Mench M.M. Fuel Cell Engines

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450 Hydrogen Storage, Generation, and Delivery

8.9 Would isothermal or nonisothermal compression with

continually increasing temperature be desirable to achieve

high-efﬁciency gas compression? Would you want an insu-

lated or cooled compressor?

8.10 Determine the fraction of throughput energy required

to compress hydrogen gas from 0.1 to 70 MPa assuming

an isothermal, ideal gas compression process. How would

nonideal gas effects affect the result?

8.11 What is the fraction of throughput energy lost to

compress liquid hydrogen from 0.1 to 30 MPa for pipeline

delivery? How does this compare to the fraction of through-

put energy lost to compress gas-phase hydrogen from 0.1 to

30 MPa for pipeline delivery?

8.12 Consider the use of on-board methanol or ethanol

storage for automotive PEFC applications. The methanol

or ethanol would be reformed on-board and sent to the fuel

cell. What minimum storage tank volume and weight would

be needed to replace a conventional 15-gal gasoline tank in

terms of energy for each of these fuels? How does this com-

pare to a metal hydride hydrogen storage tank that stored

4 wt. % hydrogen?

8.13 Consider a hydrogen production plant using electrol-

ysis for hydrogen production. If the electrolysis is 65%

efﬁcient and the automotive PEFC is 90% efﬁcient in trans-

mitting the PEFC power to propulsion, draw a plot of the net

process efﬁciency versus output cell voltage for the 200-cell

fuel cell stack. Compared to an internal combastion engine

efﬁciency of 25%, what is the lowest stack voltage where

the net efﬁciency of the hydrogen–air fuel cell is still higher

than the conventional automobile?

8.14 The estimated throughput loss of shipping pressurized

hydrogen a distance of 2000 km by pipeline is 8% output

for 480-TWh/year ﬂow. What fraction of throughput en-

ergy would be lost if this hydrogen was instead shipped by

truck at 120 km/L of gasoline. You can assume a normal

hydrogen delivery truck carries 530 kg in the gas phase, or

3370 kg in the liquid phase.

8.15 The expected hydrogen storage density in carbon is

directly proportional to surface area. Create a plot of diam-

eter of carbon spheres versus surface area if the carbon is a

packed bed of perfect spheres. Can a surface area of 3000

/g be achieved with spherical particles? Would nonspher-

ical geometries be better for hydrogen storage?

8.16 Aluminum combustion in water has been considered

as a carbon-free source of hydrogen. The enthalpy of for-

mation of aluminum oxide is −1675.7 kJ/mol:

Al +

O →

+ heat

Since the reaction is also very exothermic, the heat could

potentially be used to run a steam turbine and generate

electricity. For this problem, determine the kilograms of

hydrogen per kilogram of aluminum used and try to de-

termine the cost of hydrogen production per kilojoule of

hydrogen produced (use the LHV) using online sources.

Assume it takes about 7 kWh of energy to manufac-

ture a pound of aluminum. Is this a potentially compet-

itive way to produce hydrogen (ignoring the technical

challenges)?

8.17 Compare ﬂammability and health safety risks that

hydrogen, methanol, gasoline, and ethanol pose. You can

ﬁnd this information in material safety data sheets avail-

able online from various manufacturers. Is there a “safe”

fuel?

REFERENCES

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Applications, Vol. 3, W. Vielstich, A. Lamm, and H. A. Gasteiger, Eds., Wiley, New York, 2003,

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New York, 2003, pp. 89–100.

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ohlein, “Methanol from Fossil and Renewable Sources,” in

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announcement, DOE, Washington, DC, October, 2006.

14. J. L. C. Rowsell and O. M. Yaghi, “Effects of Functionalization, Catenation, and Variation of the

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of Metal-Organic Frameworks,” J. Am. Chem. Soc., Vol. 128, pp. 1304–1315, 2006.

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porous Metal-Organic Frameworks,” J. Am. Chem. Soc., Vol. 128, pp. 3494–3495, 2006.

