transient performance of steam reformers in the...
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TRANSIENT PERFORMANCE OF STEAM REFORMERS IN THE CONTEXT OF
AUTOMOTIVE FUEL CELL SYSTEM INTEGRATION
By
DANIEL AUGUSTO BETTS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2005
Copyright 2005
by
Daniel Augusto Betts
During my PhD studies a lot of happiness and tragedy occurred in my life. For this reason
I would like to dedicate this work, which represents the culmination of all these things, to
the following individuals: Erica E. Carr-Betts, my wife (thank you for always supporting
me. I love you very much); Carmen A. Carrington Betts, my mother (thank you for being
strong and fighting the good fight. You have immense strength and courage); Claude D.
Betts, my father (thank you for your reason and courage); Lydia C. Carrington, my
grandmother (I am so sorry that we could not save you. Thank you for teaching me that I
can); and to Matilda Eva Carr-Betts, my daughter (thank you for bringing me so much
joy).
ACKNOWLEDGMENTS
I would like to acknowledge the following individuals who directly or indirectly
contributed to this dissertation. First, my wife Erica Eva Carr-Betts was instrumental in
the elaboration of this study. She funded this endeavor, and maintained my sanity during
difficult times. Her support and love had no bounds.
My advisors (Dr. William Lear and Dr. Vernon Roan) were very patient with me.
Their instruction and encouragement fueled the hope that an end was near, even when it
was not. I am eternally grateful to them.
Those who worked at the Ford Fuel Cell Laboratory are also responsible for this
work coming to fruition. Special thanks are given to Dr. Timothy Simons and Ryotaro
Honjo, who were always available to give me a hand.
Dr. Paul Erickson, an alumni of UF and an old friend, was gracious enough to
allow me to conduct experiments in his reformers at UC-Davis. His collaboration made
this work possible.
The US Department of Education and the UF Mechanical and Aerospace
Engineering Department supported my research with a fellowship. Without this
fellowship I would not have been able to obtain this education. I am grateful. I promise to
repay this favor by dedicating part of my efforts to providing educational and
professional opportunities to others.
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TABLE OF CONTENTS page
ACKNOWLEDGMENTS ................................................................................................. iv
LIST OF TABLES............................................................................................................ vii
LIST OF FIGURES ......................................................................................................... viii
ABSTRACT....................................................................................................................... xi
CHAPTER
1 INTRODUCTION ........................................................................................................1
2 BACKGROUND ..........................................................................................................7
Fuel Processing.............................................................................................................7 Steam Reforming...................................................................................................8 Partial Oxidation Reforming .................................................................................9 Autothermal Reforming.......................................................................................10
Transportation Fuel Cells ...........................................................................................11 The Transportation Load Environment ......................................................................12 CO and Hydrogen Concentration Effects on PEMFC performance...........................16 Methanol as Fuel.........................................................................................................19
3 LITERATURE REVIEW ...........................................................................................23
Kinetics of the Catalytic Methanol Steam Reformer Reactor ....................................24 Reformer Performance................................................................................................26
4 ANALYSIS.................................................................................................................29
Steam Reformer Model...............................................................................................29 Heat Transfer .......................................................................................................31 Continuity ............................................................................................................35 Conservation of Specie........................................................................................38 Chemical Model ..................................................................................................39
Finite Difference Solution ..........................................................................................41 FEMLAB Solution......................................................................................................44 Steam Reformer Model Validation.............................................................................45
General Description.............................................................................................46
v
UC-Davis Reformer Data ....................................................................................49 Reformer Design.........................................................................................................57 Design Generalization ................................................................................................57
5 RESULTS...................................................................................................................65
Transient Efficiency....................................................................................................65 Case 1 - Infinite Reformer...................................................................................65 Case 2 - The Medium Sized Reformer ................................................................67 Case 3 - The Short Reformer...............................................................................68
Carbon Monoxide Concentration ...............................................................................70 Hydrogen Concentration.............................................................................................76
6 CONCLUSIONS ........................................................................................................78
Steam Reformer Modeling .........................................................................................78 Steady-state Reformer Operation ...............................................................................78 Unsteady Reformer Operation....................................................................................78
7 SUGGESTED FUTURE WORK ...............................................................................80
APPENDIX
A COPY OF FEMLAB SOLUTION REPORT.............................................................81
B PRELIMINARY LOAD FORECASTING STUDY..................................................99
C PHYSICAL DESCRIPTION OF THE UC-DAVIS REFORMER ..........................104
General Description ..................................................................................................104 Pumping Subassembly..............................................................................................106 Catalyst Bed Housing Subassemblies.......................................................................109 Condensing Unit Subassembly .................................................................................111
LIST OF REFERENCES.................................................................................................114
BIOGRAPHICAL SKETCH ...........................................................................................116
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LIST OF TABLES
Table page 3-1. Test parameters for Nakagaki tests.............................................................................26
4-1. Estimated maximum times for vaporizer volume flow change..................................49
4-1. Values constants used to develop virtual UC-Davis reformer ...................................52
4-2. Steady-state design of 60 kW reformer with an 11.9 mm radius and a catalyst bed density of 1983 kg/m3 ..............................................................................................63
5-1. Case 1: Summary of the transient response of the infinite reformer to changes in fuel flow rate ............................................................................................................66
5-2. Case 2: Summary of the transient response of the medium size reformer to changes in fuel flow rate ..........................................................................................68
5-3. Case 3: Summary of the transient efficiency response of the short reformer to changes in fuel flow rate ..........................................................................................69
C-1. UC-Davis reformer subassemblies ..........................................................................104
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LIST OF FIGURES
Figure page 1-1. Types of fuel cells and fuel choice used for fuel cell vehicle prototypes.....................2
1-2. Energy density of different fuels on a lower heating value (LHV) basis compared to hydrogen.................................................................................................................3
2-1. Typical polarization curves of various types of fuel cells. .........................................14
2-2. Driving load of a 30 ft phosphoric acid fuel cell bus operated at the University of Florida. The bus weighs is approximately 30,000 lbs..............................................14
2-3. Indirect methanol automotive fuel cell system power delivery schematic.................15
2-4. TBB-2 fuel cell bus methanol steam reformer and steam reformer burner temperatures during transient bus operation ............................................................15
2-5. University of Florida bus indirect methanol fuel cell system.....................................16
2-6. Effect of hydrogen concentration and utilization on PEMFC performance...............18
2-7. Effect of CO poisoning on PEMFC performance. .....................................................19
2-8. Use of air bleed to recover PEMFC performance. .....................................................19
4-1. General schematic of modeled steam reformer reactor ..............................................30
4-2. Control volume diagram.............................................................................................30
4-3. Convection-conduction ratio in the UC-Davis reformer fuel entry regions...............33
4-4. Calculated values of dT/dt for the UC-Davis reformer at the entrance region...........37
4-5. Measured temperature distributions of the UC-Davis steam reforming test rig operating at varying space velocities and varying conversion efficiencies..............37
4-6. Schematic representation chemical reaction model in the control volume. ...............40
4-7. Equilibrium products of the steam reforming reaction (CH3OH + H2O aH2O + bCO2 + cCO + dH2) with respect to temperature .....................................................41
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4-8. Separation of the reformer volume into annular elements with constant gas properties in space for the finite difference solution method used...........................42
4-9. Experimental steam reformer developed at UC Davis ...............................................50
4-10. Example of CO spike in the reformate of the UC-Davis reformer after an increase in premix fuel flow (transient condition). Also shown is a decrease of the steady-state CO concentration in the reformate with increased premix fuel flow rate....................................................................................................................50
4-11. Reformate CO composition relationship to changes in temperature in the reformer catalyst bed................................................................................................51
4-12. CO and H2 concentrations in the reformate gas in the UC-Davis reformer.............51
4-13. Estimation of catalyst bed thermal conductivity using UC-Davis reformer data.....53
4-14. Virtual UC-Davis reformer steady-state CO composition with varying premix fuel flow rates...........................................................................................................54
4-15. Hydrocarbon signal output obtained during UC-Davis reformer run......................54
4-16. Virtual UC-Davis Reformer CO spike from 10 to 15ml/min premix flow rate change.......................................................................................................................55
4-17. Virtual UC-Davis reformer temperature distribution (color plot) and methanol concentration (contour plot) for premix flow rate equal to 5 ml/min ......................56
4-18. Virtual UC-Davis reformer temperature distribution (color plot) and methanol concentration (contour plot) for premix flow rate equal to 30 ml/min ....................56
4-19. Reformer Efficiency with varying catalyst effectiveness at varying fuel flow rates ..........................................................................................................................62
5-1. Case 1: Infinite reformer operation when undergoing step variations in fuel flow rate............................................................................................................................66
5-2. Case 1: Reformer efficiency changes due to change of fuel flow rate for the infinite reformer .......................................................................................................67
5-3. Case 2: Transient efficiency of the medium size reformer under transient load changes .....................................................................................................................68
5-4. Case 2: Reformer efficiency changes due to change of fuel flow rate for the medium size reformer...............................................................................................69
5-5. Case 3: Transient efficiency of the short reformer under transient load changes ......70
ix
5-6. Case 3: Reformer efficiency changes due to change of fuel flow rate for the short reformer ....................................................................................................................71
5-7. Infinite reformer transient CO concentrations for various for changes in power output........................................................................................................................73
5-8. Infinite reformer transient off-steady-state CO concentrations for various changes in reformer power output..........................................................................................73
5-9. Medium reformer transient CO concentrations for various changes in power output........................................................................................................................74
5-10. Medium reformer off-steady-state CO concentrations for various changes in reformer power output..............................................................................................74
5-11. Short reformer transient CO concentrations for various changes in power output ..75
5-12. Short reformer off-steady-state CO concentration for various changes in reformer power output..............................................................................................75
5-13. Transient CO comparison of various size reformers operating between 40 and 50 kW hydrogen power output......................................................................................76
5-14. Comparison of transient changes in H2 concentration induced by step changes in fuel flow corresponding to hydrogen yields from 10 to 60 kW (lower heating value based) for various size reformers....................................................................77
B-1. Transient load profile for TBB-2 under the University of Florida Fuel Cell Lab driving cycle data obtained on 4-2-2004..................................................................99
B-2. Power Change Index (PCI) for TBB-2 under UFFL driving cycle data obtained on 4-2-2004. ...........................................................................................................100
B-3. Multi-layer Perceptron. ............................................................................................101
B-4. The MLP performance as a 10 second PCI predictor. .............................................103
C-1. General process diagram of the UC-Davis reformer ...............................................105
C-2. Premix reservoir and gear pump..............................................................................107
C-3. Vaporizer design ......................................................................................................107
C-4. Superheater design...................................................................................................111
C-5. The UC-Davis reactor design...................................................................................112
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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
TRANSIENT PERFORMANCE OF STEAM REFORMERS IN THE CONTEXT OF AUTOMOTIVE FUEL CELL SYSTEM INTEGRATION
By
Daniel Augusto Betts
December 2005
Chair: William Lear Cochair: Vernon Roan Major Department: Mechanical and Aerospace Engineering
Proton exchange membrane fuel cells (PEMFCs) and, to a lesser degree,
phosphoric acid fuel cells (PAFCs) have been widely studied as possible replacements for
transportation internal combustion engines (ICE). These fuel cells consume hydrogen as
fuel, which is electrochemically oxidized through an acid electrolyte. Because of the low
energy density and scarcity of elemental hydrogen, alternatives such as methanol and
natural gas have been investigated as primary fuels for PEMFC and PAFC fuel cell
systems. Of these fuels, methanol is the most easily reformed into a hydrogen-rich gas.
