1,721,014 research outputs found
Design optimization of proton exchange membrane fuel cell bipolar plate
No full textThe bipolar plate geometry design is one of the fuel cell's key features that determines the cell's power. It equally has a direct correlation to the thermal and water management of the cell as it tends to regulate the amount of by-product water that can be expunged from the fuel cell. This study, therefore, explored the development of novel bipolar plate geometry designs, namely the square baffled channel, the rectangular baffled channel, the parallel channel design, and the double serpentine geometry design. This was further compared with the traditional serpentine design to ascertain the design with the optimum fuel cell performance. With the squared baffled channel presenting the best results, varying operating conditions that will influence the performance of the novel fuel cell channel design were also evaluated. It was observed that the hydrogen mass fraction increased by 22.6% for the square baffled channel design compared with the other geometry designs considered in the present study. The square baffle channel showed 12.11% increase in power density and 14.54% increase in current density compared to the rectangular baffle channel. In terms of the parallel channel design, the square baffle showed 18.941% increase in power density and 22.278% increase in current density. The least performing channel geometry design was the double serpentine design. Comparing the double serpentine channel geometry design to the square baffle channel geometry design, there was an increase in current density by 67.72% and 77.88% in terms of power density in favour of the square baffle channel geometry design. The square baffle channel also showed 50% increase in current density and 58.23% increase in power density compared to conventional serpentine channel flow plate geometry design. An adaptive neuro fuzzy inference system (ANFIS) was also adopted to predict the output power of the cell. This was then compared with Feed Forward Back Propagation Neural Network to determine the model with the most accurate results. The adaptive neuro-fuzzy inference model accurately predicted the non-linearities associated with fuel cell performance, hence recommended as ideal for Proton Exchange membrane fuel cell prediction. The main contribution for the study is the development of optimal flow plate geometry design that will ensure maximum fuel cell performance. The current study is aimed at providing technical information to policy makers and the fuel cell industry on how optimization of the flow plate design via the introduction of baffles could increase the cell performance hence accelerates its commercialization and widen their applications in various sectors beyond the automotive industry
Advances in stationary and portable fuel cell applications
Get PDFThe reliance on fossil fuels is one of the most challenging problems that need to be dealt with vigorously in recent times. This is because using them is not sustainable and leads to serious environmental issues, such as: air pollution and global warming. This condition affects economic security and development. An alternative to fossil fuel is highly possible which will be more environmentally friendly, sustainable and efficient as well. Among all the different technologies associated with renewable energy, fuel cell technologies represent one of the most promising technological advancement to curb the situation. In this paper, an overview of the technology and its advantages and disadvantages compared with competitive technologies was revealed. The application of different fuel cell types in the stationary and portable sectors was covered. Furthermore, recent challenges
and promising developments of current fuel cell technologies in different studied applications were reviewed. Some possible solutions to the challenges were named in this paper for both the portable and stationary fuel cell applications. The paper further seeks to
expose the world to the current progress made in the fuel cell industry up to date and possible areas that needs intensified research and modifications to make the fuel cell industry more vibrant and buoyant
A study into Proton Exchange Membrane Fuel Cell power and voltage prediction using Artificial Neural Network
Get PDFPolymer Electrolyte Membrane fuel cell (PEMFC) uses hydrogen as fuel to generate electricity and by-product water at relatively low operating temperatures, which is environmentally friendly. Since PEMFC performance characteristics are inherently nonlinear and related, predicting the best performance for the different operating conditions is essential to improve the system\u27s efficiency. Thus, modeling using artificial neural networks (ANN) to predict its performance can significantly improve the capabilities of handling multi-variable nonlinear performance of the PEMFC. This paper predicts the electrical performance of a PEMFC stack under various operating conditions. The four input terms for the 5 W PEMFC include anode and cathode pressures and flow rates. The model performances are based on ANN using two different learning algorithms to estimate the stack voltage and power. The models have shown consistently to be comparable to the experimental data. All models with at least five hidden neurons have coefficients of determination of 0.95 or higher. Meanwhile, the PEMFC voltage and power models have mean squared errors of less than 1 × 10--3 V and 1 × 10--3 W, respectively. Therefore, the model results demonstrate the potential use of ANN into the implementation of such models to predict the steady state behavior of the PEMFC system (not limited to polarization curves) for different operating conditions and help in the optimization process for achieving the best performance of the system
