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Review

Diagnostic tools in PEM fuel cell research:Part I Electrochemical techniques

Jinfeng Wua, Xiao Zi Yuana, Haijiang Wanga,�, Mauricio Blancoa,b,Jonathan J. Martina, Jiujun Zhanga

aInstitute for Fuel Cell Innovation, National Research Council Canada, Vancouver, BC, Canada V6T 1W5bDepartment of Chemical and Biological Engineering, University of British Columbia, Vancouver, BC, Canada V6T 1Z4

a r t i c l e i n f o

Article history:

Received 5 December 2007

Accepted 19 January 2008

Keywords:

PEM fuel cell

Stack

Diagnostic tool

Design

nt matter & 2008 Internane.2008.01.013

thor. Tel.: +1 604 221 3038;haijiang.wang@nrc-cnrc.g

a b s t r a c t

To meet the power density, reliability, and cost requirements that will enable a widespread

use of fuel cells, many research activities focus on an understanding of the thermo-

dynamics as well as the fluid mechanical and electrochemical processes within a fuel cell.

To date, a wide range of experimental diagnostics is imperative not only to help a

fundamental understanding of fuel cell dynamics but also to provide benchmark-quality

data for modeling research. This two-part paper reviews various tools for diagnosing

polymer electrolyte membrane (PEM) fuel cells and stacks, and attempts to incorporate the

most recent technical advances in PEM fuel cell diagnosis. In Part I, we review various

electrochemical techniques and outline the principle, experimental implementation, and

data processing of each technique. Capabilities and weaknesses of these techniques are

also discussed. In Part II of the review we will cover physical/chemical methods.

& 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights

reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736

2. Electrochemical techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736

2.1. Polarization curve. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736

2.2. Current interruption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1738

2.3. Electrochemical impedance spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1739

2.3.1. Cathode behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1739

2.3.2. Anode behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1740

2.3.3. Fuel cell stack. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1740

2.3.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1741

2.4. Other electrochemical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1741

2.4.1. Cyclic voltammetry (CV). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1741

2.4.2. CO stripping voltammetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1742

tional Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

fax: +1 604 221 3001.c.ca (H. Wang).

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2.4.3. Linear sweep voltammetry (LSV) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1743

2.4.4. Cathode discharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1743

3. Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1743

Acknowledgment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1744

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1744

1. Introduction

Much attention has been paid to fuel cells because they

offer a highly efficient and environmentally friendly technol-

ogy for energy conversion. Of the various types of fuel cells

available, polymer electrolyte membrane (PEM) fuel cells are

considered to be the most promising for both stationary and

mobile applications due to their significant advantages such

as high efficiency and the absence of noxious emissions [1].

However, the commercial success of PEM fuel cells depends

on their performance durability and cost competitiveness

with other energy conversion and power generation devices.

A better understanding of all the operating parameters

influencing the function of the entire cell and phenomena

occurring in the electrodes, especially the performance and

efficiency-limiting processes, is essential for achieving this

goal.

Fuel cell science and technology cuts across multiple

disciplines, including materials science, interfacial science,

transport phenomena, electrochemistry, and catalysis. It is

always a major challenge to fully understand the thermo-

dynamics, fluid mechanics, fuel cell dynamics, and electro-

chemical processes within a fuel cell. A large number of

researchers are currently placing their focus on experimental

diagnostics and mathematical modeling. On the one hand,

diagnostic tools can help distinguish the structure–property–

performance relationships between a fuel cell and its

components. On the other hand, results obtained from

experimental diagnostics also provide benchmark-quality

data for fundamental models, which further benefit in

prediction, control, and optimization of various transport

and electrochemical processes occurring within fuel cells.

At present, researchers characterizing PEM fuel cells are

mainly concentrated on the following issues: (1) mass

distribution [2,3], especially water distribution over the active

electrode including flooding detection leading to low catalyst

utilization, (2) resistance diagnosis and membrane drying

detection [4,5], which closely relate to membrane conductiv-

ity, (3) optimization of electrode structures and components

[6], fuel cell design, and operating conditions [7,8], (4) current

density distribution in dimensionally large scale fuel cells

[9,10], (5) temperature variation resulting from a non-uniform

electrochemical reaction and contact resistance in a single

cell [11,12], and different interconnection resistances for a

stack, and (6) flow visualization for direct observation of what

is occurring within the fuel cell [13,14]. Due to the complexity

of the heat and mass transport processes occurring in fuel

cells, there are typically a multitude of parameters to be

determined. For all the previous reasons, it is important to

examine the operation of PEM fuel cells or stacks with

suitable techniques, which allow for evaluation of these

parameters separately and can determine the influence of

each on the global fuel cell performance.