The most efficient way of doing this is through catalytic steam reforming. Therefore a
clear understanding of the performance of steam reformers may lead to better integration
of these devices into fuel cell engines.
In this dissertation the results of studies regarding the transient and steady-state
performance of methanol steam reformers for automotive fuel cell system integration are
provided. To power an automobile, a fuel cell system needs to be capable of changing
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power output rapidly, to adapt to changing driving loads. Although most fuel cell
systems currently use batteries to reduce the required response time associated with the
fuel cells and other balance of plant components (including the reformer), the ultimate
goal may be to reduce the reliance of the system on batteries (which add cost, weight, and
complexity to the system). This means that the fuel cell stack and the reformer must each
be capable of changing power outputs quickly and efficiently. Fuel cell stack efficiency is
intimately related to reformate gas composition (especially CO concentration). Since the
reformer is upstream of the fuel cell stack, it has great influence on the overall power
output and efficiency response of the fuel cell system.
The results of this study are based on data obtained from an experimental reformer
and numerical models. Non-dimensionalization of the governing equations derived for
reformer model development resulted in identification of potential reformer similarity
variables. Based on these reformer sizing and scaling theories were developed. Of
particular importance was the further demonstration of the insufficiency of space velocity
and aspect ratio as sole reformer similarity variables.
Step changes in fuel flow into the experimental reformer produced transient CO
concentration spikes. These spikes have also been identified in reformer literature.
Through the use of the transient reformer model, potential physical mechanisms that
cause these CO concentration spikes were identified.
Studies in conversion efficiency and transient and steady-state reformate hydrogen
concentration were also carried out.
xii
CHAPTER 1 INTRODUCTION
Interest in fuel cell technology for transportation has led to an ever-increasing
number of prototype fuel cell vehicle demonstrations in recent years. For example, 210
new prototype fuel cell vehicles were built in 2004. This is more than the cumulative
number of fuel cell prototypes developed between 1959 and 2002 [1]. Enthusiasm for
fuel cells centers on their high energy-conversion efficiencies, the cleanliness of its
primary fuel (hydrogen), and the cleanliness of its operational by-products (water,
electricity and heat). Yet commercialization of fuel cell vehicles faces major hurdles
including design of low-cost and robust systems, proper water-management design for
transient operation at various power levels and conditions, improvement of stack life,
improvement of hydrogen storage technology, and improvement of hydrogen-production
technology.
Generally, hydrogen supplied to the fuel cell stack comes from one of two sources:
on-board hydrogen storage, or a fuel processor. Currently, most fuel cell vehicle
manufacturers are developing vehicles that use hydrogen as their primary fuel
(Figure 1-1). On-board hydrogen storage is intended to simplify fuel cell engines and
reduce costs. However, even with pure hydrogen, fuel cell systems are far from achieving
operational goals, especially when the power output of the fuel cell system is cycled
through time. In addition, hydrogen storage technology is far from achieving the energy
density goals needed for widespread vehicle commercialization. Figure 1-2 compares the
energy densities of common hydrogen-rich fuels. Even with the most advanced hydrogen
1
2
energy-storage mechanisms, the energy density of hydrogen is far less than that of other
fuels. Currently, hydrogen-fueled fuel cell vehicles have achieved a maximum driving
range of approximately 300 km [1]. Major research efforts are now aiming to improve
hydrogen storage capacity. These efforts include using carbon nanotubes as a hydrogen
storage medium, and developing safe hydrogen tanks capable of operating at pressures of
over 700 bars.
Figure 1-1. Types of fuel cells and fuel choice used for fuel cell vehicle prototypes. This
figure was published with the permission of its original authors [1].
Introduction of reformation technology into fuel cell vehicles has been proposed as
a possible inexpensive way to solve the energy density problems associated with
hydrogen [2]. Industry analysts have pointed out that alternative liquid fuels could make
use of parts of the current global fuel delivery and storage infrastructure, potentially
reducing the cost of the fuels. In addition, alternative liquid- fuels could still continue to
be used in internal combustion engine vehicles without major modifications. Of the fuels
typically considered, methanol seems the most attractive because it is easily reformed at
relatively low temperatures and can be produced from a wide range of feedstock. In terms
of energy density, methanol has approximately half the energy density of gasoline, and
methanol is approximately 1.45 times more energy dense than hydrogen stored in
advanced hydride beds (Figure 1-2). It is important to point out that the process of steam
3
and autothermal reformation includes the dissociation of water to produce hydrogen,
therefore yielding greater hydrogen per carbon concentration than the simple methanol
dissociation reaction.
0
5
10
15
20
25
30
35
40
Cetane
(dies
el)
Octane
(gas
oline
)
hepta
ne
hexa
ne
penta
ne
butan
e
ethan
e
propa
ne
ethan
ol
methan
e
methan
ol
ammon
ia
liq. H
ydrog
en
Hydrid
eW
ater
CarbonHydrogen
Ene
rgy
Den
sity
(MJ/
L)
Figure 1-2. Energy density of different fuels on a lower heating value (LHV) basis
compared to hydrogen [3].
Using methanol as primary fuel for PEMFC vehicles is technically challenging.
Methanol-derived reformate contains hydrogen diluted mostly in carbon dioxide, water,
carbon monoxide, and methanol. Among the problems is that the dilution of hydrogen
produces a drop in cell efficiency. This drop in cell performance can be measured as a
drop in cell voltage (from V1 to V2) that corresponds to a drop in cell hydrogen partial
pressure from (P1 to P2) as shown in Equation 1-1.
4
⎟⎟⎠
⎞⎜⎜⎝
⎛=−
1
212 ln
PP
CVV (1-1)
The value of the constant C has been measured to range from 0.03 to 0.06 for
PEMFCs. This drop in voltage leads to a drop in fuel cell efficiency and operational
power density range. A positive aspect of reformation is that water vapor is among the
diluents in the anode fuel stream. This reduces the need for anode gas humidification,
which in hydrogen-fueled fuel cell systems can be very complicated.
The reformate gas also contains carbon monoxide, which has a poisoning effect on
low-temperature fuel cells1. The PEMFCs have been poisoned with CO concentrations
from 30 ppm. The equilibrium concentration of CO for the steam reforming reaction of
methanol at 225oC and 300oC (the typical range of temperature for catalytic steam
reforming) are 0.8 and 2.3 mole percent, which is beyond the limits of most current
PEMFC technology tolerance. Various reformate gas “clean-up” schemes aim to reduce
the concentration of CO in the anode fuel stream. Notable among these are preferential
oxidizers and specialized membranes (generally palladium) capable of filtering CO and
other gases from the reformate stream.
Coupled with these technical issues is the need for controlling the fuel cell and the
reformer when changes in load are required, in such a way that system efficiency drops
are minimized and response speed is maximized. Figure 1-3 shows the recorded
efficiencies of one of the 30ft Georgetown fuel cell buses (TBB-2) during a typical drive
1CO poisoning in fuel cells is a reversible phenomenon. Small concentrations of oxygen can be used to reverse the CO poisoning effects. Other techniques include increasing cell current to promote the electrochemical water-gas shift reaction.
5
cycle.1 These buses use methanol as their fuel and use a steam reformer to produce
hydrogen that is consumed by a phosphoric acid fuel cell (PAFC). The transient changes
in system efficiency shown are caused by variations in anode hydrogen stoichiometric
flow, changes in reformate hydrogen gas concentration, and changes in reformate carbon
monoxide concentration. Temperature variations in the fuel cell stack may also contribute
to these efficiency changes.
The goal of this study is to provide a broader understanding of the role of the
reformer in the dynamic performance of automotive load-following fuel cell systems, and
provide a basis for reformer design and modeling. Analyses in this study are derived from
a mixture of physical modeling results and experimental observations from which general
trends in reformer steady-state and transient conversion, hydrogen concentration, and
carbon monoxide concentration were derived.
1 The TBB-2 bus is a 30 ft phosphoric acid fuel cell bus housed at the University of Florida FORD fuel cell laboratory. This bus uses on-board methanol steam reformation for hydrogen production.
6
0.1
0.2
0.3
0.4
0.5
0.6
0.7
35 45 55 65 75 85 95 105 115
Run Time (min)
FC System Efficiency Ratio (FC Power/Max Power) Stack Efficiency
Max Power = 50kWRate of Chemical Energy in the Premix flow was calculated using the lower heating value of MeOH in liquid form.
Figure 1-3. Measured transient efficiency of the 30 ft Georgetown Fuel Cell Bus (TBB-2)
CHAPTER 2 BACKGROUND
In this chapter, several basic concepts essential to the general understanding of the
analysis and results of this dissertation are provided. The chapter describes key fuel
processing techniques and compares these techniques to each other. In addition, a short
description of low temperature automotive fuel cells is provided. Also, general systems
integration issues of indirect methanol fuel cell systems1 are presented. In this section,
data obtained from the Georgetown fuel cell test bed buses is used to show transient
interactions between the fuel processor and the fuel cell in an actual system. Finally, a
general discussion regarding methanol as a potential automotive fuel cell fuel is given.
Fuel Processing
Because of the difficulties of direct electrochemical oxidation of hydrocarbons,
hydrocarbon fuels are normally processed (or reformed) to give a hydrogen-rich fuel
mixture. Reforming plays an especially important role in low-temperature fuel cells,
namely proton exchange membrane fuel cells (PEMFCs) and phosphoric acid fuel cells
(PAFCs), since they are unable to oxidize any other fuel but hydrogen (H2)2. There are
three basic reforming methods: steam reforming, partial oxidation reforming, and
1 Indirect methanol fuel cell systems refers to the use of methanol as the system fuel. The methanol in this systems use a reformer to produce hydrogen, which ultimately is the fuel cell fuel. The term indirect is used to differentiate these systems from direct methanol fuel cell systems, which are capable of oxidizing methanol in the fuel cell without the use of a reformer.
2 Direct methanol fuel cells (DMFCs) commonly use similar electrolyte material, namely Nafion, as PEMFCs. In this text the term PEMFC refers to hydrogen proton exchange membrane fuel cells and excludes DMFCs.
7
8
autothermal reforming. This study concentrates on steam reforming since, of the
aforementioned methods, it is the most efficient form of hydrogen production from
hydrocarbon fuels.
Steam Reforming
Steam reforming is the reacting of a hydrocarbon with steam to produce a
hydrogen-rich gas (reformate). Using methanol as an example feedstock, steam reforming
can theoretically produce a maximum three moles of diatomic hydrogen gas for every
mole of carbon involved in the reaction (3:1). Steam reforming processes can occur with
or without a catalyst.1 However, most low-temperature fuel cell systems that use steam
reformation make use of catalysts in the reformer. Whereas non-catalytic steam
reforming requires temperatures in excess of 1100oC for simple hydrocarbons, catalytic
steam reforming can occur at temperatures ranging from 200oC to 700oC for simple
hydrocarbons. Nonetheless, non-catalytic steam reforming is still under investigation as a
possible method of reducing the thermal mass and volume of reformers.
Equation 2-1 shows the general, ideal steam reforming reaction for alcohols.
( ) ( )COanlCOlanHamOaHOHC nml −−+−++⎟⎠⎞
⎜⎝⎛ +→+ 2
2 222 (2-1)
l, m, and n represent the number of moles of carbon, hydrogen and oxygen,
respectively, in the hydrocarbon being reformed. The variable a represents the number of
moles of water per mole of hydrocarbon reacted.
