Proton Exchange Membrane Fuel Cell Research Articles

Enhanced hunger games search algorithm that incorporates the marine predator optimization algorithm for optimal extraction of parameters in PEM fuel cells

This article introduces a novel optimization approach to improve the parameter estimation of proton exchange membrane fuel cells (PEMFCs), which are critical for diverse applications but are challenging to model due to their nonlinear behavior. The proposed method, HGS-MPA, enhances the Hunger Games Search (HGS) algorithm by integrating Marine Predator Algorithm (MPA) operators, significantly boosting its exploitation capabilities and convergence rate. The effectiveness of HGS-MPA was validated on three commercial PEMFC datasets: 250-W stack, BCS 500-W, and NedStack PS6, using the Sum Squared Error (SSE) as the performance metric. Experimental results highlight that HGS-MPA achieves minimum fitness values of 0.33770, 1.31620, and 0.01174 for the respective datasets, outperforming other state-of-the-art algorithms. These findings underscore the method’s potential for accurate PEMFC parameter estimation, offering enhanced performance and reliability.

Numerical and Experimental Investigations on an Angular Approach Flowfield (AAF) Geometry for PEM Fuel Cells

Numerical and Experimental Investigations on an Angular Approach Flowfield (AAF) Geometry for PEM Fuel Cells

In Situ 2D-XAS Imaging and Modeling Analysis of Cerium Migration in Proton Exchange Membrane Fuel Cells

Abstract In-situ two-dimensional X-ray absorption spectroscopy (XAS) imaging was employed to analyze cerium ion (Ce3+) migration in the through-plane direction in proton exchange membrane fuel cells (PEMFCs), offering fundamental insights supporting improvement of their power density and membrane durability. The transport of Ce3+ was visualized in both unreinforced thick Nafion membranes (Nafion 115, 127 µm) and reinforced thin (12 µm) perfluorosulfonic acid (PFSA) membranes under either an electrical potential gradient or a water activity gradient. The diffusion coefficients of Ce3+ were ascertained based on its behavior after removal of these gradients in both membrane types. Additionally, using a one-dimensional cation transport model, the mobility and electroosmotic drag coefficients of Ce3+ were derived from experimentally obtained data of the thick Nafion membrane. Our measurements also demonstrate that the migration of Ce3+ in the thick membranes was notably impeded by the presence of ferrous ion (Fe2+) impurities. Because Fe2+ is known to accelerate membrane degradation by promoting hydroxyl radical formation, this effect might further exacerbate membrane degradation. It therefore warrants careful consideration.

Sulfur Dioxide-Tolerant Core@shell Ru@Pt Catalysts Toward Oxygen Electro-Reduction

Proton exchange membrane fuel cells (PEMFCs) have achieved milestones in performance improvements and commercial launches. In the typical commercialized PEMFCs, the compressed air to cathode is usually supplied from ambient air, assuming that no costly pre-purification system is applied. Therefore, the working PEMFCs may suffer from the negative effects of the air impurities. In this regard, SO2, as the most poisonous species, may be fed along with air at the cathode and strongly adsorbed on the Pt surface, leading to Pt site deactivation. To address this challenge, we published a series of works in terms of poisoning mechanisms, regeneration protocols, and advanced poisoning-tolerant catalysts. Herein, we are aiming at developing a SO2-tolerant electrocatalyst toward a cathodic oxygen reduction reaction (ORR). We reasonably incorporate the Ru, synthesize Ru@Pt core@shell catalysts and investigate the relationships among Ru incorporation, ORR activity and SO2 tolerance. Impressively, the Ru@Pt/C exhibits higher initial ORR activity (0.288 A mg−1Pt), better SO2 poisoning resistance (33% loss in initial activity) than that of commercial Pt/C catalysts (0.252 A mg−1Pt; 62% loss). The engineered affinity between Pt and SO2 in the presence of Ru is uncovered to account for the improvement.

Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm

Energy scheduling for hybrid unmanned aerial vehicles (UAVs) is of critical importance to their safe and stable operation. However, traditional approaches, predominantly rule-based, often lack the dynamic adaptability and stability necessary to address the complexities of changing operational environments. To overcome these limitations, this paper proposes a novel energy scheduling framework that integrates the Model Predictive Control (MPC) with a Deep Reinforcement Learning algorithm, specifically the Deep Deterministic Policy Gradient (DDPG). The proposed method is designed to optimize energy management in hydrogen-powered UAVs across diverse flight missions. The energy system comprises a proton exchange membrane fuel cell (PEMFC), a lithium-ion battery, and a hydrogen storage tank, enabling robust optimization through the synergistic application of MPC and DDPG. The simulation results demonstrate that the MPC effectively minimizes electric power consumption under various flight conditions, while the DDPG achieves convergence and facilitates efficient scheduling. By leveraging advanced mechanisms, including continuous action space representation, efficient policy learning, experience replay, and target networks, the proposed approach significantly enhances optimization performance and system stability in complex, continuous decision-making scenarios.

The influence of electrode crack dimensions on the durability of polymer electrolyte membrane fuel cells

The influence of electrode crack dimensions on the durability of polymer electrolyte membrane fuel cells

Evaluating electrocatalytic activities of Pt, Pd, Au and Ag-based catalyst on PEMFC performance: A review

Evaluating electrocatalytic activities of Pt, Pd, Au and Ag-based catalyst on PEMFC performance: A review

Comprehensive review on the advances and comparisons of proton exchange membrane fuel cells (PEMFCs) and anion exchange membrane fuel cells (AFCs): From fundamental principles to key component technologies

Comprehensive review on the advances and comparisons of proton exchange membrane fuel cells (PEMFCs) and anion exchange membrane fuel cells (AFCs): From fundamental principles to key component technologies

Deep learning-based fault diagnosis of high-power PEMFCs with ammonia-based hydrogen sources

Deep learning-based fault diagnosis of high-power PEMFCs with ammonia-based hydrogen sources

Assessing Durability in Automotive Fuel Cells: Understanding the Degradation Patterns of PEM Fuel Cells Under Variable Loads, Temperature, Humidity, and Defective Stack Conditions

Assessing Durability in Automotive Fuel Cells: Understanding the Degradation Patterns of PEM Fuel Cells Under Variable Loads, Temperature, Humidity, and Defective Stack Conditions

Enhancing Proton Exchange Membrane Fuel Cell (PEMFC) Performance through Optimized Design of Parallel Channel Bipolar Plates

In this modern era, the demand for efficient and environmentally friendly energy sources is increasing. One technology with significant potential to meet this demand is the Proton Exchange Membrane Fuel Cell (PEMFC). This study aims to investigate the influence of channel width and depth variations in parallel bipolar plate designs on PEMFC performance. Computational Fluid Dynamics (CFD) was employed to analyze hydrogen flow distribution and pressure across various design variations. The results demonstrate that channel width and depth significantly affect pressure distribution and flow velocity, which in turn influence the efficiency of the PEMFC system. Increasing channel width generally reduces maximum pressure, while deeper channels help to distribute pressure more evenly across the bipolar plate. Optimized channel width and depth can enhance PEMFC operational performance by reducing pressure drop and promoting uniform flow distribution.

Performance of Graphene Oxide-Supported Co₃O₄ with Assisted Urea as Electrocatalysts for Oxygen Reduction Reaction in PEMFCs

In this work, cobalt oxide (Co3O4) nanoparticles supported on a graphene oxide (GO) electrocatalyst were synthesized using a simple and low-cost hydrothermal route for oxygen reduction reaction (ORR) in fuel cells. The effects of varying the urea concentration on the physicochemical and electrochemical characteristics were investigated in alkaline media using field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), Raman spectroscopy, cyclic voltammetry (CV), linear sweep voltammetry (LSV), and chronoamperometry. The electrocatalyst prepared using cobalt acetate tetrahydrate and urea with a molar ratio of 1:1 exhibited the best ORR activity where the highest onset potential (Eonset) at 0.88 V through four-electron mechanism at 25 °C. The synthesized electrocatalyst also showed improved stability compared with Pt/C. Although CN1-1 exhibits a lower power density (37.9 mW cm⁻2) compared to Pt/C (173.6 mW cm⁻2), it is still expected to be suitable as an ORR electrocatalyst for proton exchange membrane fuel cells (PEMFCs).

