Fuel crossover and internal current in proton exchange membrane fuel cell modeling

Chakraborty, Uttara

doi:10.1016/j.apenergy.2015.11.012

Cited by 32 publications

(11 citation statements)

References 18 publications

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“…During fuel cell operation, only the same ions (protons or OH − -ions) are generated [ 52 , 53 , 54 ]. Nevertheless, even in this case, it is necessary to limit gas diffusion through the membrane as much as possible, which determines the so-called fuel crossover—the undesired passage of fuel, not accompanied by energy production [ 55 , 56 , 57 ]. The ratio of fluxes of desired and undesired components determines the value of selectivity, which is one of the most important membrane operating parameters [ 37 , 58 ].…”

Section: Introductionmentioning

confidence: 99%

Ionic Mobility in Ion-Exchange Membranes

Стенина

Yaroslavtsev

2021

Membranes

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Membrane technologies are widely demanded in a number of modern industries. Ion-exchange membranes are one of the most widespread and demanded types of membranes. Their main task is the selective transfer of certain ions and prevention of transfer of other ions or molecules, and the most important characteristics are ionic conductivity and selectivity of transfer processes. Both parameters are determined by ionic and molecular mobility in membranes. To study this mobility, the main techniques used are nuclear magnetic resonance and impedance spectroscopy. In this comprehensive review, mechanisms of transfer processes in various ion-exchange membranes, including homogeneous, heterogeneous, and hybrid ones, are discussed. Correlations of structures of ion-exchange membranes and their hydration with ion transport mechanisms are also reviewed. The features of proton transfer, which plays a decisive role in the membrane used in fuel cells and electrolyzers, are highlighted. These devices largely determine development of hydrogen energy in the modern world. The features of ion transfer in heterogeneous and hybrid membranes with inorganic nanoparticles are also discussed.

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Section: Introductionmentioning

confidence: 99%

Ionic Mobility in Ion-Exchange Membranes

Стенина

Yaroslavtsev

2021

Membranes

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“…For conformity with the treatment in Ref. [42] (this is a primary reference against which comparative results are studied later in this paper), however, the expression for V stack in Equation (9) retains the inexact inclusion [48] of i n,den in the calculation of the ohmic loss term. Table 1 shows the values of the cell parameters used in this problem.…”

Section: Problem Statementmentioning

confidence: 88%

“…where r area is the area-specific resistance. Losses also occur because of the leakage of fuel through the electrolyte and because of internal currents [48]. This type of loss is usually modeled by an additional component of current, called the fuel crossover and internal current.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…where i n,den is an additional component of current density brought into the equation to account for the combined effect of fuel crossover and internal current. The fuel crossover and internal current (the "leakage" or "lost" current) does not "flow" through the same path that the "regular" current follows [48], and therefore the ohmic loss for a cell should be modeled by the expression i load,den /N p × r area . For conformity with the treatment in Ref.…”

Section: Problem Statementmentioning

confidence: 99%

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Proton Exchange Membrane Fuel Cell Stack Design Optimization Using an Improved Jaya Algorithm

Chakraborty

2019

Energies

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Fuel cell stack configuration optimization is known to be a problem that, in addition to presenting engineering challenges, is computationally hard. This paper presents an improved computational heuristic for solving the problem. The problem addressed in this paper is one of constrained optimization, where the goal is to seek optimal (or near-optimal) values of (i) the number of proton exchange membrane fuel cells (PEMFCs) to be connected in series to form a group, (ii) the number of such groups to be connected in parallel, and (iii) the cell area, such that the PEMFC assembly delivers the rated voltage at the rated power while the cost of building the assembly is as low as possible. Simulation results show that the proposed method outperforms four of the best-known methods in the literature. The improvement in performance afforded by the proposed algorithm is validated with statistical tests of significance.

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“…As a result, membranes lose proton conductivity due to poor mechanical stability [59][60][61] High temperatures are also known to cause a significant increase in fuel crossover. Hydrogen crossover is a major problem in both fuel cell and solar fuel technologies [3,62]. Increased levels of relative humidity (RH) is yet another substantial disadvantage of Nafio n® membranes.…”

Section: Energy Conversion and Storagementioning

confidence: 99%

Graphene Membranes: Transport Properties and Energy Applications

Chabi

2021

MAMS

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Graphene materials are increasingly being used in all types of membrane-based technologies ranging from water purification to energy conversion systems such as fuel cell and solar fuel technologies. Graphene's physical and chemical richness enables a variety of mass transport mechanisms that are impossible in traditional membranes. These mechanisms are dictated by the graphene microstructure and its versatility which leads transport to occur via pores, sub-nanometer pores, or via nanochannels. Graphene membranes can be designed to create nanochannels that allow highly selective ion or gas transport by biomimicking naturally occurring biological systems. However, these potentials cannot be fully explored without understanding the interplay between graphene microstructures and the transport mechanism. Toward taking advantage of graphene membrane technology, a fundamental understanding of the mass transport mechanisms is necessary. In this Review, we provide an in-depth discussion about three different types of mass transport through graphene nanopores and graphene nanochannels. By focusing on the relation between nanopores/channels chemistry e.g. effect of functional groups and pore polarity and transport mechanism, we identify key lessons, challenges, and potential solutions to empowering membrane-based energy technologies.

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Fuel crossover and internal current in proton exchange membrane fuel cell modeling

Cited by 32 publications

References 18 publications

Ionic Mobility in Ion-Exchange Membranes

Ionic Mobility in Ion-Exchange Membranes

Proton Exchange Membrane Fuel Cell Stack Design Optimization Using an Improved Jaya Algorithm

Graphene Membranes: Transport Properties and Energy Applications

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