Various diagnostic tools for the accurate analysis of PEM

fuel cells and stacks have been developed. A few review

papers have also been published about these prior efforts in

PEM fuel cell diagnostics. In a recent review about funda-

mental models for fuel cell engineering, Wang [15] briefly

summarized some diagnostic techniques, which were parti-

cularly pertinent to the modeling of PEM fuel cells. Hinds [16]

provided a good review of the literature regarding experi-

mental techniques employed in the characterization of fuel

cell performance and durability, but his work was mainly

limited to ex situ tools and applications.

The objective of this review is to provide a comprehensive

survey of in situ diagnostic tools presently used in PEM fuel

cell research. For the purpose of perspicuity, in this review,

various diagnostic tools employed in the characterization and

determination of fuel cell performances are summarized into

two general categories: electrochemical techniques and

physical/chemical methods. Electrochemical techniques are

discussed in this part, while physical/chemical methods will

be discussed in Part II.

2. Electrochemical techniques

Electrochemical techniques, such as the polarization curve,

current interruption, and electrochemical impedance spec-

troscopy (EIS), have been popularly employed in the diagnosis

of fuel cells. Recent advances in the application of these

electrochemical approaches to PEM fuel cells are described

herein, and some novel methods are covered.

2.1. Polarization curve

A plot of cell potential against current density under a set of

constant operating conditions, known as a polarization curve,

is the standard electrochemical technique for characterizing

the performance of fuel cells (both single cells and stacks)

[17–19]. It yields information on the performance losses in the

cell or stack under operating conditions. A steady-state

polarization curve can be obtained by recording the current

as a function of cell potential or recording the cell potential as

the cell current changes. A non-steady state polarization

curve can be obtained using a rapid current sweep [20]. By

measuring polarization curves certain parameters such as the

effects of the composition, flow rate, temperature, and

relative humidity of the reactant gases on cell performance

can be characterized and compared systematically.

The ideal polarization curve for a single hydrogen/air fuel

cell has three major regions, which are shown in Fig. 1 [17]. At

low current densities (the region of activation polarization),

the cell potential drops sharply and the majority of these

losses are due to the sluggish kinetics of oxygen reduction

reaction (ORR) [17]. At intermediate current densities (the

ARTICLE IN PRESS

Fig. 1 – Schematic of an ideal polarization curve with the

corresponding regions and overpotentials (modified from

Barbir [17] with permission).

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region of ohmic polarization), the voltage loss caused by

ohmic resistance becomes significant and results mainly

from resistance to the flow of ions in the electrolyte and

resistance to the flow of electrons through the electrode [21].

In this region, the cell potential decreases nearly linearly with

current density, while the activation overpotential reaches a

relatively constant value [17]. At high current densities (the

region of concentration polarization), mass transport effects

dominate due to the transport limit of the reactant gas

through the pore structure of the gas diffusion layers (GDLs)

and electrocatalyst layers (CLs), and cell performance drops

drastically [22]. From Fig. 1 it can also be seen that the

difference between the theoretical cell potential (1.23 V) and

the thermoneutral voltage (1.4 V) represents the energy loss

under the reversible condition (the reversible loss) [19]. Very

often, polarization curves are converted to power density

versus current density plots by multiplying the potential by

the current density at each point of the curve.

Up to now, several modeling studies have been carried out

to elucidate the electrochemical behavior of PEM fuel cells,

and for this purpose, several empirical equations were

introduced to mimic the polarization curves. Srinivasan

et al. [23,24] developed the following equation to describe

the relation between the cell voltage, E, and current density, i,

in the low and intermediate current density ranges, where

the electrochemical reaction is controlled by the activation

and ohmic losses:

E ¼ E0 � b logðiÞ � Ri, (1)

where E0 ¼ Er þ b log i0 and the two subsequent terms de-

scribe the different loss mechanisms. Er is the reversible

potential of the cell, i0 and b are the exchange current density

and Tafel slope for oxygen reduction, respectively. The second

term in Eq. (1) is predominant at low current densities and

describes the activation overpotential. In the third term, R

represents the resistance that causes a linear variation of the

cell potential with the current density, which is predominant

in the intermediate current density region.

Kim et al. [25] modified Eq. (1) by introducing an additional

term in order to fit the cell voltage against current density

behavior over the whole current density range,

E ¼ E0 � Ri� b logðiÞ �m expðniÞ, (2)

where m and n are the parameters related to mass transport

limitation. Bevers et al. [26] found in their one-dimensional

model that m correlates to the electrolyte conductivity and n

to the porosity of the GDL. In the high current density region

the last term becomes predominant, and is used to match the

losses due to the mass transport limitations.