Lattice Hydrogen Boosts CO Tolerance of Pd Anode Catalysts in High‐Temperature Proton Exchange Membrane Fuel Cells

AbstractHigh‐temperature proton exchange membrane fuel cells (HT‐PEMFCs) demonstrate crude hydrogen can be a cost‐effective fuel source. However, the performance of HT‐PEMFCs is hindered by challenges such as high‐concentration CO poisoning and preferential adsorption of H3PO4 on electrocatalysts. This study explores the performance of Pt group metals as anode catalysts, specifically focusing on hydrogen oxidation reaction (HOR) activity, H3PO4 tolerance, and CO tolerance under operational conditions in HT‐PEMFCs. The results reveal that all Pt‐group catalysts significantly improve HOR activity with increasing reaction temperature. Notably, Pd‐based catalysts demonstrate superior H3PO4 tolerance and CO tolerance. HT‐PEMFCs using Pd/C as the anode catalyst maintain the highest output power density, achieving a remarkable 6.4‐fold performance compared to Pt/C catalysts and superior stability in the presence of 3%–10% CO in H2. Both experimental and theoretical investigations have consistently demonstrated that Pd possesses the weakest CO adsorption energy, the existence of CO in crude H2 in HT‐PEMFCs inhibits hydrogen overflow from the lattice interstitial space of Pd, and the trapped lattice hydrogen further promotes the desorption of CO. This research contributes to the advancement of direct utilizing industrial crude hydrogen as a fuel for HT‐PEMFCs and offers invaluable insights into reactions involving CO.

Methanol-Tolerant Pd-Co Alloy Nanoparticles on Reduced Graphene Oxide as Cathode Catalyst for Oxygen Reduction in Fuel Cells

The design of efficient and cost-effective electrocatalysts to replace Pt in an oxygen reduction reaction (ORR) is crucial for advancing proton exchange membrane fuel cell (PEMFC) technologies. This study synthesized Pd-Co bimetallic alloy nanoparticles supported on reduced graphene oxide (rGO) through a simple chemical-reduction method, making it suitable for low-cost, large-scale fabrication and significantly reducing the need for Pt. The nanostructures were systematically characterized using various analytical techniques, including X-ray diffraction (XRD), high-resolution transmission electron microscopy (HR-TEM), energy-dispersive X-ray spectroscopy (EDX), and cyclic voltammetry (CV). Electrochemical investigations revealed that the Pd-Co/rGO catalyst exhibits remarkable ORR performance in an alkaline environment, with an electrode-area-normalized activity rivaling that of the commercial Pt/C catalyst. Remarkably, Pd-Co/rGO demonstrated an onset potential (Eonset) of 0.944 V (vs. RHE) and a half-wave potential (E1/2) of 0.782 V (vs. RHE), highlighting its excellent ORR activity. Furthermore, the Pd-Co/rGO catalyst displayed superior methanol-tolerant ORR activity, outperforming Pt/C and monometallic Pd/rGO and Co/rGO systems. The enhanced electrocatalytic performance is attributed to the smallest size, consistent shape, and good dispersion of the alloy structure on the RGO surface. These findings establish Pd-Co/rGO as a promising alternative to Pt-based catalysts, addressing key challenges such as methanol crossover while advancing PEMFC technology in alkaline media.