Greater concentrations of water (a) in the reactants reduce the concentration of CO,
and increase the quantity of CO2 in the products. Moreover, the amount of hydrogen is
1 Non-catalytic steam reformation requires very high temperatures.
9
increased with greater steam. The maximum concentration of water that can be reacted in
the general steam reforming reaction is
nla −= 2max (2-2)
In practice, the catalytic steam reforming reaction is dependent on three-phase
chemical kinetics with mechanisms that are complex and currently not well understood.
Modern steam reforming catalysts can be designed to suppress the formation of CO and
promote the formation of CO2. The most commonly used methanol steam reformer
catalysts in published literature are composed of copper-oxide and zinc-oxide
(CuO/ZnO). As a general rule, the steam reformation of methanol across a CuO/ZnO
catalyst is executed with 1 to 1.5 moles of water per mole of methanol. Increasing the
H2O concentration to 1.5 has been found to reduce the CO content in the products while
increasing the hydrogen yield when the reformation process is maintained in the range of
250oC-300oC. Although higher water concentrations in the fuel increases hydrogen yield
and decreases reformate CO concentrations, these benefits may be counterbalanced by
the energy penalty associated with water vaporization and superheating.
Partial Oxidation Reforming
Partial oxidation reforming is a process in which the fuel undergoes combustion in
a fuel-rich environment. The elevated temperatures generated from this combustion
breaks down the hydrocarbon fuel into a hydrogen rich gas. Assuming, ideally, that the
reaction products are only hydrogen, carbon monoxide and carbon dioxide, the general
partial oxidation reaction for an alcohol is given in Equation 2-3.
( ) ( ) OeHCOeanlCOelanHemaOOHC nml 2222 2222
++−−+−−++⎟⎠⎞
⎜⎝⎛ −→+
(2-3)
10
To obtain the maximum possible amount of hydrogen in a partial oxidation
reaction, the amount of water (e) formed must be negligible (e 0). Taking methanol as
an example, the maximum, ideal, diatomic hydrogen to carbon ratio for the partial
oxidation reaction is 2:1. This is 2/3 of the maximum possible obtainable hydrogen to
carbon ratio from steam reforming of methanol. It is important to note that for most
applications the use of pure oxygen for partial oxidation is impractical. Thus nitrogen will
be present in the products of the reaction, which further dilutes the reformate hydrogen
concentration.
Some advantages of partial oxidation over steam reforming are that water is not
required for the process, the equipment is more compact, it allows rapid start-up, the
same reactor can reform various types of fuel, and the high-temperature reactor can
tolerate many impurities (including sulfur). On the other hand, care must be taken to
prevent carbon deposition. Also, since the process is exothermic, relatively high local
temperatures are produced, causing possible materials problems. For integration with
lower temperature fuel cells, a gas clean-up step is necessary to reduce the inherently
large CO content.
Autothermal Reforming
Autothermal reforming combines aspects of steam reforming and partial oxidation
reforming. A catalyst bed, typically nickel, and steam promote the reforming reaction.
The necessary heat is generated through combustion of a portion of the reformer fuel.
The general, idealized autothermal reforming reaction is given by Equation 2-4.
( ) ( CObanlCOlbanHbmObHaOOHC nml −−−+−+++⎟⎠⎞
⎜⎝⎛ +→++ 222
2 2222 )
(2-4)
11
In autothermal reforming, the maximum amount of water (b) that can be reacted is
given by Equation 2-5.
anlb 22max −−= (2-5)
Compared to the ideal steam reforming reaction, the maximum amount of water
that can be reformed is reduced by the presence of oxygen, thus reducing the overall
hydrogen yield. On the other hand, the addition of water to the reaction allows for higher
hydrogen yields and lower carbon monoxide concentrations in the products.
Autothermal reformers have had a large amount of interest because of their
capacity to reconcile between the benefits and detriments of using either catalytic steam
reforming or partial oxidation reforming.
Transportation Fuel Cells
For transportation applications and small-scale residential power production,
PEMFCs and PAFCs have been most widely considered and explored. These fuel cells
operate similarly, oxidizing hydrogen through an electrolyte and a current collector as
shown:
• Anode: H2 4e-+2H+
• Cathode: ½ O2 + 4e-+2H+ H2O
However, PEMFCs operate at a lower temperature than PAFCs (25oC-80oC as
opposed to 150oC to 200oC). In addition, PEMFCs, due to their high efficiency over a
wide range of current densities, typically have higher energy density than PAFCs. Mainly
for this reason, PEMFCs are widely considered the preferred automotive fuel cell. This
distinction does not mean that PEMFCs are trouble-free. Major engineering challenges
are yet to be resolved in order to commercialize automotive PEMFC stacks. Foremost,
12
these fuel cells must dramatically improve their operational life; they must achieve
consistency in performance under mass production, which has not yet been demonstrated;
they must be designed to have effective humidity control and positive water balance
during all operating regimes; and their cost must be dramatically reduced. In terms of life
and humidity control, PAFCs have been demonstrated to far surpass PEMFCs. However,
PAFCs are much more expensive to produce than PEMFCs and their cost is harder to
reduce to target levels, even through mass production.
Figure 2-1 shows typical polarization curves of various types of fuel cells including
molten carbonate fuel cells (MFCs), solid oxide fuel cells (SOFCs), and alkaline fuel cell
(AFCs). The reader might find it curious that AFCs are not considered in this study even
though they exhibit much higher voltages than all other fuel cells. The reason for this is
that AFCs do not tolerate air (due to the presence of CO2). This limits their use to space
applications and as electrolyzers.
The Transportation Load Environment
The power load associated with automobiles and buses is high and extremely
transient. Vehicles are driven with a rapid succession of speed adjustments, especially in
city traffic. Any fuel cell engine that is going to be incorporated into a vehicle must be
able to change power delivery over a wide range of conditions fast and efficiently. Figure
2-2 shows driving loads obtained from a 30 ft fuel cell transit bus operated at the
University of Florida (UF) on a low speed circuit around the city of Gainesville, Florida.
The transient response of fuel cell systems is limited by their capacity to deliver fuel
(hydrogen) and oxidant (oxygen) to the fuel cell stack. In a reformer based fuel cell
system, as shown in Figure 2-3, the fuel processing subsystem must be capable of
changing hydrogen production levels at the same rate as current draw changes occur in
13
the fuel cell stack. In turn, fuel cell voltage at a certain current draw depends greatly on
H2 and CO partial pressures in the reformate gas.
The process of steam reforming is complicated by the endothermicity associated
with hydrogen production. The composition of the reformate gas is largely dependent on
the temperature at which the reforming reaction takes place. Yet, in steam reformers the
heat required to maintain the reforming reaction is provided by an external source and
thus is limited by heat transfer considerations. This results in varying reforming reaction
temperatures during steady-state and transient operation. As an example, the University
of Florida fuel cell bus (TBB-2) reformer temperatures during transient conditions are
shown in Figure 2-4.1 In TBB-2 the reformer catalyst bed is heated via an external burner
that consumes stack anode flue gas (Figure 2-5). The anode flue gas contains varying
quantities of hydrogen, depending on stack current draw and anode stoichiometry. Anode
stoichiometry is dependent upon fuel flow rate and reformate quality. Current-draw
depends on the load environment. For TBB-2 the stack power draw and the reformer
hydrogen production are coupled. University of Florida researchers have found that this
interrelation between the stack current draw and reforming heating has led to instances of
reformer overheating and under-heating, both of which have led to drops in overall
system performance [2].
1 Reformer top, center, and bottom refers to the position of thermocouples in different regions of the catalyst bed. The catalyst bed entrance is located close to the reformer bottom thermocouple. The center thermocouple is located close to the midpoint of the reformer and the top thermocouple is located close to the exit of the reformer. The reformer burner thermocouple is located close to the reformer burner flame.
14
Figure 2-1. Typical polarization curves of various types of fuel cells. This figure was
published with the permission of its original authors [4].
Transient Load Profile for TBB-2 under the UFFL driving cycle-10
0
10
20
30
40
50
0 100 200 300 400 500 600 700
Run Time (s)
Pow
er (k
W)
4-2-2004 test 1
Figure 2-2. Driving load of a 30 ft phosphoric acid fuel cell bus operated at the
University of Florida. The bus weighs is approximately 30,000 lbs.
15
Methanol:WaterPremix Tank Steam Reformer Phosphoric Acid
Fuel Cell StackPower
Conditioning
Batteries
Parasitic andAux. Loads
High VoltageDistribution
TractionDrive
Wheels
Figure 2-3. Indirect methanol automotive fuel cell system power delivery schematic
200
250
300
350
400
450
500
550
600
650
00:00.0 07:12.0 14:24.0 21:36.0 28:48.0 36:00.0 43:12.0 50:24.0 57:36.0
Time (minutes)
Tem
pera
ture
(o C
)
Reformer Top Reformer Center Reformer Bottom Reformer Burner
Ramp Up Period Steady State High Power Steady State, Idle
Ramp Down Period
Reformer Burner
Idle
Reformer Bottom
Reformer Center
Reformer Top
Figure 2-4. TBB-2 fuel cell bus methanol steam reformer and steam reformer burner
temperatures during transient bus operation
16
ReformerBurner
SteamReformer
NeatMethanol
WaterMethanolPremix
Start-upBurner
Air
Air
Excess Airand Water
Anode
Air
Cathode
Fuel Cell Stack
Anode Flue Gas
Reformate
CombustionProducts
Heat ExchangePlate
Heat Exchanger
Bypass
Vaporizer
CombustionProducts
Figure 2-5. University of Florida bus indirect methanol fuel cell system
CO and Hydrogen Concentration Effects on PEMFC performance
Small increases in reformate CO concentration lead to drastic reductions in fuel cell
performance in low-temperature fuel cells that use platinum catalyst to promote the cell
anodic reaction. In these cells, CO competes directly with hydrogen for active sites in the
anode due to its high affinity for platinum at low-temperatures. Springer et al. propose
that the reactions depicted in Equation 2-6, Equation 2-7, Equation 2-8 and Equation 2-9
represent well the competition for active sites at a PEMFC anode [5].
)(/ COMMCO bfckfc −⎯⎯⎯ →←+ (2-6)
)(/2 COMMH bfhkfh −⎯⎯⎯ →←+ (2-7)
MeHHM keh ++⎯→⎯− −+)( (2-8)
−+ +++⎯→⎯−+ eHCOMCOMOH kec 22)( 22 (2-9)
17
Equations 2-6 and 2-7 represent the competition between H2 and CO for active
sites, where kfc and kfh represent the forward reaction-rate constants. The electro-
oxidation of hydrogen and CO are represented in Equations 2-8 and 2-9, with their
respective rate constants (keh and kec). PEMFC models and experimental results have
demonstrated that drops in anode hydrogen concentration produce very mild decreases in
cell performance (Figure 2-6). However, high CO concentrations have been shown to
drastically drop cell performance, especially when diluted in reformate bearing low
hydrogen concentrations (Figure 2-7).
In order to further reduce the CO concentrations produced from steam reformers,
many fuel processing systems use preferential oxidizers and anode air bleeds (the
introduction of small quantities of air into the fuel cell anode chamber). Preferential
oxidizers require the addition of air into a catalytic bed that promotes the oxidation of
CO. Typically a small percentage of the hydrogen in the reformate is also oxidized.
Currently, control of air delivery systems for preferential oxidizers is complicated due to
the high sensitivity of the chemical rate equations to gas and catalyst temperature and CO
concentration. In addition, the amount of air associated with preferential oxidation
operation is very low and difficult to meter. In the overall reforming process high
upstream variations in CO concentrations may lead to increased concentrations of CO
leaving preferential oxidizers, thus increasing the probability of anode catalyst poisoning.
This is especially problematic since CO spikes occur during periods of increasing power
demand. This phenomenon will be further explained in subsequent chapters.
