Carbon dioxide vent for direct methanol fuel cells

Passive, stand-alone, direct methanol fuel cells require a pressure management system that releases CO₂ produced in the anode chamber. However, this must be done without allowing the methanol fuel to escape. In this paper, two siloxane membranes are investigated and shown to selectively vent CO₂ from the anode chamber. The addition of hydrophobic additives, 1,6-divinylperfluorohexane and 1,9-decadiene, improved the selectivity of the siloxane membranes. The best performing CO₂ vent was obtained with 50:50 wt% poly(1-trimethyl silyl propyne) and 1,6-divinylperfluorohexane.     

Performance of carbon dioxide vent for direct methanol fuel cells

Direct methanol fuel cells have potentially high energy density if the balance of plant and fuel losses can be kept to a minimum. CO₂ accumulation in the fuel tank can lower the efficiency and performance of closed-tank methanol fuel cells. This report discusses the implementation of a passive CO₂ vent fabricated with poly(1-trimethyl silyl propyne) and 1,6-divinylperfluorohexane. The performance of the membrane as a selective vent for carbon dioxide in the presence of methanol has been studied at various operating conditions. First, the selectivity of the vent membrane improved with temperature. Second, the activation energy for permeation through the polymer membrane corresponded to diffusion controlled transport of CO₂ and sorption controlled transport for methanol vapor. The activation energy for CO₂ transport through the poly(1-trimethyl silyl propyne) and 1,6-divinylperfluorohexane membrane was less than that for a pure poly(1-trimethyl silyl propyne) membrane. Finally, the polymer had a high selectivity for carbon dioxide compared to both liquid and vapor phase methanol.     

Two-phase flow measurement system for polymer electrolyte fuel cells

In this paper, a sensory system capable of measuring two-phase flow of water at the PEFC output is introduced. It works based on collecting and evaporating the liquid water that exits the PEFC in a vessel that is heated to a temperature above that of the fuel cell temperature. By measuring the vessel dew point temperature and flow rate, the mass of water in liquid and vapor phases are calculated. To demonstrate the capabilities of this measurement system, it is placed at the output of a PEFC cathode during membrane conditioning. The effect of two-phase flow on cell voltage reveals two distinct modes of liquid water transport in the PEFC cathode during membrane conditioning.     

The silica-doped sulfonated poly(fluorenyl ether ketone)s membrane using hydroxypropyl methyl cellulose as dispersant for high temperature proton exchange membrane fuel cells

The sulfonated poly(fluorenyl ether ketone)s (SPFEK) membranes doped with SiO₂ and dispersed by hydroxypropyl methyl cellulose (HPMC) were prepared and investigated for polymer electrolyte membrane fuel cells (PEMFCs) used at high temperature and low relative humidity (RH). The above membrane was prepared by solution dispersion of SPFEK and SiO₂ using HPMC as dispersant. The physio-chemical properties of the hybrid membrane were studied by means of scanning electron microscope (SEM), ion-exchange capacity (IEC), proton conductivity, and single cell performance tests. The hybrid membranes dispersed by HPMC were well dispersed when compared with common organic/inorganic hybrid membranes. The hybrid membranes showed superior characteristics as a proton exchange membrane (PEM) for PEMFC application, such as high ionic exchange content (IEC) of 1.51 equiv/g, high temperature operation properties, and the satisfactory ability of anti-H₂ crossover. The single cell performances of the hybrid membranes were examined in a 5 cm² commercial single cell at both 80 °C and 120 °C under different relative humidity (RH) conditions. The hybrid membrane dispersed by HPMC gave the best performance of 260 mW/cm² under conditions of 0.4 V, 120 °C, 50% RH and ambient pressure. The results demonstrated HPMC being an efficient dispersant for the organic/inorganic hybrid membrane used for PEM fuel cell.     

Gas selectivity measurements as a diagnostic tool for fuel cells

In this study, gas permeability and selectivity measurements are used to identify when membrane thinning or integrity failures have occurred in a fuel cell membrane electrode assembly and hence be used as a tool to identify when chemical or mechanical degradation is the dominant mode of failure. A fuel cell was operated at open circuit voltage conditions and the permeability of five different gasses (H₂, He, N₂, O₂, Ar) were measured periodically. The results showed that through a fresh MEA the gasses permeated via a solution diffusion type mechanism though after 150 h of degradation the permeation behaviour changed to Knudsen diffusion mechanism. This was interpreted to indicate that an integrity failure had occurred in the ionomer membrane. Voltage data also shows an increase in voltage degradation rate after 150 h and a drop in polarization performance. Furthermore, there was an increase in fluoride emission rate. Analysis of the de-catalyzed membrane after degradation revealed rips and tears in the ionomer membrane and no significant thickness changes.     