Lee et al. [27] took into account the influence of pressure

parameters on the concentration polarization in PEM fuel cell

stack models,

E ¼ E0 � Ri� b logðiÞ �m expðniÞ � a logP

PO2

!, (3)

where P is the total pressure, PO2is the partial pressure of

oxygen, and a is an empirical equation constant.

Based on Eq. (2), Squadrito et al. [28] developed a

logarithmic equation based on a mechanistic analysis in

order to find an expression for the concentration polarization,

which was then modified to fit a set of experimental data:

E ¼ E0 � Ri� b logðiÞ þ aik lnð1� biÞ, (4)

where the term aik accounts for the pre-logarithmic terms

attributed to the different contributions and acts as an

‘‘amplification term’’, expressed in potential units, k is a

dimensionless number, b is the inverse of the limiting current

density, a is the transfer coefficient. It was further claimed

that Eq. (4) was able to predict a more accurate behavior at

high current densities since k mainly influences the point at

which there is departure from the linear behavior and adetermines the shape of the curve at high current densities.

The nonlinear contributions to the cell potential drop at

high current densities result from interface phenomena

occurring in the cathode reactive region. Pisani et al. [29]

developed a semi-empirical equation, based on the integral of

the oxygen concentration over the reactive region,

E ¼ E0 � Ri� b lnðiÞ þ a ln 1�i

ilS�mð1�i=ilÞ

� �, (5)

where S is a flooding parameter, m is an empirical constant,

and il is the limiting current density.

More complex empirical equations based on Eq. (2) have also

been developed. For example, Amphlett et al. [30] presented

empirical equations and terms that related activation losses,

internal resistance, and all temperature dependencies through

fitting parameters. Sena et al. [31] analyzed the catalyst layer

and considered it as a thin film/flooded agglomerate, thus the

gas diffusion electrode is assumed to be formed by an

assembly of flooded zones (catalytic zones) and empty zones

(no catalyst present). The final equation related the oxygen

diffusion effects in the gas diffusion electrode:

E ¼ E0 � Ri� b logðiÞ þ b log 1�i

iO2L

!, (6)

where iO2L is the limiting current density due to a limiting

oxygen diffusion effect.

More recently, Williams et al. [32] described a technique

based on the analysis of polarization curves (through similar

equations shown previously) that evaluates six sources of

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polarization, mainly associated with the cathode side of a

PEM fuel cell.

Polarization curves provide information on the perfor-

mance of the cell or stack as a whole. While they are useful

indicators of overall performance under specific operating

conditions, they fail to produce much information about the

performance of individual components within the cell. They

cannot be performed during normal operation of a fuel cell

and take significant time to finish. In addition, they fail to

differentiate different mechanisms from each other; for

example, both flooding and drying inside a fuel cell cannot

be distinguished in a single polarization curve [17]. They are

also incapable of resolving time-dependent processes occur-

ring in the fuel cell and the stack [16]. For the latter purpose,

current interrupt, EIS measurements, and other electroche-

mical approaches are preferred. These techniques will be

introduced in the following sections.

2.2. Current interruption

In general, the current interrupt method is used for measure-

ment of the ohmic losses (i.e., cell resistance) in a PEM fuel

cell. The principle of the technique is that the ohmic losses

vanish much faster than the electrochemical overpotentials

when the current is interrupted [33]. As shown schematically

in Fig. 2, a typical current interrupt result is presented by

recording the voltage transient upon interruption of the

current after the fuel cell had been operated at a constant

current. The ohmic losses disappear almost immediately and

the electrochemical (or activation) overpotentials decline to

the open circuit value at a considerably slower rate. There-

fore, rapid acquisition of the voltage transient data is of vital

importance to adequate separation of the ohmic and activa-

Fig. 2 – Ideal voltage transient in a PEM fuel cell after current

interruption. The cell is operated at a fixed current. At t ¼ t0,

the current is interrupted and the ohmic losses vanish

almost immediately. After the current interruption,

overpotentials start to decay and the voltage rises

exponentially toward the open-circuit voltage. At t ¼ t1, the

current is again switched on (from Mennola et al. [4] with

permission).

tion losses [4]. Fig. 3a shows the typical equivalent circuit for a

fuel cell consisting of two resistors and a capacitor. The first

resistor, Rr, represents the ohmic losses, and the second

resistor, Ra, represents the activation losses [34]. An example

of the circuit used to perform a current interrupt procedure

can be observed in Fig. 3b. When the switch is off the current

is interrupted and no current flows through the first resistor

in the fuel cell circuit. This makes the voltage increase

instantaneously at first, but it then increases very slowly due

to the discharging of the capacitor. The system achieves the

open-circuit voltage (OCV) once the capacitor is completely

discharged [17]. An oscilloscope can be attached to the overall

circuit in order to read the voltage signal.