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17. P. Eklund, T. C. M. Chung, H. C. Foley, and V. H. Crispy, “Advanced Boron and Metal-Loaded

High Porosity Carbons,” DOE Hydrogen Program Annual Progress Report, Department of

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Nanoscale Porosity in Carbide-Derived Carbons for Hydrogen Storage,” J. Am. Chem. Soc.,

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alized Metal-Organic Frameworks,” J. Am. Chem. Soc., Vol. 126, pp. 5666–5667, 2004.

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Department of Energy, Washington, DC, 2006, pp. 515–517.

21. B. A. Peppley, J. C. Amphlett, and R. F. Mann, “Catalyst Development and Kinetics for Methanol

Fuel Processing,” in Handbook of Fuel Cells—Fundamentals, Technology and Applications,

Vol. 3, W. Vielstich, A. Lamm, and H. A. Gasteiger, Eds., Wiley, New York, 2003, pp. 132–148.

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in Handbook of Fuel Cells—Fundamentals, Technology and Applications, Vol. 3, W. Vielstich,

A. Lamm, and H. A. Gasteiger, Eds., Wiley, New York, 2003, pp. 62–77.

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Experimental Diagnostics

and Diagnosis

There have already been two oil crises; we are obligated to prevent

a third one. The fuel cell offers a realistic opportunity to supplement

the “petroleum monoculture” over the long term. All over the

world, the auto industry is working in high gear on the fuel cell.

We intend to be the market leader in this ﬁeld.

—J

urgen Schrempp, Chairman of the Board of Management,

DaimlerChrysler, November 2000

At this point the reader should be very familiar with the polarization curve and the basic

analytical approaches used to model the various polarization losses. Each of the analytical

models for these losses requires some material, transport, or other parameters to solve. In

a textbook problem, these values are simply given. In practice, however, while some basic

transport parameters are well established, there is often a need to experimentally measure

many of these parameters as new materials or diagnostic techniques become available.

For design optimization, it is especially useful to delineate the losses which affect our

polarization curve as a function of operating conditions, including the following:

1. Reactant Crossover The equivalent crossover current density or molar ﬂow rate

of crossover is desired.

2. Kinetic Losses on Anode and Cathode The exchange current density, electrochem-

ically active surface area (ECSA), and catalyst utilization are desired.

3. Ohmic Losses The ionic and electrical transport losses are desired.

4. Mass Transport Losses The gas-phase transport and ﬂooding losses (PEFC) and

the other transport-based limitations affecting the voltage are desired.

Additionally, we seek diagnostic tools to understand how the fuel cell performance varies

with the location in an individual fuel cell and between fuel cells in a stack. Spatial and

cell-to-cell variations in current, temperature, reactant concentration, and other parameters

occur, especially at moderate to high currents and during load transients, and tools are

needed which can measure or directly observe these effects. In an operating stack, the

number of sensors are limited due to various cost and size constraints, but laboratory

diagnostics are very sophisticated. To understand distributed effects such as ﬂooding in

PEFCs or temperature distribution in SOFCs, direct visualization tools and sensors are

453

Fuel Cell Engines

Matthew M. Mench

c09 JWPR067-Mench December 16, 2007 15:15 Char Count=

454 Experimental Diagnostics and Diagnosis

necessary to understand the various phenomena and optimize performance and durability.

Taken together, the various diagnostic tools available are used to develop predictive models,

optimize material selection and design, and identify the source of performance anomalies.

Finally, besides beginning-of-lifetime performance, tools are needed to diagnose the source

of physicochemical degradation modes which limit operational lifetime. Both in situ (in

cell) and ex situ (outside of a fuel cell) techniques are needed as well.