Phosphorus-doped glass proton exchange membranes for low temperature direct methanol fuel cells

Phosphorus-doped silicon dioxide thin films were used as ion exchange membranes in low temperature proton exchange membrane fuel cells. Phosphorus-doped silicon dioxide glass (PSG) was deposited via plasma-enhanced chemical vapor deposition (PECVD). The plasma deposition of PSG films allows for low temperature fabrication that is compatible with current microelectronic industrial processing. SiH₄, PH₃ and N₂O were used as the reactant gases. The effect of plasma deposition parameters, substrate temperature, RF power, and chamber pressure, on the ionic conductivity of the PSG films is elucidated. PSG conductivities as high as 2.54 × 10⁻⁴ S cm⁻¹ were realized, which is 250 times higher than the conductivity of pure SiO₂ films (1 × 10⁻⁶ S cm⁻¹) under identical deposition conditions. The higher conductivity films were deposited at low temperature, moderate pressure, limited reactant gas flow rate, and high RF power.     

On-line fault diagnostic system for proton exchange membrane fuel cells

In this paper, a supervisor system, able to diagnose different types of faults during the operation of a proton exchange membrane fuel cell is introduced. The diagnosis is developed by applying Bayesian networks, which qualify and quantify the cause–effect relationship among the variables of the process. The fault diagnosis is based on the on-line monitoring of variables easy to measure in the machine such as voltage, electric current, and temperature. The equipment is a fuel cell system which can operate even when a fault occurs. The fault effects are based on experiments on the fault tolerant fuel cell, which are reproduced in a fuel cell model. A database of fault records is constructed from the fuel cell model, improving the generation time and avoiding permanent damage to the equipment.     

An analytical model for hydrogen and nitrogen crossover rates in proton exchange membrane fuel cells

In this paper, the hydrogen and nitrogen crossover through the membrane in proton exchange membrane fuel cells, are investigated by developing a semi-empirical analytical model. Different factors that affect the gas crossover rates were considered including pressure drop in gas diffusion layer (GDL) and catalyst layer (CL), operating temperature, relative humidity (RH) of the reactants, GDL compression, and the current density effect on the membrane temperature. The model is validated by published experimental data. It is found that RH is the most important parameter, followed by temperature. The hydrogen pressure drop through GDL and CL greatly depends on the GDL substrate properties, microporous layer (MPL) and CL. When permeability is low, an increase in current density reduces gas crossover. GDL compression, when MPL is used, was found to have a low impact on gas crossover. Gas crossover is improved with current density due to an increase in membrane temperature.     

Accelerated durability tests of catalyst layers with various pore volume for catalyst coated membranes applied in PEM fuel cells

The effect of pore volume on the catalyst layer durability of PEM fuel cell was simulated by soaking the catalyst coated membrane (CCM) into H₂O₂/Fe²⁺ solution. Before this simulation, the CCM with various pore volumes in catalyst layer was fabricated. The structure of catalyst layers was optimized with an increase in pore volume, leading to an improvement of fuel cell performance. However, this treatment causes a negative effect on the lifetime of CCM especially when H₂O₂/Fe²⁺ introduced. As a result, the catalyst layer with high pore volume has a higher detaching rate than that with low pore volume. The detaching of catalyst layers could be attributed to degradation of both the recast Nafion in catalyst layers and the Nafion membrane. The catalyst layer with high pore volume accelerates the recast Nafion degradation. Thus, the durability of membrane electrode assembly should be considered when the catalyst layer is optimized.     

Design of an adaptive EMS for fuel cell vehicles

This paper addresses the energy management strategy (EMS) for a fuel cell hybrid electric vehicle (FC-HEV). In this work, model parameters are identified online by using the square root unscented Kalman filter (SR-UKF) method to seek a variation in the fuel cell performances. Then, an optimization algorithm is used on the updated model to find the best efficiency and power operating points. This process is used into two strategies: (i) A hysteresis energy management strategy (EMS) and (ii) an optimal EMS based on Pontryagin's minimum principle, for a FC-HEV. The effectiveness of the proposed EMSs is demonstrated by conducting studies on a FC-HEV model.     