The crucial issue, in efforts for in situ ohmic losses

measurements, is to separate the above two processes. Buchi

et al.’s [35] experiment showed that the time scope for

accurate current interrupt measurements must be controlled

between 0.5 and 10 ns. With the current interrupt technique,

Jaouen et al. [36] obtained specified values for various

parameters such as the exchange current density, Tafel slope,

oxygen solubility, and double-layer capacitance. Furthermore,

based on these results, their agglomerate model could fit the

experimental data well up to 200 mA=cm2 [37]. Abe et al. [38]

studied the effect of gas humidification temperature on the

ohmic resistance by the current interrupt technique. They

found that the ohmic resistance increased by 3:5 mO

when cathode gas humidification temperature decreased

from 80 to 35 1C.

Fig. 3 – (a) Equivalent circuit for a fuel cell (from Larminie

et al. [34] with permission); (b) circuit used to perform a

circuit interrupt procedure (from Barbir [17] with

permission).

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Fig. 5 – Typical impedance spectra of a PEM fuel cell. The

spectra was obtained at 30 1C using Ballard Mark V six-cell

stack with an active area of 280 cm2 (modified from Yuan

et al. [8] with permission).

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Using the current interrupt method, the effect of operating

conditions in a free-breathing PEM fuel cell on ohmic

resistances was also recognized by Noponen et al. [39].

Further, the current interrupt method was employed by

Mennola et al. [4] to determine the ohmic resistances in

individual cells of a PEM fuel cell stack. The technique

involved producing voltage transients and monitoring them

with a digital oscilloscope connected in parallel with the

individual cell. Their results showed good agreement between

the ohmic losses in the entire stack and the sum of the ohmic

losses in each individual cell.

Compared to other methods, like impedance spectroscopy,

the current interrupt method has the advantage of relatively

straightforward data analysis. However, one of the weak-

nesses of this method is that the information obtained for a

single cell or stack is limited. Another issue with this method

is the difficulty in determining the exact point in which the

voltage jumps instantaneously, thus a fast oscilloscope

should be used to record the voltage changes.

2.3. Electrochemical impedance spectroscopy

In contrast to linear sweep and potential step methods, where

the system is perturbed far from equilibrium, EIS applies a

small ac voltage or current perturbation/signal (of known

amplitude and frequency) to the cell, and the amplitude and

phase of the resulting signal are measured as a function of

frequency. This may be repeated through a wide range of

frequencies (i.e., large frequency spectrum). Basically, im-

pedance is a measure of the ability of a system to impede the

flow of electrical current, thus EIS is a powerful technique

that can resolve various sources of polarization loss in a short

time and has been widely applied to PEM fuel cells in a

number of recent studies. Fig. 4 shows the typical circuit used

for an EIS test. A common usage of EIS analysis in PEM fuel

cells is to study ORR [40,41], to characterize transport

(diffusion) losses [42–45], to evaluate ohmic resistance and

electrode properties such as charge transfer resistance and

double-layer capacitance [46] and to evaluate and optimize

the membrane electrode assembly (MEA) [47–49].

Impedance spectra are conventionally plotted in both Bode

and Nyquist form. In a Bode plot, the amplitude and phase of

the impedance is plotted as a function of frequency, while in a

Nyquist plot the imaginary part of the impedance is plotted

against the real part at each frequency. Fig. 5 shows a typical

Fig. 4 – Typical circuit for an electrochemical impedance

spectroscopy (EIS) experiment (from Barbir [17] with

permission).

impedance spectra for PEM fuel cells in Nyquist form with

two arcs, where the frequency increases from the right to the

left [8]. The high frequency arc reflects the combination of the

double-layer capacitance in the CLs, the effective charge

transfer resistance and the ohmic resistance, in which the

latter can be directly compared to the data obtained from

current interrupt measurements. The low frequency arc

always reflects the impedance due to mass transport limita-

tions [50,51].

2.3.1. Cathode behaviorDue to the fast hydrogen reduction reaction, the impedance

spectrum of the fuel cell nearly equals the cathode impe-

dance. As a result, the impedance of a fuel cell ðH2=O2Þ is

mainly used to study the cathode behavior.

2.3.1.1. High frequency arc. Many researchers have studied

the charge transfer of the cathode CL, which is represented by

the high frequency arc. The ohmic resistance, including the

membrane resistance together with the GDL, bipolar plate,

and contact resistances, is given by the real part of the high

frequency end of the high frequency arc [40,52]. It is assumed

that any change in this value during operation is caused by a

change in membrane ionic resistivity due to membrane

hydration. Therefore, the high frequency resistance is always

a measure of membrane water content.