Various solutions have been proposed for solving the problem of CO poisoning of
the fuel cell anode catalyst. Of these the most commonly reported has been the
18
introduction of small quantities of air into the cell anode during periods of decreased cell
performance due to CO poisoning. This produces catalytic oxidation of the CO in the
presence of anode platinum. Nonetheless, the air bleed also has a tendency to oxidize a
portion of the hydrogen introduced into the fuel cell. This results in a further reduction in
cell efficiency. Figure 2-8 shows how the effect of air bleed introduction in the anode
reduces the poisoning effects of CO. Also, it is difficult to distinguish between cell
performance deterioration due to CO poisoning and other operating conditions (humidity
variations, temperature variations, pressure variations, cell degradation, etc).
Based on this, a reformer that produces minimal increases in CO level during
increased fuel flow events is more desirable than one that produces high hydrogen
concentrations (within typical reformate hydrogen and carbon monoxide concentrations).
Figure 2-6. Effect of hydrogen concentration and utilization on PEMFC performance.
This figure was published with the permission of its original authors [5].
19
Figure 2-7. Effect of CO poisoning on PEMFC performance. This figure was published
with the permission of its original authors [5].
Figure 2-8. Use of air bleed to recover PEMFC performance. This figure was published with the permission of its original authors [5].
Methanol as Fuel
Since most of the results of this research are based on the study of methanol
reformation, a brief discussion of methanol as a potential fuel cell fuel is relevant.
20
Of the alternative fuels which are being considered for vehicles, many view
hydrogen as the ultimate long-term alternative fuel. However, while hydrogen has some
very desirable attributes, there are many extremely difficult issues to resolve, which
might make the time scale for a “hydrogen economy” far longer than the time scale of
readily available and affordable petroleum. Fuels which can be stored as liquids offer
major advantages for transportation applications. Of the alternative liquid fuels, in many
ways the most promising is methanol. This is because methanol reforming technology is
well developed as compared to reforming technology for other common automotive fuels.
Also methanol can be produced from natural gas, biomass, electricity, coal, and any other
hydrocarbon. These result in a fuel that can potentially be relatively inexpensive in most
regions of the globe. In addition, methanol can be used in internal combustion engines,
gas turbine engines and in fuel cell engines.
Most of the methanol produced in the U.S. is derived from natural gas. Twelve
major methanol production plants exist in the U.S., which in 2001 produced over 1.5
billion gallons of methanol (94.2 trillion BTU or equivalent to 753.6 million gallons of
gasoline). The overall U.S. methanol consumption in 2001 was, in energy terms,
equivalent to ~1,507 million gallons of gasoline, half of which was imported [6]. The
price of delivered methanol has averaged ~$0.50 per gallon (~$8/million BTU) since
1991. If the price of natural gas did not figure into the cost of methanol, the methanol
cost would be ~$1.50/million BTU.
Currently, most of the U.S. produced hydrogen is derived from natural gas steam
reforming. The U.S. consumes around 9 million tons of hydrogen (925.8 trillion BTU or
21
equivalent to ~7,407 million gallons of gasoline) per year, of which approximately 17%
is sold to chemical plants and refineries [7].
Current hydrogen costs at large scale chemical plants, where hydrogen is consumed
on site, are generally around $5.31/million BTU. If transported, the price of hydrogen is
much higher. The typical price of delivered liquid hydrogen oscillates between $1.00 and
$1.40 per pound ($20/million BTU to $27/million BTU). Therefore hydrogen prices are
comparable to methanol prices only if hydrogen is not pressurized, liquefied, or
transported.
The cost of producing hydrogen using steam reforming of natural gas minus the
cost of the natural gas, for a large plant, would be ~$4.15/million BTU. This price does
not include transportation, storage, compression or liquefaction of the gas.
While for methanol, storage and transportation costs are not essential components
of the overall fuel cost, this is not the case with hydrogen. It is expected that, due to its
lower energy density, methanol transportation costs per unit energy basis will be twice
the cost for transporting gasoline, in energy terms (~$6.92 per million BTU) [7].
Hydrogen transportation cost, in contrast, may vary drastically depending on the distance
transported and the method of transportation. Taking current gasoline transportation costs
as a baseline, it could be assumed, as an initial estimate, that because of its lower energy
density, liquid-hydrogen transportation would cost at least 5 times more than gasoline
transportation if similar transportation forms were used (mainly pipeline and truck
transport). Thus, hydrogen transportation costs could be expected to be around $18.94
per million BTU [7].
22
Hydrogen distribution costs could also be estimated by assuming that the eventual
hydrogen distribution infrastructure will be similar to that of natural gas. This assumption
is legitimate since both fuels are gaseous. The average distribution cost for natural gas,
from wellhead to residential consumer1 in the U.S., from 1991 to 2003, was $4.80/million
BTU. Thus, by applying an energy density penalty it could be estimated that the average
hydrogen distribution price in the U.S. will be ~$18.51/million BTU (similar to the
previous estimation). Note however that these estimates do not include additional cost
penalties associated with hydrogen transport such as boil-off, gas leakage, and special
materials needs.
Based on this basic analysis, it is fair to assume that methanol could be an
important fuel for transportation and fuel cells since it has the potential to be much
cheaper and more easily distributed than hydrogen. A study by the University of Florida
found that based on future fuel cell vehicle fleet estimates for 2020, and according to
various economic scenarios, methanol derived hydrogen from coal would be the least
expensive automotive fuel for fuel cell vehicles in the US if environmental concerns are
not taken into account [7].
1 Residential natural gas prices were used to estimate hydrogen distribution prices because it most closely resembles the distribution requirements of the automotive sector.
CHAPTER 3 LITERATURE REVIEW
This literature survey has the purpose of framing the work and results of this
dissertation as part of the latest research and scientific debates regarding the design and
integration of methanol steam reformers into fuel cell systems.
Generally, research conducted on reformers can be catalogued into two different
approaches, the chemical and the physical. Chemical research has concentrated in trying
to understand the chemical mechanisms and rate of reaction relations of the steam
reforming reaction. A large volume of papers and presentations have been published in
the last couple of years regarding this subject. Common among these is a general concern
among researchers that almost every research case (even when identical catalysts are
used) has lead to different rate of reaction equations, although in the same mathematical
form.
The physical approach to reformer research has dealt with understanding the
complete reformer assembly and its behavior. The volume of work in this area is limited.
In addition, most of the work has concentrated on the steady-state case. Dynamic models
and studies on fuel cell systems in published literature typically rely on user-defined
linear exponential decay functions for each fuel cell system component, including the
reformer. These investigations concentrate on the question of fuel cell systems control.
Typical of this approach is the study conducted by El-Sharkh et al. 2004 [8].
23
24
Kinetics of the Catalytic Methanol Steam Reformer Reactor
Although the actual kinetics of the methanol steam reforming reaction were outside
the scope of this study, a general review of the work in this field is herein presented. Of
note is the diversity of rate equations that have been presented in literature. This
demonstrates the complexity of the reaction and the variability that can be obtained based
on catalyst selection, catalyst preparation, and reaction conditions.
Choi et al., 2005, proposed that the methanol steam reformer products can be
obtained by with the rate equations for 3 main reactions in a Cu/ZnO/Al2O3 catalyst
manufactured by Sud-Chemie. These were [9],
222
2223
23
32
HCOOHCOHCOOHOHCH
HCOOHCH
+↔++↔+
+↔
The study conducted by Choi greatly simplified the widely cited 12 reaction rate
model previously given by Peppley et al. [10]. Peppley and Choi point out in their studies
the large degree of disagreement in literature regarding reaction mechanisms and the
debate on identifying the physical location of the steam reforming catalyst active site.
The results of their experiments were a series of rate equation for each of the proposed
methanol steam reformer reactions. Based on these reactions a methanol steam reformer,
a water gas shifter and a PROX reactor model were developed. The results of their
models show an increase in conversion with greater temperature and catalyst weight in
the reactor, however this also increased CO. The study conducted by Choi did not model
heat transfer in the reactor bed or the transient behavior of the reformer.
Lee et al., 2004, [11] recognized the importance of steam reforming kinetics in
sizing methanol steam reformers. They also recognized the large diversity of rate
25
equations found in literature. Lee, in his paper includes a list of 9 different catalytic
methanol steam reforming rate of reaction equations found in recent literature. Many of
these reaction rate equations are contradicting even when the same catalyst is being used.
Lee observes that higher water concentration in the steam reforming reaction promotes
effluent CO concentrations closer to equilibrium. The discrepancy between experimental
CO concentrations and equilibrium concentrations were between ~1mol% to <0.1mol%
for a water feed concentration between 15mol% to 30mol%. Finally Lee, in his study,
also proposed a new rate of reaction of methanol for the catalyst used.
The correlation proposed by Nakagaki et al. [12] was used in the models produced
in this study. Nakagaki obtained his correlations through a series of experiments that
closely resembled the test conditions in which data was obtained for this study. The study
conducted by Nakagaki used a temperature controlled packed-bed reformer operated at
various fuel flow rates. In obtaining his correlation, Nakagaki conducted constant catalyst
temperature studies and constant wall temperature studies (the latter allowed for
temperature gradients to exist in the reformer catalyst bed). Finally his correlation was
validated through actual reformer operation and modeling. This type of experimentation
varies from others in literature in that the effects of fuel flow (transport phenomena) and
varying reactant concentrations were considered. Also considered are the effects of
temperature gradients in the catalyst. The following is a general description of the study
conducted by Nakagaki, et al.
Nakagaki et al. obtained their correlation through experiments conducted in a
packed-bed experimental reformer. The catalyst used was Cu-Zn in alumina support
commercially available from Nissan (G66-B). The catalysts were 1/8in by 1/8 in
26
cylindrical tablets. Various concentrations of methanol diluted in simulated reformate gas
assuming conversions equivalent to 0, 10, 20, 50, and 75 percent were flowed through the
packed bed reformer. The reformer temperature was maintained constant and controlled
through the use of sheath heaters. This first test was used to determine the methanol rate
of reaction in a constant temperature reaction.
A second test controlled the temperature of the reforming reaction by maintaining a
constant wall temperature. In the second test the temperature distribution and the
conversion were recorded. The exiting reformate gas composition was recorded using a
TCD gas chromatograph. Based on second test results, the Nakagaki correlation was
refined.
Table 3-1 shows a summary of the tests conducted by Nakagaki. Nakagaki also
conducted modeling studies through a combined energy, momentum (Darcian equation),
and conservation of species equations to further validate his correlation. However, since
the application of the study was for employment in gas turbine engines, the study of CO
concentration in the reformate outlet stream was neglected.
Table 3-1. Test parameters for Nakagaki tests Parameter Test 1 Test 2 Pressure (atm) 1, 5, 10, 15 1, 10 Catalyst Temperature (K) 473, 498, 513, 538 -- Wall Temperature (K) -- 518, 548 Mass Flux (kg/(sm2)) 0.25 0.25, 0.36 Simulated conversion percentage
0, 10, 20, 50, 75 0, 80
Reformer Performance
Various studies have been published on reformer performance and design but the
majority of these have concentrated on reformer steady-state performance and catalyst
27
dynamic behavior (rates of reaction correlations). The work of Betts et al. [13] provided a
mechanistic model for observed fluctuations in reformer CO output. The identification of
CO spikes as being caused primarily by heat transfer effects in the reformer was
discussed in that study. A study by Horng [14] showed for an autothermal reformer the
existence of CO spikes once fuel was introduced into the reformer. However, the study
concentrated in the start-up process of the reformer and did not place much emphasis on
the CO phenomenon.
