Disclosure of the internal mechanism during activating a proton exchange membrane fuel cell based on the three-step activation method

In our previous peer-reviewed article, a three-step method is put forward for increasing the efficiency of activating a newly-built membrane electrode assembly (MEA). By changing the activation temperatures of each step of the three-step method, the fuel cell performance can be greatly improved when compared with a normal one-step activation method. In this article, a deep understanding of the internal mechanism of this three-step method is conducted. Both cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) are tested after each I–V test round of a step. Two indexes, i.e., resistance reducing rate and effective current generation of catalyst (ECGC), are put forward. By integrating these two indexes, it clearly shows that the three-step activation method includes two effects, i.e., pore digging effect and pore swelling effect, which dominates in Step 1 and Step 2 separately. Finally, a pore forming mechanism model is put forward, which explains that the pore digging effect helps to form more three-phase reaction points and the pore swelling effect helps the three-phase points to become more effective. The same model also explains why the electrochemical surface area (ECSA) decreases during Step 1 and Step 2.     

Parameter identification for proton exchange membrane fuel cell model using particle swarm optimization

The accurate mathematical model is an extremely useful tool for simulation and design analysis of fuel cell power systems. Particle swarm optimization (PSO) is a recently invented high-performance algorithm. In this work, a PSO-based parameter identification technique of proton exchange membrane (PEM) fuel cell models was proposed in terms of the voltage–current characteristics. Using the simulated and experimental voltage–current data, the validity of the proposed method has been confirmed. The results indicate that the PSO is an effective technique for identifying the parameters of PEM fuel cell models even in the presence of measuring noise. Moreover, the proposed method does not particularly necessitate initial guesses as close as possible to the solutions, required only is a broad range specified for each of the parameters. Therefore, the PSO method outperforms the GA and traditional optimization methods.     

The computer-aided analysis for the driving stability of a plug-in fuel cell vehicle using a proton exchange membrane fuel cell

In order to analyze the driving stability of a plug-in fuel cell vehicle (PFCV), a computer-aided simulator for PFCVs has been developed. PFCVs have been introduced around the world to achieve early commercialization of an eco-friendly and highly efficient fuel cell vehicle. The plug-in option, which allows the battery to be recharged from the electricity grid, enables a reduction in size of the fuel cell system (FCS) and an improvement of its durability. As such, the existing limitations of the fuel cell - such as its high cost, poor durability, and the insufficient hydrogen infrastructure – can be overcome. During the design phase of PFCV development, simulation-based driving stability test is necessary to determine the sizes of the electric engine of the FCS and the battery. The developed simulator is very useful for analyzing the driving stability of the PFCV with respect to the capacities of the FCS and battery. The simulation results are in fact very close to those obtained from a real system, since the estimation accuracy of PFCV component models used in this simulator, such as the fuel cell stack, battery, electric vehicle, and the other balance of plants (BOPs), are verified by the experiments, and the simulator uses the newly-proposed power distribution control logic and the pre-confirmed real driving schedule. Using these results, we can study which one will be the best in terms of driving stability.     

Highly uniform platinum nanoparticles supported on graphite nanoplatelets as a catalyst for proton exchange membrane fuel cells

Graphite nanoplatelets (GNPs), which consist of layers of graphene, are an ideal electrocatalyst support due to their high electrical and thermal conductivity, excellent chemical stability, and easy availability. However, GNPs are somewhat chemically inert, which makes the even deposition of catalytic metal nanoparticles on their surface difficult. In this paper, we present a facile method to prepare highly uniform Pt nanoparticles on GNPs, which are decorated with 1-pyrenecarboxylic acid (PCA). When the hydrophobic pyrene group of the PCA is adsorbed on the surface of GNPs via π–π interaction, its carboxylic group can serve as an anchor for the Pt deposition. This decoration facilitates a narrow size profile, which is centered at approximately 2–3 nm, and an even spatial distribution on the GNPs surface for the Pt nanoparticles. The resultant Pt/GNPs catalyst exhibits a noticeably higher durability and electrochemical activity than the commonly used Pt/C catalyst and is therefore a promising cathodic catalyst for proton exchange membrane fuel cells.     

Investigation and analysis of proton exchange membrane fuel cell dynamic response characteristics on hydrogen consumption of fuel cell vehicle

The number of working points and response speed are two essential characteristics of proton exchange membrane fuel cell (PEMFC). The improper setting of the number of working points and response speed may reduce the life of PEMFC and increase the hydrogen consumption of the vehicle. This paper explores the impact of the response speed as well as the working points of the PEMFC on the hydrogen consumption in the real-system level. In this paper a dynamic model of the PEMFC system is established and verified by experiments. The model is able to reflect the dynamic response process of PEMFC under a series different number of working points and different response speed. Based on the proposed model, the influence of working points and the response speed of PEMFC on the hydrogen consumption in the vehicle under different driving cycles is analyzed and summarized, for the first time, in the open literature. The results highlight that the hydrogen consumption will decreases in both cases that with the increase of working point number and increase of response speed. However, the reduction range of hydrogen consumption trends to smaller and may reach to an optimal level considering the trade-off between the hydrogen saving and the other costs, for example the control cost. Also, with a more complex driving cycle, the working points and response speed have a greater the impact on the hydrogen consumption in the vehicle applications.     

