribution of the fuel cell under different levels of faults are explored with segmented cell technology. A dual-input convolutional neural network is applied to combine current distribution data and sensor data for a more comprehensive system status for fault diagnosis. The results show that the model can efficiently identify flooding and drying faults with more than 98.5% accuracy, faster and more accurately than other algorithms. This work highlights the significance of segmented cell technology for the comprehension of water management inside PEMFC and provides a new concept for PEMFC fault diagnosis. [Display omitted] • The segmented cell technology is applied to investigate the current distribution during flooding and drying process. • A dual-input CNN is adopted to establish a fault diagnosis model for PEMFC water management. • The proposed method exhibits excellent diagnostic performance, with an accuracy rate of over 98.5%. [ABSTRACT FROM AUTHOR]

The Proton Exchange Membrane Fuel Cell - Mechanical Heat Pump - Combined Heat and Power (PEMFC-MHP-CHP) system is a reliable energy supply solution, which can operate independently of the grid during emergencies or be used for peak shaving and load leveling in renewable energy networks. This paper proposes two system structures, namely the separated and integrated systems and establishes MATLAB/Simulink models. Then, a sensitivity analysis is conducted, examining system design and operation. The results show that the separated system can satisfy basic heating and electricity demands without an external power supply at −14.5 °C. Increasing the number of cells by 20, reducing one room's heat load (36 m2), or increasing the current density by 0.1 A/cm2 results in reductions in compressor power consumption ranging from 1.76 % to 2.91 %, 7.42 %–10.57 %, and 6.52 %–16.88 %, respectively. On the other hand, the integrated system has higher power consumption but can operate smoothly at lower temperatures than the separated system. It is suitable for integration with auxiliary power devices in low-temperature environments. The PEMFC's heat output minimally affects system efficiency. Reducing the number of rooms improves system performance, with each reduction of one room decreasing compressor power consumption by 5.43 %–8.55 %. Meanwhile, two design options are identified based on the power supply and hot water demands. Further research and development can enhance the efficiency and performance of these systems, promoting their wider use in the future. • Established MATLAB/Simulink models for the PEMFC-MHP-CHP system. • Demonstrated better performance and stable heating capacity compared to conventional CHP systems. • Provided insights into advantages and limitations of separated and integrated systems. • Conducted a thorough performance analysis under load fluctuations for energy supply and peak shaving. • Proposed system design and operational options based on sensitivity analysis. [ABSTRACT FROM AUTHOR]

CO and H 2 S poisoning of Pt-based catalysts for hydrogen oxidation reaction (HOR) stands as one of the long-standing hindrances to the widespread commercialization of proton exchange membrane fuel cells. In this paper, a Ru/Ti 4 O 7 catalyst is successfully synthesized by the microwave-thermal method. This Ru/Ti 4 O 7 catalyst shows a much higher noble metal mass activity than those of commercial PtRu/C and conventional Ru/C catalysts. The performance of the Ru/Ti 4 O 7 catalyst under the exist of CO or H 2 S shows insignificant current decay, which is far superior to commercial PtRu/C and Pt/C catalysts. In this Ru/Ti 4 O 7 catalyst, the electron transfer between Ru and Ti to form d-p orbital hybridization is considered to be responsible for the favorable catalytic HOR performance and the corresponding CO and H 2 S tolerance. The interaction mechanism formed by electron transfer may open a promising way for the subsequent development of anti-poisoning catalysts for PEM fuel cell hydrogen oxidation reaction. [Display omitted] • Ru/Ti 4 O 7 catalyst shows a superior noble metal mass activity than those of commercial Pt–Ru/C based catalysts. • Ru/Ti 4 O 7 catalyst exhibits excellent resistance to CO poisoning. • The catalyst is extremely resistant to H 2 S while remaining CO-tolerant. • MSI of Ru/Ti 4 O 7 ensures catalytic activity and anti-poisoning properties. [ABSTRACT FROM AUTHOR]

This paper provides a cost-effective energy management method for the microgrid's standalone and on-grid operational modes. The considered microgrid based on Green-to-Green systems such as a photovoltaic array (PV), wind turbine (WT) as renewable generators, hydrogen fuel cell (FC) system, microturbine (MT), and battery storage system. The suggested technique is based on the marine predator algorithm (MPA) that and created for a scheduling horizon of one day. The main objective of this paper is to reduce operating costs while satisfying the demand power. To approve the performance of the suggested management strategy, the simulation results are compared with other recent optimization algorithms. These algorithms include particle swarm optimization (PSO), salp swarm algorithm (SSA), and coot optimization algorithm (COOT). To approve the performance of the proposed EMS, the system will be evaluated for three cases: free renewable generation, restricted generation mode, and unlimited main grid power mode. For the first case, the proposed EMS reduces the operating costs by 0.8732%. For case 2, the economic benefits have been raised by 1.0815% and by 0% for the last case because of the reduced problem complexity. • A cost-effective energy management strategy for the microgrid based PEM fuel cells is proposed. • Implementation of marine predator algorithm to minimize the operating costs. • The performance has been investigated under various operating conditions. [ABSTRACT FROM AUTHOR]