The importance of heat transfer and temperature on the performance of methanol
steam reformers was studied by Hohlein et al. [15]. Hohlein concludes that reformer
heating is a very strong determinant of reformate CO concentration.
Perhaps the most comprehensive experimental study on reformer performance was
conducted by Davieau [16]. In this study, reformer performance was measured in terms
of methanol conversion for two reformers of differing diameters. The initial interest of
Davieau was to study the degree in which space velocity and aspect ratio determines
reformer similarity. The reformers were operated at various space velocities. The results
demonstrate that space velocity and aspect ratio were not a good determinant of reformer
performance. That is, two reformers operating with the same space velocity, same
catalyst loading, same wall temperature and same aspect ratio had drastically different
performances. Yet, Davieau points out that space velocity is the most cited reformer
similarity relation in literature. Additionally, Davieau notes that temperature distribution
within the reformer is a critical performance parameter. Furthermore, it is noted that
diameter influences heat transfer and therefore has an effect on performance that is
28
beyond catalyst loading. The results obtained by Davieau were based on experimental
observations. His study did not focus on the transient behavior of the reformer.
CHAPTER 4 ANALYSIS
In accordance with the objectives of this research, a general methanol steam
reforming model was developed. The details of the derivations and major assumptions
applied to the development of this model are included in this chapter. In addition, this
chapter includes a general comparison of the steam reformer model results and
experiments conducted at UC-Davis using an experimental reformer test rig developed at
by Dr. Paul Erickson (Appendix C). Part of the analysis includes the development of a
generalized design and comparison criteria for steam reformers through similitude
parameters. Finally, in this chapter transient operation of the modeled steam reformer is
presented.
Steam Reformer Model
Packed bed catalytic steam reformers are generally composed of a reaction
chamber filled with catalyst pellets (Figure 4-1). The methanol water mix along with the
product gases flows around and through the catalyst pellets. The chemical reactions occur
at the surface and within the catalyst pellets. In the development of this model, it was
recognized that the main driver of reformate chemistry is temperature.
A control volume approach was used to obtain differential conservation of species
and conservation of energy relationships. In choosing the scale of the finite differential
control volume, it was assumed that the catalyst pellets and the gases exist in the control
volume as a homogenous mixture. That implies that the control volume used, although
small compared to the overall reformer, has length scales larger than that of the catalyst.
29
30
It was also assumed that the gas and the catalyst exist locally at the same temperature.
This comes as a result of the assumption that the catalyst and the gases are regarded as
part of a continuum. This also implies that the surface area of the catalyst inside the
control volume is very large, resulting in the gas being in thermal equilibrium with the
catalyst. In addition, the flow was assumed to occur in the axial direction (i.e. the radial
component of the velocity was assumed negligible). Figure 4-2 shows the control volume
with the major heat inputs and outputs at the boundaries.
Steam Reformer Walls
Catalyst Pellets
Methanol + Water ReformateReaction Chamber
Figure 4-1. General schematic of modeled steam reformer reactor
Figure 4-2. Control volume diagram
31
Heat Transfer
Based on the chosen control volume and the aforementioned assumptions, the heat
transfer equation can be derived (Equation 4-1).
( )xTCu
dVdE
xTk
rTk
rT
rk
tTC gaspgas
geffeff
effeffeff ∂
∂−+−
∂∂
+∂∂
+∂∂
=∂∂
•
,2
2
2
2
1 ερρ (4-1)
The variables in Equation 4-1 are defined as follows: ρeff is the effective mass
density of the catalyst-gas mixture, Ceff is the effective specific heat of the catalyst-gas
mixture, T is the temperature inside the control volume, keff is the catalyst-gas mixture
effective conductivity, r is the radial coordinate, x is the axial coordinate, d is the net
rate of heat absorbed by chemical reactions, V is the reformer volume, ρ
gE•
gas is the density
of the gas, e is the void factor of the reformer, and gaspC , is the average specific heat of
the gas. The thermal capacitance of the mass inside the control volume is assumed to be
mostly because of the catalyst. Therefore ρeffCeff is approximately equal to the catalyst
density (ρc) multiplied by the catalyst specific heat (Cc) and the void factor (ε).
The use of effective properties for modeling of catalytic reactors is a fairly common
practice. Incoprera et al., in their widely used heat transfer text book, “Fundamentals of
Heat and Mass Transfer,” describes heat transfer correlations for packed bed systems
using effective gas/packed-bed properties [17]. In published literature, various methods
for determining packed-bed effective thermal conductivity have been explored. Typical
of this work are the studies conducted by Munagavalasa et al. [18], and Brucker et al.
[19].
32
The convection term in Equation 4-1,xTCu gaspgas ∂∂
,ρ , for modeling purposes was
assumed to be small as compared to the radial conduction terms. Typically, temperature
gradients in the radial direction are typically higher than those in the axial direction
through most of the steam reformer. A possible exception to this could occur at the
entrance of the reformer if the entrance temperature is significantly different than the
reformer catalyst bed temperature. As an example of the disparity between the convection
and conduction terms, an order of magnitude analysis of these, based on data obtained
from the UC-Davis reformer (see Appendix C), is presented in Figure 4-3. The analysis is
executed for a run in which various changes in methanol flow were executed. The results
were obtained from temperature data recorded at the entrance regions of the reformer. A
finite difference approximation of the derivative and second derivative of temperature in
the axial and radial directions, respectively, were calculated using K-type thermocouple
readings. The radial thermocouples were placed at the wall, at half the radius and at the
midpoint, where the radius of the tube was 11.9 mm. The axial thermocouples were 67.6
mm apart. It is recognized that the significantly larger axial distances used to approximate
the finite difference axial temperature gradient leads to greater averaging. This in turn
may lead to an underestimation of the axial gradient in the entrance region. In spite of its
limitations, this analysis provides a general relative magnitude of the axial and radial
temperature gradients. During most of the run, the convection term did not exceed 0.4%
of the value of the conduction term. This, in order of magnitude terms, supports the
decision to disregard the convection term in the energy equation. The UC-Davis reformer
is discussed in greater detail at the latter sections of this chapter and in Appendix C.
33
Figure 4-3. Convection-conduction ratio in the UC-Davis reformer fuel entry regions
The heat dissipated in the catalyst bed is due to the reforming reaction.
Consequently, d is a function of the rate in which methanol is reacted in the steam
reforming reaction,
gE•
[ ]⎟⎠⎞
⎜⎝⎛
dtOHCHd 3 . This in turn is a function of the temperature (T),
catalyst volume (dVc), and the molar concentration of methanol in the reformate
gas ( )OHCHx3
. The rate of methanol consumed per unit mass of catalyst (rM) and can be
obtained using Equation 4-2
[ ]( )
[ ]),,(
211
3
33OHCH
ccM xPTf
dtOHCHd
drrdrdxdtOHCHd
mr =
−==πρ (4-2)
The calculation of the rate of methanol reacted in a CuO/ZnO catalyst for
methanol-steam reforming reactions was extensively studied by Nakagaki et al. at
Toshiba Power Systems [12]. One of the results of this study has provided a good
correlation for rM, shown here:
34
3.113.0
/1010 toequal sit' otherwise513K T if 10
)/(1035.1513
5
6
3
==
×=
>−=⋅⋅×=
⎟⎠⎞
⎜⎝⎛=
−
nl
molJEm
atmsgmolk
xeTPkr
cato
nOHCH
RTEm
loM
(4-3)
The Nakagaki correlation is an empirical variation of the Arhenius equation and
was obtained experimentally. Further information regarding the Nakagaki study is found
in the literature review chapter of this text.
Given these relationships, d can be defined explicitly (Equation 4-4). gE&
[ ]Mrcrg rEdrrdxdr
dtOHCHdEEd )2(3 +==
•
περ (4-4)
where the expression for the heat of reaction per mole of methanol consumed is
expressed as Er.
Therefore the energy equation for the control volume can be rewritten as Equation
4-5.
c
Mr
CrE
xT
rT
rT
rtT
−∂∂
+∂∂
+∂∂
=∂∂
2
2
2
2
ααα (4-5)
The quantity is a function of temperature, thus Equation 4-5 is non-linear.
This non-linearity is the source of the complex and sometimes unexpected behavior
associated with packed bed steam-reformers. The boundary conditions for the heat
equation (Equation 4-5) are
Mr rE
35
i
Lx
ing
w
r
TtTxT
TxTTRrT
rT
==
=∂∂
====
=∂∂
=
=
)0(
0
)0()(
0
,
0
(4-6)
Given these boundary conditions the energy equation can be solved by using a
finite difference scheme or using finite element analysis. Also, Equation 4-5 can be made
non-dimensional to yield:
2* * 2 * 2 2 *
* * *2 2 *2
* * ** 2
1
, , ,
M r
w
w
R r ET T T R TFo r r r L x T
T r x tT r x FoT r L R
αα
∂ ∂ ∂ ∂= + + −
∂ ∂ ∂ ∂
= = = = (4-7)
For purposes of this study, the heat transfer model was solved in dimensional terms
in order to relate results to real physical parameters which can be readily verified through
experimentation.
Continuity
The fluid flow within the steam reformer tube is transient, compressible and
viscous. If it is assumed that the mean flow travels in the axial direction (ux >> ur), then
the continuity equation can be written as Equation 4-8.
( )xu
txgg
∂
∂=
∂
∂−
ρρ (4-8)
where ux is the axial component of the fluid velocity vector, and ρg is the density of the
fluid. If the fluid is assumed to be an ideal gas, then the continuity equation can be
written in terms of fluid temperature. In addition, it is convenient to use mass flow rate,
36
m& , instead of the velocity because cross-sectional averages of the velocity will be used.
This yields
tT
RTPA
xm cs
∂∂
=∂∂
•
2 (4-9)
In essence Equation 4-9 states that variations in the axial mass flow are a function
of the transient change in temperature at any given location inside the reformer.
However, reformer data collected from the UC-Davis reformer suggests that tT∂∂ for
methanol steam reformers is small even at the entrance, centerline region (Zone 1 and
Zone 2). This is because the thermal capacitance of reformer catalysts is relatively high,
and because the primary mode of heat transfer is through conduction, which is relatively
slow. Figure 4-4 shows recorded values of tT∂∂ from the UC-Davis reformer. For
illustration purposes, even if the maximum value exhibited was held at ~2 K/s (the
maximum recorded from the UC-Davis reformer during reformer warm-up) and
assuming that this level of heating were to be carried out through out the entire reformer,
the change in reformate mass flow rate that would be detectable at the reformer exit
would be 0.018% for a 1 meter long reformer, based on Equation 4-10.
dxtT
RTPAmm
Lcs
inout ∂∂
∫=−0
2&& (4-10)
Therefore, the mass flow rate within the reformer will have very small transient
variations. Despite this, Equation 4-10 was used in the elaboration of the reformer model.
Temperature distribution plots for the UC-Davis reformer at varying flow rates are shown
in Figure 4-5. Note: for modeling purposes the pressure drop in the reformer was
neglected.
