Fuel Cells最新文献

Proton exchange membrane fuel cells (PEMFCs) play a central role in the transition to clean hydrogen-based energy systems. However, conventional models with fixed empirical parameters often fail to predict performance under variable operating conditions accurately. This paper introduces two novel PEMFC models with load-dependent formulations of the activation overpotential constant and its temperature coefficient, parameters shown to have the greatest sensitivity to load variation. Using the artificial hummingbird algorithm (AHA) for parameter optimization, the models were tested on four representative PEMFC configurations (Ballard-Mark-V 5 kW PEMFC, BCS 500 W, NedStack PS6 6 kW PEMFC, and Horizon 500 W). The results demonstrate a consistent reduction in prediction error compared with state-of-the-art models, with an improvement of up to 89.97% in RMSE for the Horizon cell. Sensitivity and robustness analyses further confirm stable performance under varying temperature and pressure conditions. These findings suggest that the proposed models offer a reliable and computationally efficient foundation for advanced simulation, control, and optimization of PEMFC systems in real-world applications.

Proton exchange membrane fuel cells (PEMFCs) are highly efficient electrochemical energy converters utilized for the production of sustainable, renewable, and clean power. A cell contains a membrane, bipolar plates housing flow channels, gas diffusion, and catalyst layers. The channel geometry influences pressure loss along the channel and transporting the reactant gases to porous layers. In this article, the influence of distinct widened sections in a square channel having a small cross-sectional area of 0.2 × 0.2 mm² on PEMFC performance is examined via ANSYS Fluent for 0.4–0.6 V. The enlarged section length varies 1/4, 1/2, and 3/4 of the length of cell (L = 70 mm). The results revealed that the new configurations with enlarged sections significantly diminished the pressure loss in the channels with a slight decline in the current density. The innovative channel configuration having a widened section with a length of 3L/4 reduces the current density, anode and cathode pressure drops of 5.8%, 40.4%, and 46.0%, respectively, compared to the square channel for 0.4 V. Considering pressure losses through the flow channels, this channel configuration is a better choice to enhance PEMFC efficiency.

Proton exchange membrane fuel cells (PEMFC) have been widely utilized in transportation and power generation due to their high efficiency and low pollution. However, their durability remains insufficient, and their output power decreases over time during operation. Therefore, it is important to predict the remaining useful life (RUL) of the PEMFC to ensure its efficient operation. In this paper, an improved TCN-iTransformer model is proposed for predicting the RUL of PEMFC, which integrates temporal convolutional network (TCN), iTransformer, discrete cosine transform (DCT), and the channel attention mechanism. The reliability of the model was validated using both static and dynamic datasets of different lengths. And the results showed that the improved TCN-iTransformer achieved a significant improvement over the Transformer prototype in long sequence time-series forecasting. Furthermore, smaller mean absolute percentage error (MAPE) and root mean square error (RMSE) were obtained compared to other improved models, such as long short-term memory (LSTM) and gated recurrent unit (GRU). In addition, the RUL prediction error of the model was found to not exceed 1 h.

This research compares the performance of plug-in fuel cell electric vehicles (PFCEVs), battery electric vehicles (BEVs), and fuel cell electric vehicles (FCEVs) using MATLAB Simulink. The simulations were run for 1800 s using the Worldwide Harmonized Light Vehicles Test Cycle (WLTC 3a), spanning a distance of 23 km, to assess important performance characteristics such as energy efficiency, consumption, emissions, and life cycle costs. The PFCEV architecture, which combines a medium-sized fuel cell and a sizable battery pack, has a strategic advantage because it requires fewer charging stations than BEVs and fewer hydrogen filling stations than FCEVs. The findings reveal that PFCEVs provide a unique combination of high efficiency, low emissions, rapid recharging, and greater driving range while requiring minimal hydrogen infrastructure. Compared to BEVs, PFCEVs minimize range anxiety while improving grid stability, and unlike FCEVs, they maximize hydrogen utilization via a complicated power management system. This study highlighted PFCEVs as a viable choice for sustainable mobility, serving as a valuable link between BEVs and FCEVs in the evolution of electric transportation. The findings indicate that PFCEVs have a good possibility of becoming a preferred vehicle technology, bridging the gap between battery and hydrogen-powered electric vehicles while addressing infrastructure and efficiency challenges.