The plateau environmental adaptability of the proton exchange membrane fuel cell (PEMFC) is a key technical challenge for the development of fuel cells (FCs). This paper reviews the current research on the adaptability of FCs in plateau environments, focusing on the application requirements of automotive FCs in high-cold and high-altitude areas. First, the paper investigates how low temperature and low pressure affect the internal structure and output performance of FCs in plateau environments. Second, it analyzes the recent advances in FC technology to cope with plateau environments and evaluates the technical advantages and disadvantages of various approaches based on essential indicators such as FC output performance, efficiency, and response time. Finally, it identifies future research directions in FC plateau environmental adaptability technology, aiming to provide a reference for using FCs in plateau environments. • Reviewed the development status of plateau environmental adaptation technology for fuel cells. • Analyzes the advantages and disadvantages of various cold start solutions. • The advantages and disadvantages of altitude adaptation technology are analyzed. • Suggests the future research focus of fuel cell plateau environmental adaptation technology. [ABSTRACT FROM AUTHOR]

The control of Proton Exchange Membrane Fuel Cell (PEMFC) is exceptionally challenging due to its complex nonlinearity, slow dynamics and load disturbance. In this paper, an Adaptive Model Free Control (AMFC) approach is introduced for regulating the PEMFC output voltage under load perturbation and measurement noise conditions. The proposed method consists of four sub-elements. Firstly, an Extended State Observer (ESO) based on a Single-Input Interval Type-2 Fuzzy intelligent PI (SI-IT-2-FLC-iPI) scheme is designed to enhance the performance of PEMFC. Secondly, a Nonlinear Sliding Mode Control-based Super Twisting Algorithm (NSMC-STA) is used as an auxiliary control approach to reduce the estimation error and ameliorate the system robustness. Thirdly, a Forgotten Recursive Least Square Error (FRLSE) is applied for adjusting the physical parameter of MFC and further ameliorating the control response. Finally, all these elements are merged together within what it is called Ultra Local Model (ULM). Through extensive simulation, the efficacy of the proposed regulator in accurately tracking the output signal is showcased, outperforming conventional controllers with remarkable improvements. The system achieves 0.001 steady-state error, 0% overshoot and settling time of approximately 8.9 s, which is good enough in the context of standalone fuel cell applications. • An intelligent Model Free Control structure is developed for tracking the output voltage of PEMFC. • Integrating FLC type-2 PI, NSMC-STA, ESO and online tuner based FRLSE within ULM. • The finite stability is fully demonstrated using Lyapunov theorems. • The proposed control enhances the performance of PEMFC under various operating conditions. [ABSTRACT FROM AUTHOR]

The ejector-driven hydrogen recirculation system plays an important role in enhancing efficiency of the PEM fuel cell. It's necessary to have deep knowledge of dynamic characteristic of the ejector for optimizing system state, but until now related research is not adequate. In this paper, dynamic characteristic of the ejector for the hydrogen recirculation system of the PEM fuel cell is studied using active periodic pressure excitation. Test plant is set up and active periodic pressure excitation with small amplitude is superimposed on steady pressure at the ejector primary flow inlet. Experiment result shows that in frequency domain, amplitude ratio of dynamic pressure at primary flow inlet to the dynamic delta-pressure, equal to pressure at mixing outlet minus that at backflow inlet, is independent of excitation frequency for each steady operating point. In the complex coordinate, vector of dynamic pressure at primary flow inlet is in parallel with that of dynamic delta-pressure, for all frequencies and for all stable operating points. Furthermore, amplitude ratio of dynamic pressure at primary flow inlet to dynamic delta-pressure exhibits linearity with entrainment ratio of the ejector for all stable operating points. Experiment on the 120 kW fuel cell system validates the same dynamic characteristic. • Dynamic characteristic of ejector studied using active periodic pressure excitation. • Ratio of dynamic primary-flow pressure to delta pressure independent of frequency. • Vector of primary-flow pressure in parallel with that of the dynamic delta-pressure. • Ratio of primary-flow pressure to delta pressure in linearity with entrainment ratio. [ABSTRACT FROM AUTHOR]