37
UC-Davis Reformer dT/dt values
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
0 10 20 30 40 50 60 70 8
Run Time (min)0
Zone1 dT/dt Zone2 dT/dt
Cal
cula
ted
dT/d
t [K
/s]
Figure 4-4. Calculated values of dT/dt for the UC-Davis reformer at the entrance region
Figure 4-5. Measured temperature distributions of the UC-Davis steam reforming test rig operating at varying space velocities and varying conversion efficiencies
38
Conservation of Specie
The continuity equation for each of the component gases in the control volume can
be written as Equation 4-11.
genjoutjinj mmmt
m
jjj
j
,,,j
orvolume
control theinside ofproduction of rate
volumecontrol theofout
of flow mass
volumecontrol theinto
of flow mass
volumecontrol thein of mass of
increase of rate
•••
+−=∂
∂
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡+
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡−
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡=
⎥⎥⎥
⎦
⎤
⎢⎢⎢
⎣
⎡
(4-11)
The component gases in the steam reformer products are assumed to be methanol,
water vapor, carbon dioxide, carbon monoxide, and hydrogen. The mass generated of
component j inside the control volume can be estimated using the Nakagaki correlation
(Equation 4-3) and chemical equilibrium. Thus, for a control volume at a certain
temperature and pressure, the rate of methanol reacted is known and, consequently, the
rate of generation of the product gases is also known. The rate of mass of specie j
entering the control volume is generally known from boundary conditions. However the
rate of mass escaping the control volume must be calculated.
For purposes of the model it was assumed that all species flow at the same axial
velocity as the bulk flow. The bulk flow velocity exiting the control volume can be
expressed as Equation 4-12.
outj
L
cs
in
cs
incs
cs
out
csout
outout udx
tT
TT
PARTm
PA
RTmdxtT
RTPA
PARTm
Amu ,
02
2 1=∫ ⎟
⎠⎞
⎜⎝⎛∂∂
+=⎟⎟⎠
⎞⎜⎜⎝
⎛∫ +⎟
⎠⎞
⎜⎝⎛∂∂
===&
&&&
ρ (4-12)
Consequently, the mass flow rate of the exiting gas j is given by Equation 4-13.
39
outjoutjcsj
outj mxuRT
APm && == ,, (4-13)
In the above equation, Pj is the partial pressure of gas j inside the control volume.
The term xj is the molar concentration of gas j, and is defined as Equation 4-14.
ott
N
jj
joj
n
nttx
==∑
==
1
)( (4-14)
Chemical Model
The chemical reaction for steam reforming of methanol being considered is shown
in Equation 4-15.
OHeCHdHcCObCOOaHOxHOHCH 322223 ++++→+ (4-15)
In a control volume a certain rate of methanol can be reacted (rMmc). The remaining
methanol and water that enters the control volume is not reacted (Figure 4-6). It was
assumed that the water-gas shift reaction is not the time limiting step in the reformer
reaction and thus proceeds to equilibrium rather quickly. For modeling purposes the
water gas shift reaction was assumed to reach equilibrium concentrations, while the
reforming of methanol was bound by the rate of reaction constraints of the control
volume. Similar approximations have been made in literature and the work of Rabou et
al. [20] is an example.
40
Methanol (mol/s)Water
reacted (mol/s)
Not reacted (mol/s)
CO2
H2
CO
CV
H2
COCO2
Methanol (mol/s)Water
H2
COCO2
Figure 4-6. Schematic representation chemical reaction model in the control volume.
The chemical equilibrium fractions for the water gas shift reaction can be
calculated in the following way.
The specie balance of the complete steam reforming reaction (e and f are equal to
zero) leads to
dxa −+= 2 (4-16)
2−= db (4-17)
dc −= 3 (4-18)
The solution for d can be obtained from the water-gas shift reaction
(Equation 4-19)
222 COHCOOH +↔+ (4-19)
The equilibrium constant for the water gas shift reaction can be approximated with
the Moe (1962) correlation [21] (Equation 4-20).
TK p
8.457733.4ln +−= (4-20)
where T is the temperature of the reaction in Kelvin. Given this,
41
( )[ ])1(2
254442 222
−+−−+++−−−
=Kp
KpxKpKpKpKpxKpKpxd (4-21)
With these equations the number of moles of each chemical component per mole of
methanol reacted can be obtained as a function of temperature. The number of moles of
methanol reacted can be obtained from the Nakagaki correlation (Equation 4-3). The
equilibrium heat of reaction and products as a function of temperature for the methanol
steam reforming reaction is given in Figure 4-7.
Equilibrium Reformate Composition
0
0.5
1
1.5
2
2.5
3
3.5
298 398 498 598 698 798 898 998
Temperature (K)
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
CO2 H2 CO Hr [kJ/kmol of MeOH]
Hea
t of R
eact
ion
[kJ/
km
ol o
f Met
hano
l rea
cted
]
Gas
Com
posi
tion
[km
ols/
km
ol o
f Met
hano
l rea
cted
]
Magnitude Depicted in Secondary Axis
Figure 4-7. Equilibrium products of the steam reforming reaction (CH3OH + H2O
aH2O + bCO2 + cCO + dH2) with respect to temperature
Finite Difference Solution
The control volume analysis easily leads to a finite difference solution of the heat
transfer and fluid flow problem presented in the previous sections. A grid was set up
where each element has a temperature (Tm,n), in which m represents the node index in the
42
x-direction and n represents the node index in the r-direction (as shown in Figure 4-8).
The derivatives of the catalyst bed temperature were approximated to be
( )
( )
rTT
rT
rTTT
rT
xTTT
xT
nmnm
nmnmnm
nmnmnm
∆
−≈
∂∂
∆
−+≈
∂∂
∆
−+≈
∂∂
−+
−+
−+
2
2
2
1,1,
2,1,1,
2
2
2,,1,1
2
2
(4-22)
Similarly the time derivative of the temperature could be written as
tTT
tT l
nml
nm
∆
−≈
∂∂
+,
1, (4-23)
where l is the time index.
x∆
r∆
x∆
r∆
x∆
r∆m+1,n
m,n+1
m,n
x
rR
0
Figure 4-8. Separation of the reformer volume into annular elements with constant gas properties in space for the finite difference solution method used
Given these equations, Equation 4-5 could be rewritten as
43
( ) ( )( )
c
lnmMr
lnm
lnm
lnm
cc
lnm
lnm
lnm
lnm
lnm
lnm
lnm
CrE
xTTT
Ck
rTTT
rTT
r
tTT
1,
2,,1,1
2,1,1,1,1.
,1
,
22
22
+
−+−+−+
+
−⎥⎥⎦
⎤
⎢⎢⎣
⎡
∆
−++
⎥⎥⎦
⎤
⎢⎢⎣
⎡
∆
−++
⎥⎥⎦
⎤
⎢⎢⎣
⎡
∆
−
=∆
−
K
Kρ
αα
(4-24)
Similarly the boundary conditions can be rewritten (Equation 4-25).
inm
lnM
lnM
ingl
n
lNm
lNm
wl
m
TT
TT
TT
TT
TT
=
=
=
=
=
−
−
0,
,2,
,,0
2,,
0,
(4-25)
The term is unknown and it is a function of the finite volume
temperature and methanol concentration. At first, the temperature equation can be solved
assuming a temperature and a methanol concentration. For the computer program
developed for this study, T
( ) 1,
+lnmMrrE
m,nl+1 was initially assumed approximately equal to Tm,n
l.
Similarly the concentration of methanol inside the volume, xCH3OH,m,nl+1 was at first
approximated to be equal to xCH3OH,m,nl. Once an approximate solution for the temperature
was obtained the conservation of specie equation was solved.
The finite difference expression for 4-10 is given by
1,,
1,,
1,1,
,,,, +++−
+
+−=∆
− lgennm
lnmj
lnmj
lnmj
llnmj mmm
tmm
&&& (4-26)
The expression for the mass flow of specie j leaving the finite volume can be
expressed as
44
( ) ( ) ⎥⎥
⎦
⎤
⎢⎢
⎣
⎡ −−
−
∆∆
=+
+
+−
−+
−+
+21
,
,1
,21
,1
,11
,11
,,1,, 5.0
lnm
lnm
lnm
lnm
lnm
lnmcs
lnmjl
nmjT
TT
T
TTtx
RPAx
m& (4-27)
Note that as with the temperature solution, xj,m,nl+1 is unknown. In the computer
program this value was initially assumed to be equal to xj,m,nl. From the solution of the
content of all the species in the finite volume using Equation 4-24 and 4-27, for a given
temperature field, a new value for the molar concentration of each component can be
obtained (Equation 4-28).
∑ ⎟⎟⎠
⎞⎜⎜⎝
⎛
⎟⎟⎠
⎞⎜⎜⎝
⎛
=+
+
+
N
i i
lnmi
j
lnmj
lnmj
MWm
MWm
x1
.,
1.,
1,, (4-28)
This new, revised solution for xj,m,nl+1 was used to solve for the finite volume
temperature and mass contents. This process was carried out until satisfactory
convergence was achieved.
FEMLAB Solution
Besides using a finite difference scheme, the system of differential equations was
solved using finite element analysis using FEMLAB Multiphysics modeler software. The
FEMLAB software is designed to solve systems of coupled partial differential equations
using proprietary solution schemes based on finite element analysis. The system of partial
differential equations for transient heat equation (including the convection term),
transient conservation of species, transient continuity, chemical equilibrium and the
Nakagaki correlation were programmed into the FEMLAB solver. A triangular element
grid was used to cover the two-dimensional reformer space. Appendix B specifies details
45
of the number of elements and number of degrees of freedom for each of the reformers
modeled.
The results of the FEMLAB finite element solution and the finite difference
solution were similar and compatible. However, it was found that the finite difference
solution resulted in lower reformate CO concentration. This was due to problems with the
inherent lower magnitude of CO concentration in the reformate gas as compared to water,
hydrogen and carbon dioxide concentrations. This difference created problems with
convergence and minimum error search. The FEMLAB solver uses sophisticated
minimum error search schemes which include parameter step annealing and magnitude
parity. Because of this computational error reduction feature, the FEMLAB solution was
assumed to have a higher degree of accuracy than that of the finite difference scheme.
Steam Reformer Model Validation
Validation of the steam reformer model results were done through comparison of
the performance of modeled steam reformers with the UC-Davis reformer. Experiments
were conducted using a small-scale laboratory steam reformer located at the University of
California – Davis (See Appendix C). Data from this experimentation was used for model
validation. The UC-Davis reformer was built and instrumented by Dr. Paul Erickson and
his students. Experiments for this study were conducted by UC-Davis students under the
direction of the author of this dissertation. The experimental plan was also developed by
this author for the purposes of this study. Various peer-reviewed publications have been
based on research conducted using the UC-Davis reformer. These include Liao et al. [22],
Yoon et al. [23], and Betts et al. [24] (the latter regarding some of the results of this
study).
46
Data obtained from the UC-Davis reformer cannot be used as a complete model
validation tool. The reformer suffers from loose wall temperature control and gas
sampling limitations that inevitably lead to discrepancies between the magnitudes of the
model results and the data collected. Nonetheless, important physical phenomena, such as
transient CO spikes, CO concentration dependence on reformer temperature, and steady-
state and transient reformate composition trends are captured in the data obtained.
Agreement between the model and the UC-Davis reformer were expected to be
approximate.
General Description
The UC-Davis reformer is a catalyst filled cylinder with a radius of 0.47 inches
(0.012 m), and an axial length of 21 inches (0.533 m) (Figure 4-9). The reactor
temperatures are controlled using eight electrical band heaters located on the surface of
the reactor. Thermocouple readings of the internal wall temperature of the reactor and the
centerline temperature are used to gauge the level of chemical activity in a certain region
of the reformer and are also used as feedback controller inputs for the heaters. The
reformer heaters operate in on or off mode, as triggered by computer controlled relays. A
simple feedback control loop, programmed in Labview, was used to maintain a constant
wall temperature.
Before entering the reformer water and methanol are vaporized and superheated
using a series of pipes containing cartridge heaters. The temperature of the reactants
entering the reformer is recorded and is controlled via a control and data acquisition
computer, which is capable to turning on or off the vaporizer and super-heater heaters.