A General Motors patent consisted of a correlation between

the degree of humidification and the high frequency resistance

of the membrane in a fuel cell stack [5]. They were able to

optimize the humidity level by monitoring the high frequency

resistance because they found that increased resistance

signified cell drying, while a decreased resistance in conjunc-

tion with low performance signified cell flooding. By monitor-

ing both cell resistance and pressure drop in an operational

fuel cell stack, Barbir et al. [53] were able to diagnose either

flooding or drying conditions inside the stack. Their results

showed that drying typically caused a monotonous voltage

decay, while flooding caused a rather erratic cell voltage

behavior, i.e., sudden voltage fluctuation due to liquid water

accumulation and expulsion inside the cell passages. Recently,

Oszcipok et al. [54] used EIS techniques to study the influence

of cold start behavior on the membrane resistance, as well as

performance degradation, of a PEM fuel cell.

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While the high frequency intercept corresponds to the

ohmic resistance, the diameter of the arc relates to the

charge transfer resistance of the CLs at high frequencies.

Many models were developed to discuss the mechanism of

the cathode CLs, such as the simple pore model [55],

agglomerate model [55], macrohomogeneous model [42,43],

and flooded-agglomerate model [56] under stationary condi-

tions. Several equivalent circuit models have also been

developed to mimic the spectra, such as the nonlinear least-

squares procedure (NLSQ) [56] and transmission line model

[43]. Consequently, the effects due to charge transfer, air

diffusion through the pores of CL, and diffusion in the

ionomer layer surrounding the catalyst particles could be

separated.

Based on a macrohomogeneous model of the gas diffusion

electrode, Springer et al. [42] demonstrated that simultaneous

fitting of impedance spectra obtained at different potentials

could be used to evaluate the sources of PEM fuel cell losses.

Three different types of losses caused by interfacial kinetics,

CL proton conductivity, and membrane conductivity, were

resolved in their impedance spectra. Eikerling and Korn [43]

employed the macrohomogeneous model to describe the

impedance responses of PEM fuel cells and further used the

transmission line model to simulate the impedance spectra.

The relationship between the structure of the CL and

impedance spectra was studied as well. The transmission

line model was also employed by Makharia et al. [57] to mimic

the CLs in H2=N2 and H2=O2 fueled PEM fuel cells. Parameters

such as cell ohmic resistance, CL electrolyte resistance, and

double-layer capacitance were extracted. More recently,

Lefebvre et al. [44] and Jia et al. [58] used the transmission

line model to simulate the impedance behavior of PEM fuel

cell CLs under a N2 atmosphere at the cathode side and,

ultimately, the ionomer loading in the CL [6] was optimized.

Furthermore, they used EIS to study the capacitance and ion

transport properties of CLs under H2=O2 conditions [59]. Fig. 6

illustrates the equivalent circuit of the transmission line

model, which consists of two parallel resistive elements, one

for electron transport through the conducting carbon parti-

cles ðRelÞ and the other for proton transport in the CL ðRpÞ. The

resistive elements are connected by double-layer capaci-

tances ðCdlÞ in parallel to the charge transfer resistance ðRctÞ.

2.3.1.2. Low frequency arc. It has been proven that the

appearance of the low frequency arc, illustrated in Fig. 5,

can be attributed to the limitation of oxygen diffusion

through nitrogen in the pores of the electrode [60,61].

Fig. 6 – Transmission line equivalent circuit describing the

impedance behavior of CL (from Eikerling and Kornyshev

[43] with permission).

Evidence to support this conclusion comes from the absence

of a low frequency arc for operation with pure oxygen and an

increase in the arc radius, when operated under air, with

increasing GDL thickness [62,63].

Cha et al. [64] employed impedance spectroscopy in their

investigation of the microscale transport phenomena in flow

channels for fuel cells based on the low frequency feature.

Their results showed that during flow channel scaling, the

performance of the fuel cell is maximized at a certain flow

channel size, but declined as the channel size decreased

despite improved mass transport resulting from the velocity

increase. Their explanation was that flooding blocked the

flow channels and inhibited the oxygen access. A more

comprehensive study of the impedance response of PEM fuel

cells has been conducted to investigate the effects of

membrane thickness, cell temperature, and humidification

conditions on fuel cell performance [56]. The low frequency

loop, which appeared at high current density and a low air

flow-rate, resulting in water accumulation in the GDL, was

attributed to the mass transport limitation.

2.3.2. Anode behaviorCO poisoning is a significant issue for PEMFC, lowering

performance due to the deactivation of the Pt anode catalyst.

Many efforts have been made to understand the mechanism

of CO poisoning. Some researchers have employed the EIS

technique to study CO poisoning of the anode [65–70].

However, two major problems subsist. One complex issue

with EIS measurements for investigation of anode poisoning

is the separation of the anode and cathode impedances [65].

Another problem is that the poisoning causes a change in the

state of the fuel cell, which is reflected in the recorded

impedance spectra [66].