This paper presents a novel off-grid hybrid renewable energy system integrated with hydrogen production and retired electric vehicle (EV) batteries for combined power and heat supply to a small rural community. The system consists of photovoltaic (PV) panels, evacuated tube solar collectors, a proton exchange membrane fuel cell (PEMFC), an alkaline electrolyzer, compressed hydrogen storage tanks, and reused lithium-ion batteries from EVs. A new battery model is developed in the Transient System Simulation Program (TRNSYS) to capture the capacity degradation of retired batteries. A two-stage energy management strategy is proposed to regulate power flow and maximize solar energy utilization. The system is optimized for minimum power supply disruption, hot water supply disruption, energy waste, and annualized costs over a 20-year lifetime using a multi-objective NSGA-II algorithm coupling MATLAB and TRNSYS. Optimization results reveal tradeoffs between the competing objectives. Dynamic simulations show the water tank temperature fluctuates between 20 and 100 °C with mean values dropping slightly in later years due to battery degradation. Energy waste from components rises in later years for the same reason. The replacement interval for a retired EV battery module is around 2.5 years. The integrated system proves feasible for off-grid combined power and heat supply using solar energy and retired EV batteries as storage, though battery degradation impacts long-term performance. • Integrates solar, hydrogen, retired EV battery for off-grid power and heat supply with optimized storage and backup. • Utilizes multi-objective optimization to balance system reliability, waste minimization, and costs through Pareto solutions. • Implements long-term performance over twenty years to provide insights into component lifetimes and replacement needs. [ABSTRACT FROM AUTHOR]

Enhancing the chemical durability of perfluorosulfonic acid (PFSA) membranes is important in developing proton exchange membrane fuel cells (PEMFCs). In this paper, a novel expanded polytetrafluoroethylene (ePTFE) reinforced PFSA membrane with nature organic naringin (NAR) as radical scavenger (PFSA@ePTFE/NAR) was prepared by a simple solution-cast method. NAR exhibited an excellent radical scavenging ability and does not influence the original PFSA structure. A comparison between NAR and Ce3+ showed that NAR had higher free radical scavenging ability. PFSA@ePTFE/NAR shows high proton conductivity of 153.1 mS cm−1 in water at 80 °C, high tensile strength of 50.5 MPa, and good output single cell performance. The addition of 1 wt% NAR significantly reduced the fluoride ion release rate of the membrane by 81% after the 96 h Fenton's test, and prolonged the lifetime of the membrane in cell as demonstrated by single-cell tests and open-circuit voltage tests. [Display omitted] • A novel ePTFE reinforced PFSA membrane with nature organic naringin (NAR) as radical scavenger was prepared. • PFSA@ePTFE/NAR shows high proton conductivity, high tensile strength, and good output single cell performance. • 1 wt% NAR significantly reduced the fluoride ion release rate and prolonged the lifetime of the membrane in cell. [ABSTRACT FROM AUTHOR]

In this paper, the mechanism of proton exchange membrane fuel cell (PEMFC) cathode cycling is discussed and the high potential suppression control problem for fuel cell vehicles is investigated by using cathode cycling. Firstly, a rigorous single-cell experimental investigation is performed to reveal the impact mechanism of cathode recirculation on the internal polarization processes of PEMFC. Results show that an increase in the recirculation ratio leads to an increase in the polarization impedance in the low and medium frequency regions but decreases the ohmic impedance. Consequently, when the recirculation ratio increases to 1, the voltage drop rates are 2.2%, 3%, 4.6%, 5.8%, and 7% as the current density varies from 0 to 0.2 A/cm2, respectively, and the ohmic impedance decreases by 28.1%. On the basis, the optimal control scheme for high potential suppression based on cathode circulation in vehicular PEMFC system is proposed. The performance comparison of different control method is carried out on a software-in-the-loop testing platform. The results show that, for the same control objective, the model predictive control (T-S MPC) method is 55.5% and 16.7% lower than the proportional integral (PI) controller and the Takagi-Sugeno linear quadratic Gaussian (T-S LQG) in terms of controller input cost. On the contrary, the cumulative error of voltage tracking is reduced by 62% and 30.4% and the voltage response against disturbances is improved by 9.7% and 42.8%. Overall, the T-S MPC achieves the optimal control effect with less control effort. • An insight into the mechanism of cathode recirculation affecting PEMFC performance. • Cathode recirculation reduces ORR reaction rate and oxygen diffusion rate. • The T-S MPC provides optimal closed-loop control of high potential suppression. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell (PEMFC) is a highly promising renewable energy conversion technology. However, durability issues have hindered their large-scale commercialization process. Performance degradation prediction is an essential component of PEMFC prognostics and health management and is critical for extending the service life of fuel cell. Given that, this paper proposes a novel data-driven prediction model that fuses multi-head self-attention (MHSA) mechanism and bi-directional long short-term memory (BiLSTM). This model can effectively capture different types of dependencies from large-scale high-dimensional data and achieve global information modeling. Specifically, the preprocessed historical voltage data and PEMFC system operating parameters are fed into the proposed prediction model. Where BiLSTM understands the contextual information and temporal dependencies in sequence data by calculating the hidden states in both forward and backward directions. MHSA captures the complex relationships and extracts key information in the input sequence by simultaneously learning multiple sets of attention weights between different locations. Finally, the proposed model is validated based on the health monitoring data under stationary and quasi-dynamic conditions. The validation results indicate that the proposed model can ensure absolute errors of less than 0.6 × 10−3 V for at least 71.9% of the prediction results under stationary and quasi-dynamic conditions (less than 1.2 × 10−3 V for at least 97.6% of prediction results). • A prediction model fusing BiLSTM network and MHSA mechanism is proposed. • MHSA mechanism is used to further extract the key information form the sequence. • Considered the impact of different dimensions of health monitoring data on PEMFC. • Quantified the potential of the MHSA mechanism in improving predictive accuracy. • The proposed model achieves accurate predictions under different current conditions. [ABSTRACT FROM AUTHOR]