9.1 ELECTROCHEMICAL METHODS TO UNDERSTAND

POLARIZATION CURVE LOSSES

A wide variety of steady and transient, in situ and ex situ, AC and DC methods have been

developed to study electrochemical system behavior. To fully understand and apply these

techniques requires a greater depth than the brief summary in this chapter can provide. For a

more detailed explanation, the reader is referred to various texts devoted to electrochemical

testing techniques, such as by Bard and Faulkner [1]. This chapter is designed to serve as

an introduction to the potential techniques available to obtain a greater understanding and

parameterization of the various polarization losses.

9.1.1 Experimental Determination of Kinetic Parameters

and Polarization

Electrochemical Impedance Spectroscopy A commonly used technique for delineating

some polarizations, electrochemical impedance spectroscopy (EIS), is used to study many

complex problems in electrochemistry such as corrosion or the kinetics of a given elec-

trode reaction. Advanced laboratory equipment for this purpose is readily available. In

each fuel cell, the total voltage loss at a given current density is a result of a combina-

tion of ohmic and nonohmic contributions. The ohmic contributions, such as ionic and

electronic ohmic resistance in the electrolyte and through the other components, can be

studied using direct current (DC) techniques. However, the nonohmic contributions, such

as adsorption processes at the electrodes, the charge transfer across the double layer, and the

kinetically based concentration polarization, normally have frequency-dependent response

times which make them ideal for study using alternating current (AC) techniques. Applying

an AC signal of varying frequency over the electrochemical reaction interface causes the

electrode–electrolyte interface and redox couple (e.g., H

) to oscillate with the same

applied frequency. The characteristic response of the redox couple to the applied oscillation

frequency can be used to discern qualitative details of the kinetics and concentration polar-

ization behavior at the electrode. Electrochemical impedance spectroscopy can be applied

to a single electrode if a reference electrode is available or used to study the overall behavior

of the electrochemical cell, including the anode and cathode. In fuel cells, it is most often

applied to study the overall system response so that information on the charge transfer and

concentration polarization processes can be gleaned.

The EIS data can be utilized to gain a wealth of information on the ohmic, charge

transfer, and mass transfer resistances using an equivalent circuit or a ﬁrst-principles-based

modeling approach. Consider the equilibrium charge transfer process occurring at a single

electrode in a fuel cell, shown in Figure 9.1.

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9.1 Electrochemical Methods to Understand Polarization Curve Losses 455

Figure 9.1 Simpliﬁed illustration of ion exchange process across single electrode.

The charge transfer can be modeled by an equivalent electrical circuit, the most basic

of which is illustrated in Figure 9.2. In the electrochemical circuit, there is an electrical

resistance, an ionic resistance, and a charge transfer resistance that represent the losses

associated with ion transfer through the catalyst and surface, the electrolyte, and across the

double layer, respectively.

There is also an equivalent capacitor and inductance associated with the charge transfer

process across the charge double layer. In the basic equivalent circuit shown in Figure 9.2,

the electrode is treated as a ﬂat planar charge transfer surface. In a fuel cell, the electrode

is normally a highly three-dimensional porous surface with many parallel charge transfer

pathways. In this case, a more complicated line transmission model can be used, where

the planar charge transfer circuit is replaced with many such circuits acting in parallel and

representing each element of the porous electrode as shown in Figure 9.3 [2].

The equivalent circuit can be expanded to consider the entire fuel cell. Figure 9.4 is an

illustration of the charge transfer and current transport process through both electrodes in

a fuel cell. A simpliﬁed equivalent circuit for this is shown in Figure 9.5.

At this point it should be cautioned that the equivalent circuit approach can yield

detailed information of the physicochemical processes of ohmic, mass transfer, and ki-

netic resistances for a given system, but it is subject to the assumptions of the equivalent

circuit used. That is, the use of equivalent circuit analysis offers inﬁnite possibilities and

combinations of electrical circuits which all can be rearranged in different ways. The EIS

diff

+ i

metal

elyte

diff

Figure 9.2 Basic equivalent circuit used to model electrode in Figure 9.1.

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456 Experimental Diagnostics and Diagnosis

+ i

i i

+ i

Single Particle

Figure 9.3 Line transmission model used to emulate characteristics of porous electrode (based on

[2]).