Wagner et al. [66] observed that by carrying out the

measurements in galvanostatic rather than potentiostatic

mode the change in fuel cell impedance was mainly due to

that of the anode. Based on this measurement mode, the EIS

technique was used to investigate the influence of CO

poisoning on the Pt anode [67]. A combination of three

mathematical procedures, real-time drift compensation, time

course interpolation, and the Z-HIT refinement, has been

developed to validate and evaluate the EIS data of PEM fuel

cell systems change of state over time [68]. A similar EIS study

of CO tolerance for different Pt-alloy anode catalysts in PEM

fuel cells was presented as well [69].

2.3.3. Fuel cell stackEvaluation of the stack performance is of importance for PEM

fuel cell applications. For large fuel cell stacks, EIS application

is limited because most commercial load banks operating at

higher currents do not have good frequency responses. In our

lab the EIS of a 500 W PEM fuel cell stack was measured

successfully with the combination of a FuelCon test station, a

TDI loadbank, and a Solartron 1260 [8]. The effects of

temperature, flow rate, and reactant humidity on the stack

performance and impedance spectra were investigated. A

rotary switch, that was developed in-house, was used in order

for the individual cell impedances to be measured [71].

For simultaneous measurement of individual cell impe-

dances, Hakenjos et al. [72] set up a measurement system

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Fig. 7 – (a) Schematic of a typical voltage sweep back and

forth between two voltage limits; (b) typical plot of current

versus voltage (from O’Hayre et al. [82] with permission).

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containing a multichannel frequency response analyzer. As a

proof of reliability, their results showed good agreement

between the sum of the impedance of the single cells and the

measured impedance of the whole stack. The absolute

deviation was less than 2.5%. In addition, by controlling

different air flow rates, they found that a flooding event in a

single cell was observed with the impedance measurement

minutes before it showed up as a voltage drop.

2.3.4. SummaryEIS is a powerful technique for fuel cell studies. This dynamic

method can provide more information than steady-state

experiments and can provide diagnostic criteria for evaluat-

ing PEM fuel cell performance. The main advantage of EIS as a

diagnostic tool for evaluating fuel cell behavior is its ability to

resolve, in the frequency domain, the individual contribu-

tions of the various factors determining the overall PEM fuel

cell power losses: ohmic, kinetic, and mass transport. Such a

separation provides useful information both for optimization

of the fuel cell design and selection of the most appropriate

operating conditions.

However, the interpretation of impedance spectra hitherto

is difficult due to the complexity of the porous electrode and

still remains a debated issue. Experimental results from

Makharia et al. [57] showed that ohmic resistance estimated

using EIS at 1 kHz also included a contribution, of approxi-

mately 20240 mO cm2, due to the electrolyte resistance in the

CL. The low frequency impedance, typically ascribed solely to

limitations of oxygen transport to the cathode active sites

through the flooded porous cathode, was also influenced by

dehydration of the membrane close to the anode at high

current densities [73]. The experiment of Andreaus et al. [74]

demonstrated that this effect was more pronounced with a

thicker membrane, where back diffusion of water from the

cathode was less efficient. To summarize, there are still

unresolved issues regarding the explanation of the impe-

dance spectra. For example, it is difficult to distinguish the

individual contributions from the anode and cathode sides,

although it is generally considered that the rapid kinetics and

mass transport of the hydrogen oxidation reaction result in

negligible impedance contribution from the anode CL. And as

previously discussed, the interpretation of the low frequency

feature can be very sophisticated. For more information and

details in EIS for fuel cells and electrochemical power sources

in general refer to Barsoukov et al. [75].

2.4. Other electrochemical methods

2.4.1. Cyclic voltammetry (CV)Cyclic voltammetry (CV) is a commonly used electrochemical

approach for fuel cell research, especially to describe fuel cell

catalyst activity in more detail. The in situ CV technique has

proven to be quite valuable for ascertaining the electroche-

mical surface area (ECA) of gas diffusion electrodes, as

described in many research papers [54,76–81]. In this techni-

que the potential of a system is swept back and forth between

two set voltage limits while the current is recorded. The

voltage sweep is normally linear with time (see Fig. 7a) and

the plot of the current versus voltage is called a cyclic

voltammogram (see Fig. 7b) [82]. In a normal CV it can be

observed that when the voltage sweeps past a potential that is

related to an active electrochemical reaction the resultant

current will increase, creating a peak. After this first peak, the

current will stabilize once the available reactants have been

consumed almost completely. On the reverse voltage scan,

the reverse electrochemical reaction (with a reverse current

direction) may be observed. The characteristics of these peaks

can give information about the relative rates of reaction and

diffusion in the electrochemical system (see Fig. 7b) [82].