To address the limitations of battery-powered unmanned surface vehicles (USVs) in terms of endurance mileage, this study introduces proton exchange membrane fuel cells (PEMFCs) into the power system of USVs. This paper focuses on the design and testing of a hybrid power system and its energy management strategy for a lightweight USV. The test results demonstrate that the hybrid power system effectively fulfills the power requirements of the USV across various operational conditions. Specifically, the amplitudes of bus voltage overshoot and undershoot remain below 0.31 V even during sudden changes in working conditions. The energy management strategy, in conjunction with an auxiliary battery, successfully limits the PEMFC power fluctuation to 200 W/s, thereby enhancing the lifespan of the PEMFC. Moreover, the study reveals that replacing Li-ion batteries with the PEMFC system as the primary power source can significantly enhance the USV's endurance mileage by 1.33–1.70 times carrying the same weight and 1.07–1.36 times carrying the same volume, respectively. And with increased hydrogen storage, the PEMFC system's energy density advantage over Li-ion batteries becomes more pronounced. These findings contribute to the exploration of PEMFCs as a promising solution for addressing the endurance limitations of battery-powered USVs, leading to their improved performance and extended operational range. • A whole vessel model including electrical, dynamic and control system is established. • A strategy based on bus voltage and PEMFC operating stability is proposed. • The energy management strategy has good adaptability to operating conditions. • Replacing Li-ion batteries with PEMFCs effectively increases the range of USVs. [ABSTRACT FROM AUTHOR]

Graded cathode catalyst layer (CCL) design can improve performance and reduce the cost of proton exchange membrane fuel cells (PEMFCs). However, it sacrifices the uniformity of oxygen concentration, thereby shortening the duration of PEMFC. Thus, this paper introduces a many-objective optimization algorithm called the Non-dominated sorting genetic algorithm-third version (NSGA-III) to optimize the performance, oxygen distribution quality, and cost of PEMFC with a graded CCL structure via four evaluation indexes. The four evaluation indexes include the new proposed local oxygen transport resistance and the uniformity of oxygen concentration at the Pt surface. Furthermore, artificial intelligence (AI) based models are established to enhance the optimization efficiency. Then, the NSGA-III algorithm is used to optimize the graded CCL structure parameters and operating voltage to find the Pareto solutions. Moreover, two optimization strategies are proposed to improve the power density and uniformity of oxygen concentration of PEMFC or to save the precious Pt and ionomer while maintaining the performance. Lastly, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to select the optimal solution for each strategy. Results show that the AI-based models have enough predicting abilities, and the selected optimal solutions can satisfy the goals of the corresponding strategy, which provides efficient ways to develop high-performance, long-lifetime, or low-cost, long-lifespan PEMFCs. • NSGA-III is used to optimize performance, oxygen distribution, and cost of PEMFC. • Two new evaluation indexes are proposed to optimize PEMFC with graded CCL design. • AI-based models for PEMFC are established to enhance optimization efficiency. • High-performance, long-lifetime PEMFC is obtained via many-objective optimization. • Low-cost, long-lifespan PEMFC is developed via many-objective optimization. [ABSTRACT FROM AUTHOR]

Membrane electrode assemblies (MEAs) have been subjected to alternating hygrothermal conditions, and frequent load changes significantly reduces the proton exchange membrane fuel cells (PEMFCs) lifetime. PEMs with a reinforced layer of e-PTFE have gained widespread application with the PEMFC development. However, the fatigue mechanism beyond the glass transition temperature remains to be elucidated. In this study, two accelerated stress tests (AMFT-85 and AMFT-95) are designed to investigate the PEM response to humidity under varying operating temperatures. In-situ fatigue experiments are conducted to comprehensively examine the fatigue mechanism of MEAs through the integration of electrochemical property characterization, mechanical property evaluation, and surface morphology analysis. The polarization curve results indicate that the AMFT-95 condition accelerates output performance degradation. The catalyzer-coated membrane displays a diminishing trend regarding of final strain, ultimate tensile strength, fracture toughness, and glass transition temperature due to the formation of cracks and delamination induced by cyclic stresses during physical fatigue. This decreasing trend becomes more pronounced with higher operating temperatures. Furthermore, elevated temperatures decreased the viscoelastic properties of the membranes, rendering catalyzer-coated membranes more susceptible to creep-fatigue failure and microstructural damage. This study proposes an experimental approach to enhance the understanding of physical fatigue in PEMs, contributing to mitigate fatigue failure and enhance PEMFC service life. • These paper focus on the temperature on CCM mechanical degradation mechanism. • The results confirm the relationship between temperature and cracks. • Elevated temperature degraded CCMs have lower glass transition temperatures. • Mechanical degradation is more severe above glass transition temperature. [ABSTRACT FROM AUTHOR]