Comparative exergy analysis of direct alcohol fuel cells using fuel mixtures

Within the last years there has been increasing interest in direct liquid fuel cells as power sources for portable devices and, in the future, power plants for electric vehicles and other transport media as ships will join those applications. Methanol is considerably more convenient and easy to use than gaseous hydrogen and a considerable work is devoted to the development of direct methanol fuel cells. But ethanol has much lower toxicity and from an ecological viewpoint ethanol is exceptional among all other types of fuel as is the only chemical fuel in renewable supply. The aim of this study is to investigate the possibility of using direct alcohol fuel cells fed with alcohol mixtures. For this purpose, a comparative exergy analysis of a direct alcohol fuel cell fed with alcohol mixtures against the same fuel cell fed with single alcohols is performed. The exergetic efficiency and the exergy loss and destruction are calculated and compared in each case. When alcohol mixtures are fed to the fuel cell, the contribution of each fuel to the fuel cell performance is weighted attending to their relative proportion in the aqueous solution. The optimum alcohol composition for methanol/ethanol mixtures has been determined.     

Understanding the performance degradation of anion-exchange membrane direct ethanol fuel cells

It has recently been demonstrated that anion-exchange membrane direct ethanol fuel cells (AEM DEFCs) can yield a high power density. The operating stability and durability of this type of fuel cell is, however, a concern. In this work, we report the durability test of an AEM DEFC that is composed of a Pd/C anode, an A201 membrane, and a Fe-Co cathode and show that the major voltage loss occurs in the initial discharge stage, but the loss becomes smaller and more stable with the discharge time. It is also found that the irreversible degradation rate of the fuel cell is around 0.02 mV h⁻¹, which is similar to the degradation rate of conventional acid direct methanol fuel cells (DMFCs). The experimental results also reveal that the performance loss of the AEM DEFC is mainly attributed to the anode degradation, while the performance of the cathode and the membrane remains relatively stable. The TEM results indicate that the particle size of the anode catalyst increases from 2.3 to 3.5 nm after the long-term discharge, which reduces the electrochemical active surface area and hence causes a decrease in the anode performance.     

Multi-input and multi-output neural model of the mechanical nonlinear behaviour of a PEM fuel cell system

A fuel cell system model is necessary to prepare and analyse vibration tests. However, in the literature, the mechanical aspect of the fuel cell systems is neglected. In this paper, a neural network modelling approach for the mechanical nonlinear behaviour of a proton exchange membrane (PEM) fuel cell system is proposed. An experimental set is designed for this purpose: a fuel cell system in operation is subjected to random and swept-sine excitations on a vibrating platform in three axes directions. Its mechanical response is measured with three-dimensional accelerometers. The raw experimental data are exploited to create a multi-input and multi-output (MIMO) model using a multi-layer perceptron neural network combined with a time regression input vector. The model is trained and tested. Results from the analysis show good prediction accuracy. This approach is promising because it can be extended to further complex applications. In the future, the mechanical fuel cell system controller will be implemented on a real-time system that provides an environment to analyse the performance and optimize mechanical parameters design of the PEM fuel system and its auxiliaries.     

Degradation prediction model for proton exchange membrane fuel cells based on long short-term memory neural network and Savitzky-Golay filter

Proton exchange membrane fuel cell (PEMFC) as a promising green power source, can be applied to vehicles, ships, and buildings. However, the lifetime of the fuel cell needs to be prolonged in order to achieve a wide range of applications. Consequently, the prediction of the health state draws attention lately and is critical to improving the reliability of the fuel cell. Since the degradation mechanism of the fuel cell is not fully understood, the data-driven method is very suitable for designing degradation prediction models. However, the data-driven method usually requires a lot of data, which is difficult to be obtained. To solve the issues, we propose a degradation prediction model for PEMFC based on long short-term memory neural network (LSTM) and Savitzky-Golay filter in this paper. First, we select the monitoring parameters for building the degradation prediction model by analyzing the degradation phenomenon of the fuel cell. Then, Savitzky-Golay filter is utilized to smooth out the selected data, and the sliding time window is used to generate training samples. Finally, the LSTM is applied to establish the degradation prediction model. Moreover, the dropout layer and mini-batch method are adopted to improve the model generalization ability. We use an actual aging data of the fuel cell to verified the proposed degradation prediction model. The results demonstrate that the proposed model can precisely predict the fuel cell degradation. It is worth mentioning that the determination coefficient (R²) of the test set based on the model trained by 25% of data is 0.9065.     

Prediction of local current distribution in polymer electrolyte membrane fuel cell with artificial neural network

In the development process of a fuel cell, understanding the local current distribution is essentially required to achieve better performance and durability. Therefore, many developers apply a segmented fuel cell to observe current distribution under various operating conditions. With the application, experimental data is collected. This study suggests a utilization method for this collected data to develop a local current prediction model. The details of this neural network-based prediction model are introduced, including the pretreatment of the data. In the pretreatment process, current residual values are used for better prediction performance. As a result, the model predicted local current values with a 2.98% error. With the model, the effects of pressure, temperature, cathode relative humidity, and cathode flow rate on local current distribution trends are analyzed. Since the non-uniform current distribution of a fuel cell often leads to low performances or fast local degradation, the optimal operating condition to achieve current uniformity is acquired with an additional model. This model is developed by switching inputs and outputs of the local current prediction model. With the model application, the uniform current distribution is achieved with a standard deviation of 0.039 A/cm² under the current load at 1 Acm^?2.     

