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![2. An exploded view of a polymer electrolyte membrane fuel cell stack [3]](profile/Colleen-Spiegel-2/publication/239837002/figure/fig2/AS:669426504433667@1536615124081/An-exploded-view-of-a-polymer-electrolyte-membrane-fuel-cell-stack-3.jpg)
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![Figure 1.1. A single PEM fuel cell [2]](profile/Colleen-Spiegel-2/publication/239837002/figure/fig1/AS:669426500247559@1536615123966/A-single-PEM-fuel-cell-2_Q320.jpg)
![Figure 1.3. A serpentine flow field design [2]](profile/Colleen-Spiegel-2/publication/239837002/figure/fig3/AS:669426504458241@1536615124125/A-serpentine-flow-field-design-2_Q320.jpg)
![Figure 1.4. A parallel flow field design [2]](profile/Colleen-Spiegel-2/publication/239837002/figure/fig4/AS:669426504433668@1536615124136/A-parallel-flow-field-design-2_Q320.jpg)
![Figure 1.5. Multiple serpentine flow channel design [2]](profile/Colleen-Spiegel-2/publication/239837002/figure/fig5/AS:669426504450048@1536615124154/Multiple-serpentine-flow-channel-design-2_Q320.jpg)
Fuel cells are predicted to be the power delivery devices of the future. They have many advantages such as the wide fuel selection, high energy density, high efficiency and an inherent safety which explains the immense interest in this power source. The need for advanced designs has been limited by the lack of understanding of the transport process...
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This theoretical study of bunches which are hollow in longitudinal phase space is motivated by experimental work performed at the CERN PS Booster where hollow bunches have been made by introducing empty high harmonic buckets into the particle beam prior to capture into the fundamental RF accelerating buckets. A hollow bunch is the superposition of...
Citations
... For high power generation PEM fuel cell stacks, thermal management is crucial [12,13] since about 58% of the fuel energy is converted to heat [14]. Liquid cooling is preferable to air cooling in high power generation PEM fuel cells due to the high cooling capacity of liquids compared to air. ...
Polymer electrolyte membrane (PEM) fuel cells are promising eco-friendly and sustainable power generation technology. Thermal management of these cells is one of the main challenges facing their commercialization. Alumina nanofluids, in addition to others, have been proposed to overcome excess heat generated within the PEM fuel cell stacks. However, most the previous studies investigated the hydrothermal performance of the nanofluids as a function of Reynolds number (Re). It is evident that all parameters must be kept constants except one to examine its effect on the performance. To this end, choosing Re as a parameter (independent variable) is problematic as it is a function not only of nanofluid's velocity, but also its density and viscosity. In this study, a well-validated CFD model has been built to simulate the hydrothermal performance of alumina nanofluids of different volumetric concentrations (0%, 0.05%, 0.1% and 0.2%) as functions of Re (170 < Re < 530), flow rate (20 ml/min ≤ Vf ≤ 50 ml/min), and pumping power (0.025 mW < Pp < 0.3 mW). This study shows a maximum reduction of 7.9% in the thermal effectiveness and a maximum increase of 6% in the pumping power when using the nanofluids instead of water. This deterioration in the hydrothermal performance is due to the reduction in the effective specific heat capacity and increase in viscosity of the nanofluids. Also, it is concluded that it is incorrect to use Re as an independent variable in analysing the hydrothermal performance of nanofluids because of the dependency of Re on some of the thermophysical properties of the nanofluids, which are functions of the concentration. Adopting such analysing procedure leads to false conclusions.
... A change in RH at constant temperature leads to a linear change in ionic conductivity. Proton conductivity (r) in polyelectrolytes (e.g., Nafion) also depends on temperature ðrT ¼ r 0 e Ea kT Þ and the hydrophilic volume fraction, r * (u-u c ) 2 (Choi et al. 2005;Spiegel 2008). This volume fraction has also been seen to share a quadratic relation with the diffusion of water molecules, D w $ u 2 (Choi et al. 2005;Jalal et al. 2017b). ...
... The diffusion of H ? ions is governed by the Grotthuss mechanism, en masse diffusion, and surface diffusion. Hence, the overall membrane conductivity, r H? is found from the Nernst's equation as follows (Spiegel 2008): ...