One of the effective strategies to pursue the highly durable high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) is to introduce inorganic fillers to the phosphoric acid-doped polybenzimidazole (PA/PBI) membranes. Among the inorganic fillers, phosphates such as phosphosilicate are effective in mitigating acid loss at elevated temperatures (200–300 °C). In this paper, the effect of in situ formed phosphosilicate on the performance and stability of SiO 2 /PA/PBI composite membranes is studied in detail. The mechanical properties and electrochemical performances of the in situ formed SiO 2 /PA/PBI membranes depend strongly on the content of in situ formed Si 5 P 6 O 25 fillers and its distribution and microstructure in the membrane. Such in situ formed SiO 2 /PA/PBI composite membranes show a high conductivity of 53.5 mS cm−1 at 220 °C. The assembled single cell shows a maximum peak power density (PPD) of 530.6 mW cm−2 and excellent stability at elevated temperature of 220 °C for over 130 h. The exceptional stability at 220 °C is most likely due to the existence of predominant amorphous phosphosilicate phases in the in situ formed SiO 2 /PA/PBI composite membranes, which inhibits the evaporation and leaching of PA at elevated temperatures. The results indicate the practical application of in situ formed SiO 2 /PA/PBI composite membranes for HT-PEMFCs. • In situ formation of predominantly amorphous phosphosilicate phases in SiO 2 /PA/PBI composite membranes. • The as-synthesized SiO 2 /PA/PBI membrane based PEMFCs can operate at elevated high temperatures of 200–250 °C. • The composite membranes based PEMFCs show high performance and excellent stability at 220 °C. • The in situ formed predominantly amorphous phosphosilicate phases can effectively contain PA at high temperatures. [ABSTRACT FROM AUTHOR]

At high current density, the mass transfer in proton exchange membrane fuel cells (PEMFC) is significantly influenced by the flow field structure. In this paper, a bilateral track flow field (BTFF) is proposed to improve the transverse and longitudinal mass transfer as well as the water removal capacity of PEMFC. The geometry of the BTFF is optimized by orthogonal tests to obtain the optimal combination of geometric parameters and levels. Then using numerical modeling, the impact of the optimized BTFF (BT6) on the efficiency of the PEMFC was examined. The results show that BT6 significantly improves the utilization of the under-rib region by shortening the reactive gas diffusion path length to obtain a more uniform oxygen distribution, and the average oxygen concentration in the midline of the under-rib of the BT6 is increased by 102.60%, furthermore, the current density is increased by 16.32% compared with that of the parallel flow field (case0). In addition, by reducing the cross-sectional area of the gas flow channel, the BT6 has a higher gas flow velocity, which accelerates the removal of cathode liquid water, and the average liquid water saturation in the midline of the under-rib of the BT6 is reduced by 15.26% compared with case0. Finally, by analyzing the net power density of PEMFC, it can be found that the net power density of BT6 is increased by 15.68% compared with case0, which has good practical application value. • A novel bilateral track flow field is proposed and optimized by orthogonal test. • Locally improved structure enhances transverse and longitudinal mass transfer. • The average oxygen concentration under-rib of the optimized flow field has increased by 102.60%. • The optimized flow field net power density has increased by 15.68%. [ABSTRACT FROM AUTHOR]

The microchannels on the bipolar plates (BPPs) of a proton exchange membrane fuel cell (PEMFC) have various functions. Increasing the microchannel depth leads to an increase in the efficiency of the fuel cell. In this paper, metallic BPPs of the PEMFC made of commercial pure titanium (CP-Ti) with an initial thickness of 0.1 mm are manufactured using the stamping process. First, after performing the process using experimental tests and finite elements (FE) simulation, the accuracy of the numerical results is confirmed. In the following, using the FE model and considering process parameters including die clearance, forming speed, and sheet/die friction coefficient, a set of experiments is implemented using the response surface method (RSM). The results of the filling rate are obtained from the experiments and a regression model is established to predict the filling rate of the microchannel. Then, four meta-heuristics methods including artificial bee colony optimization (ABCO), genetic algorithm (GA), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are used to estimate the formability of the CP-Ti BPPs. According to the results, the ANFIS model with an error of 0.0062 × 10−3 % compared to experiments is more reliable to predict the filling rate in the stamping of the CP-Ti BPPs. • The titanium bipolar plates for proton exchange membrane fuel cells are manufactured using stamping. • Effect of clearance, forming speed, and friction coefficient on the maximum filling rate of the stamped plates investigated. • Meta-heuristics methods are applied to estimate the formability of the stamped bipolar plates in terms of filling rate. [ABSTRACT FROM AUTHOR]