In a fuel cell, H2 is fed to one side of the fuel cell, acting both

as the counter electrode and reference electrode, to function

as a dynamic hydrogen electrode (DHE). The other side is

flushed with inert gas (N2 or Ar) and connected to the working

electrode. Voltammetric studies are performed using a

potentiostat/galvanostat and the cyclic voltammograms can

be recorded at different sweep rates. A lower sweep rate is

often used, e.g., 10 mV/s, in order to minimize the impedance

losses in the porous electrodes [76]. The ECA of the electrode

is estimated based on the relationship between the surface

area and the H2 adsorption charge on the electrode, as

determined from the CV measurement. The H2 adsorption

charge on a smooth Pt electrode has been measured to be

210mC=cm2 of Pt loading in the CL. The ECA of electrodes is

then calculated using the following equation [83]:

ECAðcm2Pt=gPtÞ

¼chargeðmC=cm2Þ

210ðmC=cm2PtÞ � catalyst loadingðgPt=cm2Þ. (7)

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The disadvantage of this technique for assessing supported

electrocatalysts is that the carbon features mask the H2

adsorption and desorption characteristics, e.g., double layer

charging and redox behavior of surface active groups on

carbon. To avoid the occurrence of carbon oxidation, the

anodic limit is always set below 1.0 V (versus DHE) [77]. In

Fig. 8 a typical fuel cell CV can be observed. The two peaks

identified represent the hydrogen adsorption and desorption

peaks on the platinum catalyst surface [82]. The forward and

reverse double-layer current density, Idl charging, which is offset

from the zero current value by the crossover current density,

icrossover, is also shown in this figure.

2.4.2. CO stripping voltammetryCO stripping voltammetry is another common technique for

determining the ECA of electrodes through the oxidation of

adsorbed CO at room temperature, operating under the same

principle as CV [84,85]. One side of the fuel cell is supplied

with CO plus inert gas, or humidified high purity inert gas

(Ar or N2Þ, and connected to the working electrode while

humidified H2 is fed to the other side, serving as the DHE [85].

During the CO adsorption process, CO plus inert gas is

supplied to the anode at a certain flow rate, while keeping

the electrode potential at about 0.1 V (versus DHE). Then, the

gas is switched to high-purity Ar for a long time to remove

any CO from the gas phase. To record the CO stripping

voltammogram, the potential is scanned from the adsorption

value to near 0.9 V with a scan rate of 5 [86] or 10 mV/s [84].

When assessing ECA based on CO stripping voltammetry, one

can also employ Eq. (7) by utilizing a value of 424mC=cm2 for

polycrystalline Pt [87]. An example of absorbed CO stripping

voltammograms for bulk PtRu alloys with a range of well-

characterized surface compositions is shown in Fig. 9 [88].

The CO stripping peak charge can provide information on

the active surface sites of the CL. Experimental results have

Fig. 8 – Schematic of a fuel cell CV. The two peaks identified

represent the hydrogen adsorption and desorption peaks on

the platinum fuel cell catalyst surface. The forward and

reverse double-layer charging current density, Idl charging, and

the crossover current density, icrossover, are also shown

(modified from O’Hayre et al. [82] and Cooper et al. [46] with

permission).

Fig. 9 – CO stripping voltammetry of sputter-cleaned Pt–Ru

alloys electrodes and of pure Ru: (—) stripping of a

monolayer of CO in the first positive-going sweep; (- - -)

second positive-going sweep. Conditions: 20 mV/s; 0.5 M

H2SO4; adsorption and immersion at 25 mV. Ru surface

compositions ðxRu;sÞ are indicated in the figure in atomic

fractions (from Gasteiger et al. [88] with permission).

also demonstrated that the CO stripping peak potential can

provide information on the composition of an unsupported

metal alloy surface [86] and was useful for exploring the

reaction mechanism of a metal alloy with enhanced CO

tolerance [89,90]. Song et al. [91] used this technique to

investigate the effect of different electrode fabrication

procedures on the structural properties of MEAs. It has also

been found that exposing CO to platinum and the subsequent

removal of that CO by electrochemical stripping is an

excellent method of cleaning and activating Pt [84]. During

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the CO adsorption and desorption processes, no degradation

in the MEA performance or the ECA of Pt was noted.

It is important to note that the study in Brett et al. [84] was

performed with the use of a segmented cell also used to

investigate current distribution in PEM fuel cells. For more

information on current distribution refer to the second part of

this review.