Water and methanol fuel flows are metered using positive displacement gear pumps. The
47
gear pump RPM was used to measure flow. A scale, on top of which the reactants sat,
was also used to measure methanol and water flow into the reformer.
Reformate gas analysis was done using a NOVA Analytical Systems, Inc. gas
analyzer (Model 7904CM). This analyzer was designed for simultaneous analysis of
hydrogen, carbon dioxide, methane, and carbon monoxide. The instrument recorded
carbon dioxide, carbon monoxide and methane using a Non-Dispersive Infrared (NDIR)
detector with temperature and pressure compensation. Hydrogen was detected using a
temperature controlled thermal conductivity (TC) cell.
Before being analyzed for composition, the reformate gases were cooled to an
almost freezing temperature (i.e. ~0oC) and the condensed liquid was extracted. The UC-
Davis reformer was designed with the capability to capture all condensed liquids before
gas sampling to perform conversion studies. Due to the condenser volume, a short time
response delay exists in the gas analysis data. Although the exact time response delay is a
complex computation problem that falls outside the scope of this study, a general
estimation can be performed. The length of the condenser tube is 18ft (5.5m). Reformate
enters the condenser at approximately 300oC and leaves at approximately 0oC. If the mass
flow rate of fuel entering the reformer is assumed to be the same as that entering the
condenser, then the reformate volume flow entering the condenser can be calculated. For
purposes of estimation the mass flow rate leaving the condenser can be said to be equal to
the reformate mass entering it. Based on these assumptions the time it would take the
time it would take to have a complete condenser volume gas change (i.e. retention time)
for a premix flows at STP ranging from 5 mL/min to 30 mL/min would range between
1.3 to 0.2 seconds. Additionally, for all premix fuel flow rates, the flow through the
48
condenser can be estimated to be mostly laminar due to low Reynolds number. This
means that a well organized concentration boundary layer is expected to exist within the
condenser pipe. Therefore, although the reformate gas composition may change, traces of
previous reformate gas could still be trapped in the boundary layer, close to the walls.
This may lead to a decrease in the sharpness of the data obtainable from the gas analyzer.
The NOVA gas analyzer manufacturer-quoted response time is 3 seconds to 90%
response. The gas analyzer takes samples at a rate of 1 L/min through a positive
displacement pump. At this flow rate the condenser unit would have a retention time in
the order of 1 s. Since the response time is in the order of seconds and the measurable
effects (that is reformate gas concentration changes) occur in the order of minutes, these
effects are recordable using the UC-Davis hardware configuration.
In terms of time response, passage through the vaporizers may be the limiting
factor. For the model, the fuel flow rate boundary condition is at the inlet of the reformer.
This is not the case for the UC-Davis reformer. If it were assumed that only liquid fuel
passes through the vaporizers, then the residence times of the vaporizers would be as
shown in Table 4-1. The estimated residence times presented in this table are maximum
values. For lower fuel flows the space velocity is over-estimated because vaporization
occurs earlier in the vaporizer tube, which increases the volume flow rate of the fuel.
Also, the degree in which vaporization occurs within the vaporizers is not immediate and
this will result in a ramped increase in fuel flow into the reformer instead of a step
increase as in the model. This should result in smoother, drawn-out, transient gas
composition data for the UC-Davis reformer.
49
Table 4-1. Estimated maximum times for vaporizer volume flow change. Fuel Flow Rate (cm3/min) Vaporizer residence times 5 5 min 10 3 min 15 2 min 20 1.3 min 25 1 min 30 ~50 s
Experimental Method
The reformer catalyst bed was maintained idle for storage completely sealed and
pressurized with carbon dioxide. This process ensured minimum catalyst deactivation due
to oxidation. For experimentation, the reformer was first heated using the reformer band
heaters under a CO2 gas purge. Once the appropriate reformer temperature was reached
(250oC), vaporized and superheated water and methanol were introduced. The experiment
maintained the reformer wall temperature at a nominal 300oC with fluctuations due to
heater binary control. Water-methanol flows between 5 and 30ml/min were passed
through the reformer in 5ml/min intervals. Changes in methanol-water flows were
executed every 10 minutes. The data sampling rate was two seconds.
UC-Davis Reformer Data
The data obtained from the UC-Davis reformer shows the following trends:
• There is a temporary increase in the CO concentration in the reformate gas leaving the reformer when there is an increase in fuel flow rate into the reformer (Figure 4-10).
• The CO concentration in the reformate is very closely related to the catalyst bed temperature (Figure 4-11). Catalyst bed temperature fluctuations in the UC-Davis reformer were mostly because of band heaters binary operation and imposed control scheme.
• The steady-state CO concentration in the reformate lowers with increased fuel flow rate into the reformer (Figure 4-10 and Figure 4-12).
50
Figure 4-9. Experimental steam reformer developed at UC Davis
CO Spike Due to Change in Flow Rate0
2
4
6
8
10
12
14
16
22 23 24 25 26 27 28 29 30
Run Time (min)
0
0.5
1
1.5
2
2.5
3
Pump feedback (ml/min) CO concentration (%)
Increased levels of CO are registered when there is an increase in flow rate
Steady state CO levels are lowered with increased flow rate
Data obtained at U.C. Davis on 2/5/2004
Met
hano
l - W
ater
Mix
Flo
w R
ate
CO
Con
cent
ratio
n (%
)
Figure 4-10. Example of CO spike in the reformate of the UC-Davis reformer after an
increase in premix fuel flow (transient condition). Also shown is a decrease of the steady-state CO concentration in the reformate with increased premix fuel flow rate in units of mL/min.
51
Relationship between CO production and Catalyst Temperature
200
210
220
230
240
250
260
270
280
290
300
5 15 25 35 45 55 65 75
Run Time
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Reformer Exit Centerline Temperature Average Centerline Temperature (oC)CO concentration (%)
Tem
pera
ture
( o C
)
CO
Con
cent
ratio
n (%
)
Magnitude is depicted in secondary axis
Figure 4-11. Reformate CO composition relationship to changes in temperature in the
reformer catalyst bed1
Feb. 5th, 2004 Test Run at UC Davis
0
10
20
30
40
50
60
70
80
5 15 25 35 45 55Run Time (min)
0
0.5
1
1.5
2
2.5
3
Pump feedback (ml/min) H2 concentration (%) CO concentration (%)
H2 G
as C
once
ntra
tion
(%)
Pre
mix
Flo
w R
ate
(std
. mL/
min
)
CO
Gas
Con
cent
ratio
n (%
)
CO Spike
CO Spike
Figure 4-12. CO and H2 concentrations in the reformate gas in the UC-Davis reformer
1 The drastic decrease in CO concentration at the end of the graph comes as a result of shutting down the premix flow into the reformer.
52
It was a major goal of this investigation to be able to analytically reproduce the
general operating characteristics of actual reformers. For this purpose an analytic version
of the UC-Davis reformer was developed using the heat and chemical rate equations
previously outlined. The virtual version of the UC-Davis reformer exhibited all of the
major performance characteristics of the actual reformer to varying extents.
The constants used for the virtual reformer are shown in Table 4-1 and were
matched as best as possible, to measured or inferred UC-Davis reformer constants.
Table 4-1. Values constants used to develop virtual UC-Davis reformer Name Value Used How it was
determined Catalyst Bed Heat Capacity (Cc) 900 J/kg-K Inferred Catalyst Bed Thermal Conductivity (keff) 5.00 W/mK Estimated
from Data Catalyst Bed Density (eρc) 1983. kg/m3 Measured Length (L) 0.53340 m Measured Radius (R) 11.9 x 10-3 m Measured # of Radial Elements (NR) 5 Number of Axial Elements (NL) 150 Time Step (∆t) 0.5 s * The catalyst heat capacity was assumed to be equal to an average of the heat capacities of copper and zinc. ** The catalyst heat capacity was assumed to be equal to an average of the heat capacities of copper and zinc. *** The void factor used was 50% and the catalyst density was measured via a water displacement method for a single pellet.
To determine the value for catalyst bed thermal conductivity (keff), an average was
taken of the measured thermal conductivity of the UC-Davis reformer catalyst bed at
different points during the warm up stage, when no fuel flow exists. Figure 4-13 shows
an example of the data used a band heater zone in the UC-Davis reformer.
The resulting steady-state carbon monoxide composition of the virtual UC-Davis
reformer are shown in Figure 4-14. In arrows are listed the average steady-state CO
53
compositions for the actual UC-Davis reformer. In this figure, note that greater flow rate
results in lower steady-state CO concentrations.
Error between the UC-Davis reformer steady-state CO concentration and that of the
virtual reformer is potentially due to the existence of un-reacted methanol in the sampled
gas. Although before sampling the reformate gas was cooled to extract condensate, the
difference between methanol and water freezing temperature only permitted a reduction
in temperature to almost 0oC. The existence of unreformed methanol in the sampled gas
is detectable through the methane (or hydrocarbon) signature detected by the NOVA gas
analyzer (Figure 4-15).
Zone 2 Thermal Conductivity
200
220
240
260
280
300
320
340
0 1 2 3 4 5
Time (mins)
Tem
pera
ture
(oC
)
0
1
2
3
4
5
6
Cal
cula
ted
Ther
mal
C
ondu
ctiv
ity (W
/(m-K
))
Zone 2 Surface Zone 2 Exit Wall Zone 2 Exit Centerline Effective Conductivity
Average Conductivity = 4.87 W/(K-m)
Figure 4-13. Estimation of catalyst bed thermal conductivity using UC-Davis reformer
data
54
1.98E-021.98E-021.98E-021.98E-021.98E-021.98E-021.98E-021.98E-021.98E-021.98E-02 1.96E-021.96E-021.96E-021.96E-021.96E-021.96E-021.96E-021.96E-021.96E-021.96E-02 1.92E-021.92E-021.92E-021.92E-021.92E-021.92E-021.92E-02 1.89E-021.89E-021.89E-021.89E-021.89E-021.89E-021.89E-021.89E-021.89E-021.89E-02 1.87E-021.87E-021.87E-021.87E-021.87E-021.87E-021.87E-021.87E-021.87E-021.87E-02 1.85E-021.85E-021.85E-021.85E-021.85E-021.85E-021.85E-021.85E-021.85E-021.85E-021.72E-021.72E-021.72E-021.72E-021.72E-021.72E-021.72E-021.72E-021.72E-021.72E-02 1.68E-021.68E-021.68E-021.68E-021.68E-021.68E-021.68E-021.68E-021.68E-021.68E-02 1.61E-021.61E-021.61E-021.61E-021.61E-021.61E-021.61E-021.61E-021.61E-021.61E-02
1.52E-021.52E-021.52E-021.52E-021.52E-021.52E-021.52E-021.52E-021.52E-021.52E-021.44E-021.44E-021.44E-021.44E-021.44E-021.44E-021.44E-021.44E-021.44E-021.44E-02 1.36E-021.36E-021.36E-021.36E-021.36E-021.36E-021.36E-021.36E-021.36E-021.36E-02
0.0000
0.0050
0.0100
0.0150
0.0200
0.0250
0 5 10 15 20 25 30 35
Premix Flow (std.mL/min)
CO
(mol
e fr
actio
n)
x CO (dry) x CO (dry w/ MeOH)
1.14%UC-Davis
0.93%UC-Davis
Figure 4-14. Virtual UC-Davis reformer steady-state CO composition with varying premix fuel flow rates
0
2
4
6
8
10
12
0 10 20 30 40 50 60 70 8
Run Time (min)
Sign
al O
utpu
t
0
Figure 4-15. Hydrocarbon signal output obtained during UC-Davis reformer run.