Dynamic modelling and analysis of Organic Rankine Cycle power units for the recovery of waste heat from 110kW Proton Exchange Membrane Fuel cell system
Get PDFThe recovery of waste heat from Proton Exchange Membrane (PEM) Fuel cell is sin qua non to the development of organic Rankin cycle units. Despite the appreciable increase in the sale of PEM fuel cell units in 2021, the waste heat from some of these fuel cell units is typified by large fluctuations in mass flow rate as well as temperature which is more likely to affect the overall performance of an organic Rankine cycle (ORC) unit when coupled to a fuel cell. It is therefore imperative that the dynamic modelling of the Proton Exchange Membrane Fuel cell and organic Rankine cycle integrated system is developed to analyse the performance of the integrated system. This also involves the development of an appropriate control strategy for guaranteeing safer and optimum performance of the integrated system. The developed Proportional, Integral, Derivative (PID) control unit is able to maintain the thermal efficiency of the ORC system at 10% subject to the mass flow rate of the waste heat as well as the working fluid and also ensure safe operation of the integrated system. There is a 0.9% increase in the output power of the PEMFC after 2000 seconds of operation clearly highlighting the contribution of the integrated system in improving the overall output power being harnessed
Dynamic thermal model development of direct methanol fuel cell
Get PDFDirect methanol fuel cell (DMFC) is fueled with liquid methanol coupled with air to produce power at reasonably lower operational conditions while resulting in by-products of carbon dioxide and water, which is more environmentally friendly. Due to the complexity associated with the performance of direct methanol fuel cell, the application of artificial neural network (ANN) can significantly predict the characteristic performance of the cells. Nevertheless, limited studies have delved into the exploration of artificial neural network in the prediction of the transient characteristics of direct methanol fuel cells. The current study however presents a detailed investigation into the prediction of the dynamic thermal characteristics of a direct methanol fuel cell stack subjected to varying operational environment. Parameters considered in the study as input include methanol concentration, anode as well as cathode inlet flow rates, coupled with current. Outcomes for the artificial neural network models for three varying learning algorithms were ascertained for anode and cathode temperatures, which were forecasted closely by models with higher number of hidden neurons. Such models have coefficients of determination of 0.95 or more and mean square error less than 0.04. Thus, the outcome of the study presents prospects for artificial neural network methods as optimum control approach in direct methanol fuel cell development
Technical and Commercial Challenges of Proton-Exchange Membrane (PEM) Fuel Cells
Get PDFThis review critically evaluates the latest trends in fuel cell development for portable and stationary fuel cell applications and their integration into the automotive industry. Fast start-up, high efficiency, no toxic emissions into the atmosphere and good modularity are the key advantages of fuel cell applications. Despite the merits associated with fuel cells, the high cost of the technology remains a key factor impeding its widespread commercialization. Therefore, this review presents detailed information into the best operating conditions that yield maximum fuel cell performance. The paper recommends future research geared towards robust fuel cell geometry designs, as this determines the cell losses, and material characterization of the various cell components. When this is done properly, it will support a total reduction in the cost of the cell which in effect will reduce the total cost of the system. Despite the strides made by the fuel cell research community, there is a need for public sensitization as some people have reservations regarding the safety of the technology. This hurdle can be overcome if there is a well-documented risk assessment, which also needs to be considered in future research activities
Performance analysis of a vertical axis wind turbine using computational fluid dynamics
Get PDFVertical axis wind turbines (VAWTs) have gained popularity in the last few decades due to their numerous advantages when deployed in urban areas. Despite this, Vertical axis wind turbines have complex aerodynamics, dynamic stall, hence lower performance. Low/zero starting torque, noise, visual impact, as well as blade safeness are further hurdles when they are fitted into the physical environment. Due to these pertinent issues that comes to play in a vertical axis wind turbine, the current investigation explores an augmented vertical axis wind turbine (AVAWT) having a rotor and a stator. The outcome of the study highlighted the effect of mesh density and the type of turbulence model selected in the determination of the forces being exerted on the blade using computational fluid dynamics. Investigation into the effect of time steps showed lesser effect of this parameter on the performance of the blade computationally. The newly developed augmented turbine blades improved the output power by 1.35 times in comparison to an open rotor. The shape for the conical surface and the stator blade impacted the performance as well. Furthermore, it was deduced that there was higher dynamic stall for scenarios where the tip speed ratios were lower. The study showed the importance of the stator in a vertical axis wind turbine in ensuring that the incoming wind attains some acceleration as well as creating a lower pressure outlet but overall aids in the improvement of the power and torque coefficients by more than 36%
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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