Figure 9.4 Simpliﬁed illustration of ion exchange process across both electrodes in an electro-

chemical cell.

anode

diff

cathode

diff

+ i

elyte

+ i

Figure 9.5 Basic equivalent circuit used to model electrochemical cell in Figure 9.4.

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9.1 Electrochemical Methods to Understand Polarization Curve Losses 457

Imaginary Impedance

Real Impedance

High

frequency

region –

ohmic

resistances

Medium

frequency

region –

charge

transfer

resistances

Low

frequency

region –

mass

transfer

resistances

Figure 9.6 Generalized Nyquist plot for fuel cell showing general regions of polarization losses.

software will solve for many different outcomes depending on the circuit chosen, so to

some extent the output is only as reliable as the input model chosen. Additionally, the

different capacitive and ohmic resistances often overlap each other, making interpretation

more difﬁcult. Sometimes several properties and processes are lumped in a single element

so that only partial understanding is possible. Therefore, this approach should be viewed

only as a semiquantitative tool to help discern modes of polarization loss, since the results

depend on the particular equivalent circuit used to model the electrode processes.

Despite the limitations of the equivalent circuit approach, in many cases it is possible to

separate the contribution from individual processes to the overall cell resistance. A Nyquist

plot

of the imaginary versus real impedance can be used to map out and determine the

limiting polarization behavior, as shown in Figure 9.6. At high frequencies (on the left side

of the ﬁgure), the imaginary axis intercept represents the ohmic resistance. This value is

called the high-frequency resistance (HFR) of the system, discussed later in this chapter,

and includes all of the ohmic resistances in the system (i.e., the contact losses, the ionic

losses in the electrolyte, and electronic resistances). In the midrange AC frequency region,

the semicircle response is a result of charge transfer resistance across the electrochemical

double layer. The half-circle diameter is the charge-transfer resistance. A worse electrode

would have a larger semicircle. Note that for a full cell there is a charge transfer resistance

at the anode and cathode, so that two semicircles often overlap, and it can be difﬁcult to

separate the two. At very low frequencies (the right side of the Nyquist plot), the mass

transport resistances dominate the response. Other effects such as parallel charge transfer

reactions at a given electrode or parallel limiting transport modes with the same order of

magnitude can convolute the results. The actual EIS response can be very different from

the perfect semicircles predicted for simpliﬁed circuits, however. In particular, phenomena

The reader is referred to introductory texts from electrical engineering or control theory for greater detail on

Nyquist and related plots.

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458 Experimental Diagnostics and Diagnosis

with overlapping frequency responses complicate results, and the effects of the porous or

partially ﬂooded electrode make perfect ﬁtting with physical relevance very challenging.

The effectiveness of EIS can be greatly enhanced with the use of a reference electrode,

which has a stable potential at the time of measurement [3]. A suitable reference electrode al-

lows discernment of the different electrode losses from the overall cell response, resulting in

a more appropriate equivalent circuit. Ideally, the collective responses of the anode and cath-

ode will add to the full cell resistance. Because the use of a stable reference electrode in many

fuel cell systems is difﬁcult, one common way to examine fuel cell behavior is the use of

a dynamic hydrogen electrode (DHE). In this case, one of the electrodes is used as the

DHE, with hydrogen ﬂow at this location. It is assumed that the losses associated with the

DHE are minor, and all polarizations measured can be attributed to the other electrode.

This approach can be dubious and is not appropriate when there are phenomena at the DHE

that can affect losses, such as anode dryout in a PEFC. Note that the DHE does not have to

be the actual anode in the fuel cell but can be used at either electrode to examine the

polarization of the opposing electrode. For example, a DHE can be used at the cathode

of a DMFC to examine the polarization behavior of the anode in the DMFC. In this case,

of course, the reaction does not galvanically proceed in the desired direction, and external

power from a galvanostat/potentiostat system must be applied to drive the reaction in the

desired direction.