Neural network model of 100 W portable PEM fuel cell and experimental verification

The inherent properties of artificial neural networks (ANNs) such as low sensitivity to noise and incomplete information make the ANN a promising candidate to model the fuel cell system. In this paper, an ANN-based model of 100 W portable direct hydrogen fed proton exchange membrane fuel cell (PEMFC) is presented. The model is built based on experimentally collected data from a portable 100 W direct hydrogen fed PEMFC in the authors’ laboratory. A multilayer feedforward ANN with back-propagation training algorithm is used to model the portable PEMFC. The ANN consists of fully connected four layers network with two hidden layers. The PEMFC ANN model is trained using extracted data from experimentally measured and calculated parameters. To validate the model, the outputs of the PEMFC ANN are compared against experimental data and results from a dynamic model of portable direct hydrogen fed PEMFC. In addition, three statistical indices to measure variations, unbiasedness (precision), and accuracy in voltage, power, and hydrogen flow are used to evaluate the PEMFC ANN model performance. The indices indicate that the maximum variations, unbiasedness, and accuracy of the voltage, power, and hydrogen flow are 1.45%, 2.04%, and 1.90%, respectively, which shows a close agreement between the outputs of the PEMFC ANN and the experimental results.     

Degradation phenomena in PEM fuel cell with dead-ended anode

To improve the performance and durability of a dead-ended anode (DEA) fuel cell, it is important to understand and characterize the degradation associated with the DEA operation. To this end, the multiple degradation phenomena in DEA operation were investigated via systematic experiments. Three lifetime degradation tests were conducted with different cell temperatures and cathode relative humidities, during which the temporal evolutions of cell voltage and high frequency resistance (HFR) were recorded. When the cathode supply was fully humidified and the cell temperature was mild, the cathode carbon corrosion was the predominant degradation observed from scanning electronic microscopy (SEM) of postmortem samples. The catalyst layer and membrane thickness were measured at multiple locations across the cell active area in order to map the degradation patterns. These observations confirm a strong correlation between the cathode carbon corrosion and the anode fuel starvation occurring near the cell outlet. When the cathode supply RH reduced to 50%, membrane pin-hole failures terminated the degradation test. Postmortem analysis showed membrane cracks and delamination in the inlet region where membrane water content was the lowest.     

Survey of sulfonated polyimide membrane as a good candidate for nafion substitution in fuel cell

Studies in fuel cell membranes show that modification of polyimides by introduction of aliphatic linkages in the structure of sulfonated copolyimides, synthesis of branched/crosslinked sulfonated polyimides, and semi and fully interpenetrating polymer networks of sulfonated polyimides restrain suitable potential for Nafion substitution.     

Sensitivity analysis for solid oxide fuel cells using a three-dimensional numerical model

A three-dimensional numerical solver is developed to model complex transport processes inside all components of a solid oxide fuel cell (SOFC). An initial assessment of the accuracy of the model is made by comparing a numerically generated polarization curve with experimental results. Sensitivity derivatives of objective functions representing the cell voltage and the concentration polarization are obtained with respect to the material properties of the anode and the cathode using discrete adjoint method. Implementation of the discrete adjoint method is validated by comparing sensitivity derivatives obtained using the adjoint technique with results obtained using direct-differentiation and finite-difference methods.     

A bibliometric analysis on safety of fuel cells: Research trends and perspectives

Fuel cells, as energy conversion devices, are receiving attention from researchers and developers due to their high efficiency and environmentally friendly characteristics. However, despite the prospect of booming fuel cell development, the overall quality and level of development still need to be improved, and safety is one of the key development indicators. This article presents a scientometric and knowledge network analysis of fuel cell safety based on information from 890 relevant publications in the Web of Science Core Collection. The bibliometric software VOSviewer and Co-Occurrence are used for in-depth analysis and visual presentation of the publication information. The results show that the first publication is released in 1991, and this research field has exploded since 2017. Moreover, the USA and China have the strongest cooperation in this field. The hot areas of fuel cell safety research are focused on five clusters: electrode and catalyst safety, fuel cell electric vehicle safety, hydrogen safety, energy generation and storage safety, and solid oxide fuel cell safety. This article maps the knowledge of research related to fuel cell safety and helps readers gain a quick perspective on the research structure and future directions in this field.