Development of a proton exchange membrane fuel cell cogeneration system

A proton exchange membrane fuel cell (PEMFC) cogeneration system that provides high-quality electricity and hot water has been developed. A specially designed thermal management system together with a microcontroller embedded with appropriate control algorithm is integrated into a PEM fuel cell system. The thermal management system does not only control the fuel cell operation temperature but also recover the heat dissipated by FC stack. The dynamic behaviors of thermal and electrical characteristics are presented to verify the stability of the fuel cell cogeneration system. In addition, the reliability of the fuel cell cogeneration system is proved by one-day demonstration that deals with the daily power demand in a typical family. Finally, the effects of external loads on the efficiencies of the fuel cell cogeneration system are examined. Results reveal that the maximum system efficiency was as high as 81% when combining heat and power.     

Thermal analysis and management of proton exchange membrane fuel cell stacks for automotive vehicle

The thermal management of a proton exchange membrane fuel cell (PEMFC) is crucial for fuel cell vehicles. This paper presents a new simulation model for the water-cooled PEMFC stacks for automotive vehicles and cooling systems. The cooling system model considers both the cooling of the stack and cooling of the compressed air through the intercooler. Theoretical analysis was carried out to calculate the heat dissipation requirements for the cooling system. The case study results show that more than 99.0% of heat dissipation requirement is for thermal management of the PEMFC stack; more than 98.5% of cooling water will be distributed to the stack cooling loop. It is also demonstrated that controlling cooling water flow rate and stack inlet cooling water temperature could effectively satisfy thermal management constraints. These thermal management constraints are differences in stack inlet and outlet cooling water temperature, stack temperature, fan power consumption, and pump power consumption.     

Water content diagnosis for proton exchange membrane fuel cell based on wavelet transformation

The fuel cell reliability and durability are still the main factors limiting the large scale commercialization. To a certain degree, water content, transportation, distribution and state in the fuel cell influence the fuel cell State of Health (SOH). However, it's very difficult to measure water content inside fuel cell directly. The PEMFC system voltage fluctuate during hydrogen purging process, due to the removal of liquid water will affect the reactants transformation. Different internal water content will cause different voltage fluctuations. For this characteristic, The Energy Intensity of Reconstructed Vibrating Voltage (EIV) based on wavelet transformation is proposed and validated in this paper. The boundary value of EIV is determined to be 0.1 through experiments. The results show that the fuel cell voltage drop is reduced to 0.32 V/h from 1.39 V/h by using this method to avoid anode flooding. By several PEMFC system experiment results in test bench, this method can diagnosis the water content in PEMFC properly.     

Novel serpentine-baffle flow field design for proton exchange membrane fuel cells

An appropriate flow field in the bipolar plates of a fuel cell can effectively enhance the reactant transport rates and liquid water removal efficiency, improving cell performance. This paper proposes a novel serpentine-baffle flow field (SBFF) design to improve the cell performance compared to that for a conventional serpentine flow field (SFF). A three-dimensional model is used to analyze the reactant and product transport and the electrochemical reactions in the cell. The results show that at high operating voltages, the conventional design and the baffled design have the same performance, because the electrochemical rate is low and only a small amount of oxygen is consumed, so the oxygen transport rates for both designs are sufficient to maintain the reaction rates. However, at low operating voltages, the baffled design shows better performance than the conventional design. Analyses of the local transport phenomena in the cell indicate that the baffled design induces larger pressure differences between adjacent flow channels over the entire electrode surface than does the conventional design, enhancing under-rib convection through the electrode porous layer. The under-rib convection increases the mass transport rates of the reactants and products to and from the catalyst layer and reduces the amount of liquid water trapped in the porous electrode. The baffled design increases the limiting current density and improves the cell performance relative to conventional design.     

Maximization of high-temperature proton exchange membrane fuel cell performance with the optimum distribution of phosphoric acid

A proton exchange membrane fuel cell (PEMFC) using a controlled amount of phosphoric acid (PA) in a membrane-electrode assembly (MEA) is operated at 150 °C without humidification of the cells. The effects on MEA performance of Pt loading and the amount of PA in the cathode are investigated. The catalyst utilization is maximized by optimizing the PA content in the cathodes and results in lowering of the Pt loading in the MEA. In-situ cyclic voltammetry is used to confirm that the highest value of the active electrochemical area is achieved with the optimum amount of PA in the cathode. The transient response of cell voltage during current density–voltage experiments (I–V curve) is also found to be affected by the amount of PA in the electrodes.     