Modern EIS test systems are equipped with an equivalent circuit analysis software

capability, greatly simplifying data analysis. The EIS analysis can be conducted on an

individual electrode or on a full fuel cell for qualitative comparison of the various losses

between different materials, electrodes, fuel cell design, or operating conditions. Note that

ﬁtting the EIS data to a given electrical circuit does not guarantee the model is correct, only

that the data ﬁt the assumed model.

A more fundamental approach to EIS data interpretation is based on ﬁrst principles

and attempts to describe the frequency response data directly from analytical models. Both

single- electrode and full-cell models have been developed to describe observed EIS data

for fuel cells, with successful explanation of some of the EIS response [e.g., 3–10]. This

approach has the ultimate goal of being able to fully predict the EIS response for a given

electrode conﬁguration, so that optimal surfaces can be developed. While the end goal is

ultimately more fundamental than the equivalent circuit approach, the complexity involved

with the porous and partially ﬂooded electrode structures found in fuel cells has precluded

its extensive application.

Cyclic Voltammetry Cyclic voltammetry (CV) is perhaps the most widely used electro-

chemical technique and is frequently applied for the initial characterization of a redox

system. It can provide information about the number of oxidation states as well as qual-

itative information about the stability of these oxidation states and the electron transfer

kinetics. In particular, CV provides quantiﬁcation of redox potentials of the electroactive

species and convenient evaluation of the effect of different materials, morphology, or op-

erating environments upon the redox process. In fuel cell studies, the CV is nondestructive

and does not require the fuel cell to be disassembled during operation. Cyclic voltammetry

has been used for the following purposes in fuel cell study:

1. To delineate the reactions on an electrode surface as a function of electrode voltage.

2. To determine the ECSA of an electrode.

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9.1 Electrochemical Methods to Understand Polarization Curve Losses 459

3. To determine the presence of adsorbed surface poisons and to identify the effective-

ness of various catalyst combinations in tolerance to impurities.

4. To study performance dependence on crystal lattice structure and particle size of

the catalyst.

5. To study the catalyst degradation as a function of time, environmental conditions,

or service life.

Cyclic voltammetry can be used for other measurements as well, including ex situ

studies of a single electrode. The general principle of the CV measurement is that the

electrode of interest undergoes a steady voltage potential sweep from a low potential to a

high potential and the resulting current generated at the electrode is measured. From the

plot of the resulting electrode current versus the potential (a voltammogram), detail about

the surface reactions for the electrode can be deduced. The sweep rate of the electrode

is important and must be chosen to properly resolve the various electrode reactions while

being reasonable. In PEFCs, a sweep rate of around 50 mV/s is typical [11]. There are

generally two time constants involved, the time constant for the double layer to charge and

that for the various faradaic reactions to take place. Both double-layer and faradaic reaction

processes will generate some current during the charging process.

In a general ex situ electrode CV analysis, reference, counter, and working electrode

conﬁgurations are used. In a fuel cell situation, often the use of a reference electrode

is difﬁcult, and the reference (RE) and counter (CE) electrodes are the same. This is

accomplished via the experimental conﬁguration in Figure 9.7. The electrode of interest

acts as the working electrode (WE), and nitrogen (or humidiﬁed nitrogen in the case of

PEFCs) is introduced to eliminate background noise from hydrogen adsorption in addition

to the hydrogen evolution/oxidation reaction. Typically, several hundred CV scans are

averaged once a steady state is obtained to minimize error.

A typical CV from a platinum electrode in an alkaline solution is shown in Figure 9.8,

and of a platinum electrode in an acid solution in Figure 9.9. Qualitatively, the results are

similar, but some of the reactions are slightly different.

At the low-potential region of both curves is the adsorbed hydrogen oxidation region,

which may contain several peaks. The peaks are actually a result of different crystalline

structures of platinum present on the electrode. These results can be used to select the

Figure 9.7 A CV experimental setup on fuel cell without reference electrode.