This paper proposes a performance degradation model based on empirical approaches, which can break down the power loss and quantify the influence of each aging phenomena from the overall performance degradation. With the presence of primary degradation mechanisms, the approach can be used to analyze the performance degradation of fuel cells under different degradation conditions. The aging parameters that represent hydrogen crossover, membrane resistance increase, and electrochemical active surface area (ECSA) loss are introduced to characterize the performance degradation. Based on the polarization behavior of proton exchange membrane fuel cells (PEMFCs), the variations of degradation stressors are determinated by fitting the aging parameters to the measuring polarization curves. The empirical approach is validated by a 150 h durability experiment and agrees well with all polarization curves. The results show that ECSA loss always maintains an apparent influence and hydrogen crossover accounts for 56% of the performance degradation in OCV. • An empirical approach is developed to analyze the durability of PEMFC. • The integrated effects of degradation stressors are considered. • Variations of degradation stressors during dynamic cycles are studied. • Voltage degradation due to various aging mechanisms is investigated. [ABSTRACT FROM AUTHOR]

Oxygen stoichiometry (OS) and stack temperature (ST) significantly affect the output performance and durability of proton exchange membrane fuel cells. This paper investigates the prescribed performance tracking control strategy of OS and ST under external disturbances, modeling errors, actuators faults and limited communication resources. The total disturbances are compensated by a variable-bandwidth extended state observer to simplify the control design and enhance the system robustness. To tolerate excessive disturbances and relax the strict requirement on the initial conditions, a new event-triggered adaptive sliding mode controller that integrates modified dynamic performance constraints and nonsingular error transformation is developed to ensure the user-designed transient and steady-state performance constraints, while saving the communication costs and avoiding the chattering and jump in control signals. The numerical validation results under combined working scenarios indicate that the proposed controller always ensures the preset error constraints and possesses superior performance in tracking the optimal OS value 2 and the optimal ST value 353.15K than other three representative controllers, with the integral absolute errors of 0.732 for OS tracking and 12.94 for ST tracking; besides, it achieves satisfactory robustness to uncertain model parameters and relatively large initial tracking errors. [Display omitted] • A robust event-triggered prescribed performance controller for PEM fuel cell systems. • Oxygen stoichiometry (OS) and stack temperature (ST) are simultaneously controlled. • Integral absolute errors when tracking OS and ST are 0.732 and 12.94 respectively. • A better compromise between control performance and communication cost. • The chattering and jump phenomena in control signals are suppressed. [ABSTRACT FROM AUTHOR]

The world is still largely dependent on oil and natural gas for its energy requirements which are harmful to the environment; therefore, it is high time that we look for alternative technologies for our growing energy needs. One such emerging area is fuel cell technology which produces clean energy in the form of electrical power. Integrating a Metal Hydride Hydrogen Storage (MHHS) system with a fuel cell can help increase energy efficiency. The heat dissipated during hydrogen absorption in MHHS can be used in other applications. In this paper, energy and exergy analysis of a fuel cell-based integrated system is performed. The system presents a Reversible Proton Exchange Membrane Fuel Cell capable of working in dual modes, i.e., as an Electrolyser as well as a fuel cell. The MHHS and Vapour Absorption Refrigeration System (VARS) are coupled with a reversible fuel cell for hydrogen storage and cooling applications, respectively. While working in the fuel cell mode, maximum efficiency of 47.84% is evaluated at 80 °C. The system efficiency with and without the VARS system at 80 °C was 73.29% and 47.84%, respectively. On the contrary, in the electrolyzer mode, the maximum efficiency comes out to be 85.65%. The use of the MHHS system for hydrogen storage results in excess heat release, and as a result, the overall efficiency of the electrolyzer was increased to 94.05%. • Thermodynamic integration of PEMFC with MHHS and VARS is performed. • Effect of key parameters on fuel cell system performance is investigated. • System energy and exergy efficiency of 73.3% and 59.5% respectively are reported. • The proposed system can achieve maximum electrolyzer efficiency of 85.65%. • Maximum cooling output from vapour absorption system is found to be 60.56 kW. [ABSTRACT FROM AUTHOR]

Polymer-carbon composite bipolar plates (PCCBP) are accepted over graphite bipolar plates (BP) for their use in proton exchange membrane fuel cell (PEMFC), specially in hydrogen fuel cell-powered electric vehicles. This study developed a novel copper fiber-filled PCCBP with epoxy resin as the binder and natural flake graphite (NFG), carbon black (CB), and Cu fiber as filler materials. The fabrication is done by compression molding. Both electrical conductivity and flexural strength increased with the addition of Cu fiber. The composite BP fabricated with 8 vol % Cu fiber, 10 vol % CB, and 42 vol % NFG exhibited electrical conductivity of 169 S/cm, flexural strength of 43 MPa, thermal conductivity of 17 W m−1 K−1 and corrosion current density of 0.972 μA/cm2. The composite also showed acceptable results for contact angle, density and thermal stability tests. This research paper provides insights into further developments of the metal-based PCCBP. • Novel Cu fiber-filled composite bipolar plates were developed for PEM fuel cells. • Effect of content of epoxy resin, carbon black, and copper fiber was investigated. • Enhancement of electrical conductivity and flexural strength achieved concurrently. • Provides insights into future developments of the metal-based PCCBP. [ABSTRACT FROM AUTHOR]