Investigation of Membrane–Electrode Separation Processes for the Recycling of Ionomer Membranes in End-of-Life PEM Fuel Cells

Investigation of Membrane–Electrode Separation Processes for the Recycling of Ionomer Membranes in End-of-Life PEM Fuel Cells

Proton Exchange Membrane Fuel Cell Stack Durability Prediction Using Arrhenius-Based Accelerated Degradation Model

To expand the applications of proton exchange membrane fuel cell (PEMFC) stacks, it is essential to address the issue of their short lifetime. Various studies are being conducted to improve this limitation, and efficient methods for verifying durability in a short period of time are required. This study presents a novel dynamic load cycling protocol designed to emulate the real-world driving conditions of commercial vehicles. This protocol was employed as an accelerated degradation test for PEMFC stacks under two elevated temperatures (65 and 80 °C), each conducted for 1000 h. A bi-exponential model, incorporating Arrhenius principles, was fitted to the degradation data. During this process, a mixed effects modeling approach was employed to distinguish between fixed and random effects within the model parameters. The activation energy was consistent across all cells and was thus designated as a fixed effect. Activation energy, which predominantly affects the long-term durability of PEMFC stacks, was estimated as 0.808 eV. By applying this estimated value to the Arrhenius equation, we calculated the acceleration factors for the degradation of fuel cell performance. Specifically, the rate of voltage degradation was found to be approximately 1.516 times faster at 65 °C and 4.923 times faster at 80 °C, compared to the standard operating temperature of 60 °C. Additionally, Monte Carlo simulations were conducted to predict the failure-time distribution under normal use conditions, estimating a median lifetime of 3884 h, which corresponds to 155,360 km of driving. This methodology offers a reliable and time-efficient framework for assessing PEMFC durability, with significant implications for reducing testing costs and accelerating the development of hydrogen fuel cell technology.

Effect of Solid Content and Ionomer-to-Carbon Ratio on High-Solid-Content Ink-Cast Catalyst Layers for PEM Fuel Cells

Effect of Solid Content and Ionomer-to-Carbon Ratio on High-Solid-Content Ink-Cast Catalyst Layers for PEM Fuel Cells

Estimation of Fuel Cell Power Demand on Commercial Vehicles Based on Improved Multiple Grey Prediction Method Considering Dynamic Time Window

A frequently large variation in load conditions is of great impact on the service life of fuel cells during the operation of fuel cell vehicles and further increases the maintenance cost of the system. This study proposed a method of power demand prediction of the proton exchange membrane fuel cell (PEMFC) on vehicles in the actual traffic environment. The hybrid power system topology of fuel cells and power battery on commercial vehicles is selected to build a fuel cell model, and the accuracy of the fuel cell model is verified. An improved multiple grey prediction method is then proposed to predict the power demand during the sampling period of the fuel cell while considering a dynamic time window in the prediction period. Comparisons were made between this proposed model and the other two prediction models as a single-step prediction and multi-step prediction. Data of CHTC-HT and field testing working conditions were used to evaluate these three prediction models in fuel cell power demand. Results showed that the multiple grey method showed a better prediction performance than the other models, indicated by the lowest error value of 16.944% under the CHTC-HT condition, the lowest error value of 2.169% under stable conditions with less variable load and 1.930% under dynamic conditions with frequent load changes in field testing. This study of the demand power prediction can be devoted to pre-tuning the fuel cell system to avoid performance degradation caused by unanticipated power fluctuation.

Advanced Strategies for Mitigating Catalyst Poisoning in Low and High Temperature Proton Exchange Membrane Fuel Cells: Recent Progress and Perspectives

Catalyst poisoning remains a persistent barrier to the efficiency and longevity of electrocatalytic energy conversion devices, namely fuel cells. To address this challenge, this review provides a systematic investigation of recent advancements in mitigation strategies, with particular emphasis on surface engineering, alloying, and combined approaches. Notable developments include the rational design of Pt-alloy catalysts with enhanced CO, H2S, and H3PO4 tolerance as well as the implementation of anti-poisoning molecular architectures and carbon-based protective layers. These methods collectively show considerable promise for improving catalytic activity by fine-tuning electronic structures and minimizing interactions with undesired adsorbates. In addition to presenting a comprehensive overview of the current progress, this review identifies promising future directions, guiding the design and realization of robust, poison-tolerant catalysts crucial for sustainable energy technologies.

Pore-Scale Investigation of the Compression Effect on Liquid Water Transport in the Gas Diffusion Layer of Proton Exchange Membrane Fuel Cells

Pore-Scale Investigation of the Compression Effect on Liquid Water Transport in the Gas Diffusion Layer of Proton Exchange Membrane Fuel Cells