Nowadays, green hydrogen technology is a pivotal innovation for reducing environmental pollution and combating global climate change. In the pursuit of sustainability, proton exchange membrane fuel cells (PEMFCs) are considered a promising solution for optimizing the utilization of green hydrogen and enhancing energy storage capabilities. This article presents a novel application of the mirage search optimization (MSO) algorithm for developing an accurate PEMFC model. Through a comprehensive study of four typical PEMFC stacks, the results demonstrate the superior performance of the proposed MSO algorithm when compared to other optimizers in terms of accuracy and convergence speed. The optimization algorithms used for comparison with MSO include the grey wolf optimizer, whale optimization algorithm, chimpanzee optimization algorithm, and other optimizers from the literature. The enhancement in modeling accuracy by obtaining a better fitness value using MSO over other optimizers is up to 10.7% for NedStack PS6, 7.1% for Ballard Mark 5 kW, 31.5% for BCS 500 W, and 85.39% for Horizon H-500. Furthermore, a sensitivity analysis is carried out to validate the results obtained by MSO and to verify the accuracy of the developed model. Through comprehensive performance assessments, it can be confirmed that MSO is a promising algorithm for accurately estimating the parameters of PEMFC models, as it demonstrates high efficiency and robustness.

This study employs an integrated approach combining three-dimensional multiphase numerical simulations with experimental validation. A refined single-channel proton exchange membrane fuel cell (PEMFC) model, verified for grid independence, was developed. User-defined functions (UDFs) were implemented to accurately describe key processes, including electrochemical reactions, water phase change (liquid/ice), and transport phenomena. A systematic simulation analysis was conducted to elucidate the influence of operating temperature (50–70°C), anode/cathode inlet humidity (50–100% relative humidity), and gas diffusion layer (GDL) porosity (0.4–0.8) on cell output characteristics (polarization curves, power density) and internal mass transport dynamics. Concurrently, cyclic voltammetry (CV) and linear sweep voltammetry (LSV) experiments were performed to deeply investigate the electrochemical performance degradation and microstructural evolution of electrodes with varying water contents under freeze–thaw cycling. The results demonstrate that elevating the operating temperature to 60–70°C significantly enhances cell performance, primarily attributable to increased membrane conductivity and optimized water management. A synergistic optimization effect was identified between reactant gas humidity and GDL porosity. At 60°C, a combination of 75% anode humidity and 100% cathode humidity achieved an optimal balance between output performance and operational stability. Increasing GDL porosity to 0.6–0.8 effectively enhanced reactant gas transport and liquid water removal, reducing current density decay during cold start (−10°C) by approximately 50% and significantly mitigating mass transport blockage and performance degradation caused by ice formation. Freeze–thaw cycling experiments further revealed that electrode water content is a critical factor determining its durability. Flooded conditions exacerbated structural damage from freezing, leading to persistent performance decay, whereas lower water content conditions effectively preserved electrode structural integrity and catalytic activity. This research elucidates the interactive mechanisms of water–thermal–mass transport under multiphysics coupling, providing a theoretical foundation and practical design guidelines for optimizing performance and enhancing the durability of PEMFCs under complex operating conditions.

The interconversion of chemical energy and electrical energy is a promising approach to alleviate the intermittency, fluctuation, and regionality of renewable energy. Direct liquid fuel cells (DLFCs) directly convert the chemical energy in liquid fuel into electricity, although avoiding the storage and transportation problems of gaseous hydrogen, their development has long been limited by the low cell performance. The pH-disparate strategy, which uses alkaline liquid fuel as anode reductant and acidified hydrogen peroxide as the cathode oxidant, has been proposed to fundamentally improve the thermodynamic voltage and cell performance of DLFCs. Herein, the prospect and challenge of hydrogen peroxide in constructing high-performance pH-disparate DLFCs are reviewed and summarized. First, the reaction mechanisms of both hydrogen peroxide oxidation and reduction on different electrocatalysts were elucidated in this review, and then the thermodynamic properties, including pH dependent thermodynamic voltage, energy density, and capacity, of different types of pH-disparate DLFCs were described in detail. Finally, we summarized the impact of the system design and operating conditions on the cell performance of pH-disparate DLFCs. Hopefully, this review will provide a reference guidance for the practical application of hydrogen peroxide in DLFCs.

By overcoming low-temperature limitations, it paves the way for widespread commercialization of fuel cells, reinforcing their role in achieving sustainable energy systems and combating climate change. Therefore, this work systematically analyzes the reasons for the degradation of the fuel cell stack after low-temperature start-up operation with an effective area of 367 cm² and 170 cells. To investigate the root causes, systematic characterization of the catalyst layer (CL) and gas diffusion layer (GDL) was performed. Transmission electron microscopy and x-ray diffraction analyses confirmed that Pt particles exhibited increased defects and particle size at three membrane electrode positions, particularly at the hydrogen inlet/outlet, where the (111) interplanar spacing expanded significantly. Raman spectroscopy detected carbon corrosion on both anode and cathode sides after cold start, with anode corrosion being more severe. GDL permeability decreased significantly post-cold start, especially at the hydrogen outlet. Cold-start-induced water redistribution promotes ice formation at CL/GDL interfaces, triggering localized reverse polarity. Reverse polarity accelerates carbon corrosion, destabilizing catalyst supports (Pt agglomeration) and GDL pore structure (carbon powder loss). This study elucidates the multiscale degradation mechanisms of membrane electrodes under cold-start conditions, providing critical insights for improving fuel cell low-temperature durability.