Nafion membrane is a commercial type of electrolyte membrane that is widely used in low-temperature fuel cells. Nafion membrane is expensive and allows fuel to crossover from anode to cathode. Therefore, it decreases fuel utilization and results in mixed potential at the cathode. Modifying the Nafion membrane and/or replacing it with non-Nafion-based materials has shown promising results in solving these problems. Graphene is a two-dimensional material with exceptional properties that positively affect the performance of several energy conversion/storage devices. With its large surface functional groups, graphene oxide exhibits considerable ionic conductivity with low fuel crossover. This paper reviews and discusses the recent progress in utilizing graphene or its derivatives as a blend with Nafion and non-Nafion based membranes as well as a standalone membrane in low-temperature fuel cells. Graphene or its derivatives possess a high potential as a standalone membrane or a composite membrane in the various low temperature fuel cells applications in terms of high ionic conductivity at low humidity and relevant high temperature, high thermal, mechanical, and chemical stabilities. This work summarizes the recent progress in utilizing graphene and its derivatives (graphene oxide and other doped graphene) in different types of fuel cells, whether as a standalone or as a modifier of the Nafion and non-Nafion based membranes. The review covers the usage of graphene and its derivatives in PEMFCs, DMFCs, anion exchange DMFCs, and MFCs. Furthermore, it elaborates on the science and the engineering aspects of utilizing graphene and its derivatives in different fuel cells. This work demonstrates the importance of the graphene and its derivatives in improving the performance of low temperature fuel cells. • GO promoted high water retention of the fuel cell's membrane. • GO has excellent mechanical, chemical, and thermal stability, and thus its polymer blends gain these properties. • The blends of the electrolyte polymer with GO decreases the fuel crossover. • Applying of graphene as a standalone membrane in PEMFC was summarized. • The performance of Nafion-based and non Nafion-based membranes modified with graphene in fuel cells was summarized. [ABSTRACT FROM AUTHOR]

In this communication, an experimental investigation is carried out on a PEM (Proton Exchange Membrane) fuel cell. A small-scale standalone PEM fuel cell system of 1 kW capacity is demonstrated in the present study. The fuel cell is connected to the charge controller, and the charge controller is further connected to the DC and AC loads to study the fuel cell characteristics. A battery bank backup is also provided to account for the stable power output from the fuel cell. The purpose of the study is to determine the fuel cell's performance when operated with resistive, AC, and DC loads (home appliances within the rated power range). The effect of hydrogen flow rates on the power output is also presented in this paper. The DC and AC loads are connected to the fuel cell setup to study the characteristics of the fuel cell. From the study, it can be observed that the performance of the fuel cell is better at higher flow rates of hydrogen. The experimental results showed that the maximum power obtained was 986.8 W at a hydrogen supply rate of 15 LPM. The maximum fuel cell efficiency was found to be 44% at the flow rate of 8 LPM. The charge controller efficiency reported for DC and AC load connections is 94.97% and 96.98%, respectively. The inverter efficiency was observed to increase with the current value, with the maximum value reaching around 98.86%. • Experimental results of a 1 kW small scale PEM fuel cell are presented. • Study explores the effect of resistive, AC and DC loads on fuel cell performance. • Maximum PEM stack efficiency is determined to be 44%. [ABSTRACT FROM AUTHOR]

This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project. • State machine-based supervisory controller for fuel cell system is designed. • The designed control structure is implemented in a prototype hydrogen-based vehicle. • The controller comprises: State Machine, Setpoint Generator, Power Limit Calculator. • The proposed control structure handles the startup and shutdown process of PEMFC. • Minimizing stack degradation by implementing a fuel cell power limit calculator. [ABSTRACT FROM AUTHOR]

Given the current maturity of hydrogen technologies, accurate and computationally efficient numerical models are crucial for improving their understanding and development. Traditional models are either computationally prohibitive or lack the capacity to assess the spatial distribution of critical variables. The present paper suggests a hybrid numerical model for Fuel Cells (FCs) and electrolysers, articulating the coupling between a 1D analytical model and a Computational Fluid Dynamics (CFD) model via a nonlinear regression. Results present an initial validation of the 1D analytical model and the CFD model, and, once the validation is proven successful, the hybrid model is evaluated with a relatively long and highly varying loading profile that covers a wide range of the potential operational points of a FC. The hybrid model shows promising results, showing fidelity levels similar to CFD models, including the capacity to assess the spatial distribution, and a low computational cost. Hence, this hybrid model is demonstrated to be an attractive tool for the design of FCs and electrolysers, optimisation of thermal management and control strategies, degradation analysis, and techno-economic analysis. [ABSTRACT FROM AUTHOR]