A proton exchange membrane (PEM) fuel cell-based wearable alcohol sensing device has been explored for the monitoring of blood alcohol content (BAC) in real time. The watch-like alcohol monitoring device detects alcohol from the perspiration of the human skin. This transcutaneous (transdermal) fuel cell sensor can detect a wide range of concentrations of alcohol, including a physiological range of concentration (5–100 mg/dl), with the detection time of ~ 5 s. A calibration model, such as principal component regression (PCR), was implemented to reduce standard errors and refine the calibration of this sensor by offsetting noise. The BAC values from the transcutaneous sensor were closer to the theoretical values, with 77.47% improvement in accuracy compared to readings from off the shelf breathalyzer. The results from human studies demonstrate that this fuel cell sensing device in accompany with the proposed PCR model can be employed for the determination of BAC through transcutaneous measurements.
... Spiegel. [7], presented that energy components were predicted to be the power delivery devices of the future. The developed model was made by MATLAB. ...
... It varies in both through-plane and in-plane directions. There still exists a significant discrepancy in the understanding of distribution of entropic heat generation in the through-plane direction [48,49]. Due to the interdependence of the local current density, temperature, reactant concentration and water content, the local heat generation is usually non-uniform in the in-plane direction. ...
In an effort to reduce the environmental impact of the energy sector that is mostly based on fossil fuels, researchers are looking for a clean alternative of our existing energy sources. Hydrogen Energy and Fuel Cells, and in particular Polymer ElectrolyteMembrane Fuel Cells (PEMFCs) have emerged as a leading candidate for transportation as well as stationary and portable applications. Due to the irreversibility of the electrochemical reactions and ohmic heating in the fuel cell components, the PEMFC produces a significant amount of heat and this heat has to be removed in order to avoid cell or stack overheating. In this paper, a review of the key heat transfer mechanisms and the various cooling strategies that are available for heat removal from PEMFCs are presented. Due to the interrelated nature and difficulty of conducting in-situ thermal measurements on the operating PEMFCs, computational modelling provides a fast and efficient way of designing PEMFC cooling systems and understanding the heat transfer mechanisms. Therefore PEMFC thermal modelling is also highlighted together with present challenges and potential areas for further research and development works.
In this paper, a new nature-inspired Artificial Ecosystem Optimization (AEO) methodology is presented for reducing the complexity of nonlinear PEMFC SR-12 500 W system. From the point view of this system, the hydrogen and oxygen pressures P H2 ¼ 60 atm, P O2 ¼ 30 atm as two inputs, the cell voltage and current as two outputs.By implementation of identification technique, the state space model of PEMFC stack is generated using nlarx modelling procedures where the obtained model is reduced their order by AEO method. The AEO mimics the energy flow behaviour between living organisms in a natural ecosystem, including production, consumption, and decomposition.This algorithm minimize the synergy (H 2 ; H 1) norm of error between full PEMFC model and reduced order model. The obtained results are compared with the other optimization algorithms such as MRFO,S-SA,ALO and GWO, and they are confirmed that the approximate model obtained by proposed algorithm has faster convergence and better approximation performance in synergy (H 2 ; H 1) norm than those obtained by comparative algorithms in addition, it is proven to be accurate and reliable to investigate the PEMFC optimum global reduced order model which preserved the main behaviour of original PEMFC SR-12 500 W model.
This chapter aims to present the implementation and real time simulation stages of a PEM fuel cell using OPAL-RT technology. The following topics are presented: OPAL-RT technology, real-time simulation, conditions regarding the implementation of a mathematical model from Simulink/MATLAB in the RT-LAB platform using the OPAL-RT technology. Through the developed mathematical models, the authors can optimize the fuel cells, but also the integration of monitoring and control systems with the purpose of real time visualization of parameters as well as data acquisition using CAN, data storage and processing. The physical mathematical equations of the model were implemented in a programming language, in the form of code or block diagram, in order to be simulated in real-time. The advantages of real-time simulation of the mathematical models developed in the research projects are characterized by three decisive factors: speed of implementation, development flexibility and results predictability. The originality of the method is that the model can be simulated in real time (HIL) using an OPAL-RT architecture.
The aim of this study is to analyze the exergy efficiency of a high‐temperature proton exchange membrane fuel cell. To do this purpose, meta‐heuristic technique has been used. First, the model of a membrane fuel cell is simulated and the polarization diagram shows a potent agreement with empirical data. Then, a new improved version of collective animal behavior algorithm is utilized for evaluating and optimizing the thermodynamic irreversibility, exergy efficiency, and work of the fuel cell. The algorithm uses opposition‐based learning and Lévy flight for improving the algorithm's premature convergence shortcoming. The result of this study shows that by comparison with standard collective animal behavior algorithm, genetic algorithm, and empirical results, the proposed algorithm has better achievements for both terms of optimal value finding and convergence strength.