2.4.3. Linear sweep voltammetry (LSV)Crossover of hydrogen and oxygen through the membrane is

considered to be one of the most important phenomena in

PEM fuel cells, which leads to a fuel inefficiency [92]. Linear

sweep voltammetry (LSV) experiments are always conducted

at room temperature to evaluate and monitor fuel crossover

and to check for the presence of electrical shorts [93,94]. The

experiment procedure is similar to the CV technique, with the

principal difference of being the irreversible scan. Humidified

H2 and N2 are supplied to the anode and cathode sides of the

fuel cell, respectively. The scan potential ranges from 0 to

0.8 V with higher voltages being avoided to prevent Pt

oxidation [93]. The experimental procedure involves control-

ling the potential of the fuel cell cathode (working electrode)

and monitoring any electrochemical activity that occurs in

the form of a current. Since N2 gas is the only substance

introduced into the cathode side, any current generated in the

given potential range is solely attributed to the electroche-

mical oxidation of H2 gas that crosses over from the anode

side through the membrane. The crossover current typically

increases with the scan potential and rapidly reaches a

limiting value when the potential grows to around 300 mV

[94]. At this value all crossover H2 is instantaneously oxidized

due to the high overpotential applied. Based on the limiting

current, one can, ultimately, calculate the flux of H2 gas using

Faraday’s law [94]. Using this diagnostic method, Song et al.

[95] determined the hydrogen crossover rate through Nafion

112 membrane at elevated temperatures up to 120 1C.

More recently, Kocha et al. [92] examined the effects of

Fig. 10 – Sample of a linear sweep voltammogram on MEAs

containing Nations=PTA membranes of types I–III (25% PTA

loading). Scan rate 4 mV/s; room temperature; ambient

pressure operation; 200 cm3 H2 on anode; 200 cm3 N2 on

cathode (from Ramani et al. [93] with permission).

various operating temperatures, gas pressures, and relative

humidities on hydrogen crossover. A sample of a linear

sweep voltammogram for different types of MEAs is pre-

sented in Fig. 10 [93].

Another method for measuring H2 crossover through the

membrane is Chronocoulometry (CC), which is quite similar

to LSV [96,97]. The fuel cell is operated with hydrogen at the

anode and nitrogen at the cathode. A certain potential, e.g.

0.5 V, is applied to the cathode side of the cell, which serves as

the working electrode, instead of a potential scan. Hydrogen

crossing over the membrane from the reverse electrode is

oxidized completely at this potential. The electrical charge

passing through this electrode is recorded as a function of

time. By measuring the coulombs evolved by the oxidation,

the H2 crossover rate can be calculated as a mass transfer

limited current.

Crossover currents, measured before and after durability

tests under load, can also be used to diagnose membrane

degradation over time [96,98]. In Liu et al.’s [98] experiment,

the reinforced Gore composite membranes exhibited an order

of magnitude longer lifetime than the Nafion membrane of

comparable thickness. This in situ method was further

employed by Yu et al. [97,99] to investigate degradation

mechanisms under low humidification of the feed stream.

2.4.4. Cathode dischargeStumper et al. [100] developed an in situ cathode discharge

method to determine the MEA resistance and electrode

diffusion coefficient (MRED) for a fuel cell. This method was

based on the galvanostatic discharge of a fuel cell with an

interrupted reactant supply. During a cathode discharge

experiment, the cathode compartment was separated from

the gas supply by closing both inlet and outlet valves,

whereas the anode side continued to be supplied with H2.

Then the load was switched on with a constant current, and

the cell voltage transient was recorded during the discharge

of the fuel cell. The pure ohmic resistance of the fuel cell

could be determined by a fit of the equation presented by

Srinivasan et al. [23] (Eq. (1)) to the transient polarization

curve, which was extracted from a series of cell discharge

voltage profiles obtained at different current densities. The

mass transport coefficient of the electrode, could be ex-

pressed and determined using Fick’s laws. The MRED method

can provide valuable experimental data for the investigation

of the structure–performance relationships for fuel cell

electrodes, but its data processing includes some assump-

tions and empirical models, which could decrease the

accuracy of the results.

3. Concluding remarks

This paper reviews various electrochemical techniques em-

ployed in PEM fuel cell diagnosis. The polarization curve is,

nevertheless, the simplest and easiest way of characterizing

the fuel cell. EIS is also considered to be a powerful technique

for investigating the electrochemical systems. This method

allows the separate examination of different processes in PEM

fuel cell, such as anode kinetics, anode mass transport,

cathode kinetics, cathode mass transport, and membrane

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conductivity. Moreover, it is a powerful tool to determine

electrode parameters as functions of the structure and

composition, which is a prerequisite to optimize the elec-

trode.

Other techniques employed in PEM fuel cell diagnosis are

catalogued into physical/chemical methods, such as neutron

imaging, magnetic resonant imaging, and current distribution

approaches. Physical/chemical methods will be discussed in

the second part of this review.

Acknowledgment

The authors gratefully acknowledge the National Fuel Cell

program of National Research Council Canada for supporting

this project.

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