In the paper, electrochemical behavior of platinum based cathode catalyst in a polymer electrolyte membrane fuel cell is studied under non-symmetric square-wave electric potential cycling applied in accelerated stress test. Following the modeling by Holby and Morgan, degradation due to Pt dissolution, ion diffusion, and oxide coverage is performed with respect to cycling operating conditions and model parameters. The computer simulation demonstrates impact of the electrochemical surface area loss rate under variation of the temperature, pH, platinum particle diameter, loading, Pt to Carbon volume fraction, and their simultaneous effect. From physical consistency and multi-parametric sensitivity analysis, a statement on feasible domain of the parameters for the PEMFC operation is concluded. • Holby–Morgan model of platinum electrochemical degradation in PEMFC is applied. • The catalyst degradation is calculated under EU FCH 2JU AST cycling protocol. • ECSA ratio loss rate is correlated with operating conditions and model parameters. • Sensitivity analysis gives feasible range of multiple variable parameters. • Temperature, pH, Pt particle diameter, loading, and Pt/C volume fraction are tested. [ABSTRACT FROM AUTHOR]

Zinc-air batteries (ZABs) and Proton exchange membrane fuel cells (PEMFCs) have attracted wide attention because of their high energy density. However, the oxygen reduction reaction (ORR) occurred at the cathode is 6 orders of magnitude lower than the oxidation reaction occurred at the anode. In recent years, atomically dispersed metal-nitrogen-carbon (M-N-C) catalyst has been widely considered as one of the most promising catalysts to replace platinum-based catalysts. However, the performance of M-N-C catalyst is much lower than that of the most advanced Pt catalysts. The key to improving the catalytic activity of M-N-C ORR catalysts is to increase the intrinsic activity of the catalyst active sites. In this paper, the active sites of atomically dispersed M-N-C ORR catalysts are introduced, and the strategies of enhancing the intrinsic activity of the active sites including heteroatom doping, construction of dual atoms sites and creation rich defects in carbon materials are systematically summarized. Finally, the opportunities and challenges of further development of atomically dispersed M-N-C catalysts are proposed. • A comprehensive overview of atomically dispersed M-N-C catalysts for ORR. • Focus on the enhancement of the intrinsic activity of the active site. • Future directions of developing advanced M-N-C catalysts for ORR are outlined. [ABSTRACT FROM AUTHOR]

This paper proposes a new type of rotary proton exchange membrane fuel cell (R-PEMFC) and its simulation model is established and verified based on experimental data. Then the effects of different rotational angular speeds (RASs) on reactant flow characteristics and electrochemical reactions are investigated. Also, the key quantitative indexes, such as average value, uniformity index and effective mass transfer coefficient (EMTC) are adopted, while combining the polarization curve and net power to estimate the comprehensive R-PEMFC performance. The results indicate that the R-PEMFC effectively ameliorates uneven distribution and improves the transmission capability and output performance. Compared with the static state (0 rpm), the EMTC and maximum power density are enhanced by 65.86 % and 8.51 % respectively at the RAS of 1080 rpm, and the net power density can reach 5316 W·m−2. • A novel rotary proton exchange membrane fuel cell is first proposed and designed. • Effects of rotational angular speed on the R-PEMFC performance are investigated. • Key quantitative indexes are adopted to evaluate the comprehensive performance. • Compare static scheme effective mass transfer coefficient raise 65.86 % at 1080 rpm. • Maximum net power density of the newly designed R-PEMFC can reach 5316 W m−2. [ABSTRACT FROM AUTHOR]

In recent years, supervised deep learning-based methods have achieved significant results in fuel cell system fault diagnosis. However, most existing deep learning-based fault prediction methods suffer from missing fault labels and data limitations due to the difficulty in obtaining fault and degradation data in real fuel cell systems. To address the above challenges, this paper proposes a fault diagnosis method based on digital twin and unsupervised domain adaptive learning. The method has two key features: First, a maximum-relevance minimum-redundancy algorithm is used to select the input signals. Then a high-order fuel cell system model is developed to obtain a large amount of digital domain fault data at low cost by simulating fault injection. Second, domain-invariant features are extracted using a domain-adaptive adversarial learning approach to reduce the distribution differences between the digital and real domains. The method successfully diagnosed nine typical faults in the fuel cell air, hydrogen, and thermal subsystems without real data fault labels. Under dynamic load conditions, the diagnostic accuracy reached 92.5 %. In addition, the method achieves a diagnostic accuracy of over 90 % under domain adversarial training using only normal real data. The experimental results show that the proposed method can achieve fuel cell system fault diagnosis without fault labels and significantly reduce the dependence on fault data. [Display omitted] • An unsupervised fault diagnosis method for PEMFC systems is proposed. • The diagnostic algorithm is investigated for nine typical faults. • The training process of diagnostic framework does not require fault labels. • The algorithm still has high accuracy using only normal test data for training. [ABSTRACT FROM AUTHOR]