Numerical studies on ejector structure optimization and performance prediction based on a novel pressure drop model for proton exchange membrane fuel cell anode

The performance of hydrogen ejectors can be affected by the working conditions of the fuel cell system especially associating with the working pressure and pressure drop of the anode. However, the pressure drop characteristics model of the anode is correlated to the fuel cell parameters. In this work, a porous jump boundary is used as a pressure drop characteristics model of the anode which is weakly relevant to the parameters of fuel cells by employing the pressure drop characteristic curve of fuel cells. Based on the model, the influence of the condition parameters on the property of the ejector can be predicted. According to our results, the entrainment performance of the ejector can be influenced by anode inlet temperature, relative humidity, and differential pressure. Also, it is helpful for the design and prediction of the ejector in different fuel cell systems depend on the pressure drop.     

Degradations in porous components of a proton exchange membrane fuel cell under freeze-thaw cycles: Morphology and microstructure effects

In this study, porous components of a proton exchange membrane (PEM) fuel cell, i.e., single-layer gas diffusion layer (GDL, carbon paper), double-layer GDL (microporous layer (MPL) deposited carbon papers), and catalyzed electrodes, are subjected to 60 repetitive freeze-thaw cycles between −40 °C and 30 °C under water-submerged conditions; and their morphological and microstructural characteristics are investigated at each 15 cycles and compared with those of virgin materials. The results indicate that consecutive cycling of temperature causes different degradation patterns in different components. The single-layer GDL shows a unique degradation mechanism, in which macro-scale pores volumetrically expand, and relatively small-scale hollows and cracks form on the polymeric binder and carbon fiber interfaces, respectively. For the double-layer GDL, large-scale surface cracks form on the MPL surface after 15 cycles, and the morphology and microstructure degradation gains momentum with the formation of these cracks, and upon completion of 30 cycles, large-scale carbon/hydrophobic agent flakes start to detach from the surface. For the catalyzed electrodes, due to their inherently cracked surface, the catalyst layers (CLs) degrade first through expansion of the cracks in the in- and through-plane directions, and then through swelling and agglomeration of the ionomer; and combination of these two patterns triggers detachment of large CL flakes from the surface, negatively affecting the microstructure.     

Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems

This paper studies the prediction of the output voltage reduction caused by degradation during nominal operating condition of a PEM fuel cell stack. It proposes a methodology based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) which use as input the measures of the fuel cell output voltage during operation. The paper presents the architecture of the ANFIS and studies the selection of its parameters. As the output voltage cannot be represented as a periodical signal, the paper proposes to predict its temporal variation which is then used to construct the prediction of the output voltage. The paper also proposes to split this signal in two components: normal operation and external perturbations. The second component cannot be predicted and then it is not used to train the ANFIS. The performance of the prediction is evaluated on the output voltage of two fuel cells during a long term operation (1000 h). Validation results suggest that the proposed technique is well adapted to predict degradation in fuel cell systems.     

A novel three-dimensional, two-phase and non-isothermal numerical model for proton exchange membrane fuel cell

A three-dimensional, two-phase and non-isothermal model of a proton exchange membrane fuel cell (PEMFC) based on the previously developed model is established using the two-fluid method. This two-phase model considers the liquid water transport in both cathode and anode sides and accounts for the intrinsic heat transfer between the reactant fluids and the solid matrices. The latent heat of water condensation/evaporation is considered in the present model. The numerical results demonstrate that the lower cathode humidity is beneficial for cell performance. In the anode side, the water vapor can be condensed at high current density because the water vapor transport is less than the hydrogen consumption rate. Near the catalyst layer, the reactant fluid temperature is higher than the solid matrix temperature, and far from the catalyst layer, the temperature difference between the reactant fluid and the solid matrix decreases. Near the channel, the reactant fluid temperature is lower than the solid matrix temperature.     

Performance degradation prediction of proton exchange membrane fuel cell using a hybrid prognostic approach

The proton exchange membrane fuel cell has been widely used for industrial systems; however, its performance gradually degrades during use. Therefore, the study on the performance degradation prediction of fuel cells is helpful to extend its lifespan. In this paper, a novel hybrid approach using a combination of model-based adaptive Kalman filter and data-driven NARX neural network is proposed to predict the degradation of fuel cells. The overall degradation trend (i.e., irreversible degradation process) is captured by an empirical aging model and adaptive Kalman filter. Meanwhile, the detail degradation information (i.e., reversible degradation process) is depicted by the NARX neural network. Moreover, the correlation analysis of the reversible voltage time series is carried out to obtain the number of delays of the NARX neural network based on the autocorrelation function and the partial autocorrelation function. Then, the total degradation prediction is the sum of the overall degradation prediction and the detail degradation prediction. Finally, the prognostic capability of the proposed method is verified by two aging datasets, and the results show the effectiveness and superiority of the proposed method which can provide accurate degradation forecasting and remaining useful life.     

Fractal model for prediction of effective thermal conductivity of gas diffusion layer in proton exchange membrane fuel cell

The process of heat transfer within porous media is usually considered as a transport through large numbers of straight channels with uniform pore sizes. For the prediction of effective thermal conductivity of gas diffusion layer (GDL), morphological properties such as the tortuosity of channels and pore-size distribution of this porous layer should be considered. Thus in this article, novel parallel and series-parallel prediction models of effective thermal conductivity for the GDL in proton exchange membrane fuel cell (PEMFC) have been derived by fractal theoretical characterization of the real microstructure of GDL. The prediction of fractal parallel model for carbon paper, a basal material of the GDL, is in good agreement with the reference value supplied by Toray Inc. The prediction results from the proposed models are also reasonable because they are distributed between the upper and lower bounds. Parametric effect has been investigated by using the presented models in dimensionless formalism. It can be concluded that dimensionless effective thermal conductivity (k^′eff${k^{\prime }}_{\text{eff}}$) has a positive correlation with effective porosity (?) or the pore-area fractal dimension (D_p) when k_s/k_g < 1; whereas it has a negative correlation with ? or D_p when k_s/k_g > 1 and with tortuous fractal dimension (D_t) whether k_s/k_g < 1 or not. Furthermore, these fractal models have been modified by considering the effect of polytetrafluoroethylene (PTFE) incorporated into the pore spaces of carbon paper, and the corresponding model prediction shows that there is an increase in the effective thermal conductivity due to the filling of PTFE that has high thermal conductivity.     

Modeling and thermal management of proton exchange membrane fuel cell for fuel cell/battery hybrid automotive vehicle

The proton exchange membrane fuel cell (PEMFC) stack is a key component in the fuel cell/battery hybrid vehicle. Thermal management and optimized control of the PEMFC under real driving cycle remains a challenging issue. This paper presents a new hybrid vehicle model, including simulations of diver behavior, vehicle dynamic, vehicle control unit, energy control unit, PEMFC stack, cooling system, battery, DC/DC converter, and motor. The stack model had been validated against experimental results. The aim is to model and analyze the characteristics of the 30 kW PEMFC stack regulated by its cooling system under actual driving conditions. Under actual driving cycles (0–65 kW/h), 33%–50% of the total energy becomes stack heat; the heat dissipation requirements of the PEMFC stack are high and increase at high speed and acceleration. A PID control is proposed; the cooling water flow rate is adjusted; the control succeeded in stabilizing the stack temperature at 350 K at actual driving conditions. Constant and relative lower inlet cooling water temperature (340 K) improves the regulation ability of the PID control. The hybrid vehicle model can provide a theoretical basis for the thermal management of the PEMFC stack in complex vehicle driving conditions.     

Cross-linked PEEK-WC proton exchange membrane for fuel cell

The low cost proton exchange membrane was prepared by cross-linking water soluble sulfonated-sulfinated poly(oxa-p-phenylene-3,3-phthalido-p-phenylene-oxa-p-phenylene-oxy-phenylene) (SsPEEK-WC). The prepared cross-linked membrane became insoluble in water, and exhibited high proton conductivity, 2.9 × 10⁻² S/cm at room temperature. The proton conductivity was comparable with that of Nafion^® 117 membrane (6.2 × 10⁻² S/cm). The methanol permeability of the cross-linked membrane was 1.6 × 10⁻⁷ cm²/s, much lower than that of Nafion^® 117 membrane.     

Covalent-ionically cross-linked polyetheretherketone proton exchange membrane for direct methanol fuel cell

In this paper, the proton exchange membrane prepared by covalent-ionically cross-linking water soluble sulfonated-sulfinated poly(oxa-p-phenylene-3,3-phthalido-p-phenylene-oxa-p-phenylene-oxy-phenylene) (SsPEEK-WC) is reported. Compared with covalent cross-linked PEEK-WC membrane, this covalent-ionically cross-linked PEEK-WC membrane exhibits extremely reduced water uptake and methanol permeability, but just slightly sacrificed proton conductivity. The proton conductivity of the covalent-ionically cross-linked PEEK-WC membrane reaches to 2.1 × 10⁻² S cm⁻¹ at room temperature and 4.1 × 10⁻² S cm⁻¹ at 80 °C. The methanol permeability is 1.3 × 10⁻⁷ cm² s⁻¹, 10 times lower than that of Nafion^® 117 membrane. The results suggest that the covalent-ionically cross-linked PEEK-WC membrane is a promising candidate for direct methanol fuel cell because of low methanol permeability and adequate proton conductivity.