55
Figure 4-16 shows a representative CO spike at the point in which the premix flow
rate changes from 10 to 15 ml/min. The change in flow rate was produced at time zero.
This figure is meant to be a parallel to Figure 4-10. Figures 4-16 and 4-17 show the
temperature distributions of the modeled reformer for 5 ml/min and 30 ml/min flow rate,
respectively. The temperature distribution is similar to those recorded for the UC-Davis
reformer (Figure 4-4), where the minimum temperature is recorded at the reformer
entrance region. These results support the observations made from data obtained from the
UC-Davis reformer and therefore demonstrate the validity of the assumptions made in the
model presented.
Virtual Reformer CO Spike (10 to 15ml/min)
0.0158
0.0159
0.016
0.0161
0.0162
0.0163
0.0164
0.0165
0 10 20 30 40 5
Time After Point of Flow Rate Change (s)
CO
Mol
e Fr
actio
n
0
Figure 4-16. Virtual UC-Davis Reformer CO spike from 10 to 15ml/min premix flow rate
change
56
Figure 4-17. Virtual UC-Davis reformer temperature distribution (color plot) and
methanol concentration (contour plot) for premix flow rate equal to 5 ml/min
Figure 4-18. Virtual UC-Davis reformer temperature distribution (color plot) and
methanol concentration (contour plot) for premix flow rate equal to 30 ml/min
57
Reformer Design
Currently, most reformer design is done based on a space velocity basis. This
method is not consistent with the complex nature of the reforming reaction and the
virtually infinite number of possible reformer designs. As part of this study, a set of non-
dimensional reformer performance variables are introduced in order to provide generality
to the results obtained from analytical modeling and experiments. This section generally
describes some parameters that affect reformer performance. In particular the question of
how reformer length, catalyst loading and fuel flow rate affects the reformate gas
composition is investigated using these suggested non-dimensional parameters.
Design Generalization
It has already been established that heat transfer and chemical rate characteristics
are major determinants of complex reformer performance. Equation 4-5 can be rewritten
as Equation 4-29.
Mrceffeffeff
c rExTk
rTk
rT
rk
tTC ερρε −
∂∂
+∂∂
+∂∂
=∂∂
2
2
2
2
(4-29)
In order to generalize the design of reformers, it is useful to define non-dimensional
variables. For a reformer tube of a certain radius (R), the volume of catalyst in the
reformer (Vc) will determine the length of the reformer (L). According to Nakagaki and
other correlations it could be said that the mass of the reformer has a potential
reformation capacity, Ω. The potential reformation capacity of the catalyst could be
defined as the theoretical hydrogen power (PH2) that a certain mass of catalyst could
produce if the reformer were maintained exactly at the wall temperature, and with the
inlet methanol concentration. This can be easily calculated by using the Nakagaki
58
correlation. For example, the potential reformation capacity of the UC-Davis reformer
can be calculated in the following way.
The catalyst mass in the UC-Davis reformer is
( ) ( ) ( )[ ] kgmmmkgLRVm ccc 470565.05334.00119.01983 2
32 =⎟
⎠⎞
⎜⎝⎛=== ππερερ (4-30)
If the wall temperature were to remain constant at 300oC, then rM,max and the
potential rate of methanol reacted ( )can be calculated as shown in
Equation 4-31.
max,,3 reactedOHCHn&
( )
sec108921.4
sec100396.1,
5max,,3
4,3max,
kmolmrn
kgkmolxTr
cMreactedOHCH
inletOHCHwM
−
−
×==
⋅×=
&
(4-31)
Since the theoretical chemical reaction for the reformation of methanol yields three
moles of hydrogen per mole of methanol, the potential reformation capacity (Ω) can be
obtained as shown in Equation 4-32.
kWkmolkmolkJnLHV reactedOHCHH 4609.35
sec108921.424162033 5
max,,32=⎟
⎠⎞
⎜⎝⎛ ×⎟⎠⎞
⎜⎝⎛==Ω −&
(4-32)
Also a non-dimensional temperature, θ, can be defined as
wTT
=θ , (4-33)
and a non-dimensional length and radius can be defined as
Rrr =*
(4-34)
Lxx =*
(4-35)
59
Given these formulations, Equation 4-29 can be non-dimensionalized to yield
Ω−
∂∂
Ω+
∂∂
Ω+
∂∂
Ω=
∂∂
ΩVrE
xVTR
rRkVT
rrRkVT
tTCV Mrcweffweffwwcc ερθπθθθερ
2*
24
2*
2
2**2
1
(4-36)
Equation 4-38 is made up of various important non-dimensional groups. A non-
dimensional conductivity, k*, can be expressed as
Ω= 2
*
RkVT
k effw
(4-37)
The non-dimensional conductivity can be construed as a measure of the ratio
between the potential radial conduction heat transfer into the reformer and the potential
rate of energy absorbed by the reforming reaction. It is important to point out that the
non-dimensional conduction is not actually a function of catalyst length. The non-
dimensional conduction could be expressed as
22
*
3 RLHVkT
kcH
effw
ερ=
(4-38)
For the UC-Davis reformer the non-dimensional conduction is equal to 0.135.
The last term in Equation 4-36, is a measure of the ratio of the actual rate of energy
absorbed due to the reformation reaction and the potential rate of energy absorbed by the
same reaction in terms of hydrogen production. The potential reformation capacity, Ω, is
actually a measure of the potential hydrogen production of a certain mass of catalyst at a
certain temperature. Thus it would be convenient to express the last term in
Equation 4-36 in terms of hydrogen production and not methanol consumption. In
practical terms the hydrogen production is easier to measure than the methanol converted.
60
With this formulation a catalyst effectiveness, λ, can be defined as the ratio of the
actual hydrogen power output obtained from a certain amount of catalyst (PH2) and the
potential reformation capacity of the catalyst (Ω) (Equation 4-39).
Ω= 2HP
λ (4-39)
The catalyst effectiveness is a measure of the degree of reforming activity that a
certain mass of catalyst undergoes. High catalyst effectiveness is desirable because it
means that the reformer is operating closer to its idealized potential hydrogen yield. High
catalyst effectiveness occurs in short reformers. On the other hand, the larger the
reformer, the lower the catalyst effectiveness will be.
From Equation 4-40, it is also notable the time constant term, τ,
max,23 MH
wcwcc
rLHVTCTCV
=Ω
=ερτ
(4-40)
The transient response in a reformer would be strongly determined by τ. A low
value of τ would lead to very fast temperature changes in the reformer tube leading to a
decrease in prominence of the CO spikes. For the purpose of fully expressing the heat
equation in non-dimensional terms a non-dimensional time (t*) is defined
(Equation 4-41).
wcc TCVttερΩ
=* (4-41)
The non-dimensional heat equation is
max,22*
24
2*
2*
**
*
* 3 MH
Mrw
rLHVrE
xVTR
rk
rrk
t−
∂∂
Ω+
∂∂
+∂∂
=∂∂ θπθθθ (4-42)
It is also convenient to non-dimensionalize the fuel flow into the reformer as
61
Ω=
•
fuelfuelND
mLHVflow
(4-43)
where LHVfuel represents the lower heating value of the fuel, and represents the
mass flow rate of the fuel. The non-dimensional flow is a ratio between the rate of fuel
energy introduced into the reactor and the reactors reformation capacity. The non-
dimensional flow can be expressed in terms of space velocity (S
fuelm•
v) as shown in Equation
4-43.
cM
infuelvND r
Sflow
ερρ
max,
,
3= (4-44)
Also useful is the definition of reformer efficiency, ηref,
fuel
Href P
P2=η
(4-45)
The chosen reformer efficiency definition neglects the power required to promote
and sustain the reforming reaction. This definition only deals with issues of conversion,
since a detailed analysis of reformer heating design is outside the scope of this study. In
Equation 4-42, represents the rate of hydrogen chemical energy obtained from the
reformer, and represents the rate of fuel energy introduced into the reformer. The
maximum reformer efficiency for a methanol reformer is given by
2HP
fuelP
OHCH
Href LHV
LHV
3
2max,
3=η (4-46)
The non-dimensional flow can be re-written as
⎟⎟⎠
⎞⎜⎜⎝
⎛=
max,,,3
,,3
max,
1
reactedOHCH
inOHCH
refND n
nflow
&
&
η (4-47)
62
Given these definitions, the reformer model was used to obtain characteristic
reformer efficiencies versus catalyst effectiveness curves for reformers with the same
non-dimensional conduction (0.315) as the UC-Davis reformer at various fuel flow rates
and different lengths. These curves are shown in Figure 4-19. Additionally Figure 4-19
shows the corresponding non-dimensional fuel flow rates as a function of catalyst
effectiveness.
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1
Catalyst Effectiveness
0
1
2
3
4
5
6
7
Efficiency (5ml/min) Efficiency (10ml/min) Efficiency (15ml/min)Efficiency (20ml/min) Flow ND (5ml/min) Flow ND (10ml/min)Flow ND (15ml/min) Flow ND (20ml/min)
Effic
ienc
y (%
)
Non
-dim
ensi
onal
Flo
w
Magnitude represented on secondary axis
Figure 4-19. Reformer Efficiency with varying catalyst effectiveness at varying fuel flow rates
From Figure 4-19 certain observations can be drawn. First, for non-dimensional
fuel flow values less than 1, the variations in reformer efficiency versus catalyst
effectiveness and non-dimensional fuel flow versus catalyst effectiveness, collapse into a
single representative performance curve. Second, as mentioned previously, lowered
catalyst effectiveness results in higher reformer efficiency. In other words, longer
63
reformers will exhibit higher steady-state efficiencies at the cost of ever increasing
catalyst mass. Therefore, there are diminishing benefits to a long reformer, which will
have a similar hydrogen yield as a reformer designed with catalyst effectiveness equal to
0.1. As the fuel flow rate of a reformer approaches infinity, the catalyst effectiveness will
approach 1 and the reformer hydrogen yield will approach zero.
These results can be used to scale a reformer using non-dimensional variables. For
the purposes of this study, three reformer designs were considered: an infinite reformer
with catalyst effectiveness equal to 0.05 at maximum power; a mid-size reformer with
catalyst effectiveness equal to 0.1 at maximum power; and a small reformer with catalyst
effectiveness equal to 0.2 at maximum power. The terms small, medium and large are
used as visual clues to the general aspect ratio that these reformers would have in
comparison with each other if the diameter were to remain the same. All reformers were
designed to produce a maximum 60 kW of hydrogen (lower heating value based). If a
reformer tube with the same non-dimensional conduction as the UC-Davis reformer were
to be scaled to produce 60 kW of power, its length and steady-state operating
characteristics would be as shown in Table 4-2, based on steady-state catalyst
effectiveness and reformer efficiency analysis.
Table 4-2. Steady-state design of 60 kW reformer with an 11.9 mm radius and a catalyst bed density of 1983 kg/m3
Catalyst Effectiveness (λ)
Reformer Tube Length (m)
Steady Sate Reformer Efficiency (%)
Premix Power to Produce 60 kW of H2 (kW)
0.05 18.05 112.9 53.14 0.10 9.03 112.5 53.35 0.20 4.51 110.5 54.28
D. Davieau [16] studied the use of space velocity and aspect ratio as major
similitude parameters for reformer design. His conclusions are that these two parameters
64
are not sufficient to fully characterize reformer steady-state conversion and reformate
quality. These conclusions are supported by the analysis presented in this study. The
space velocity and aspect ratio, although important, do not capture the governing physics
of the reformation process.
CHAPTER 5 RESULTS
In this chapter, the primary chemical and heat transfer conditions that produce
variations in hydrogen and carbon monoxide levels in the reformate are presented and
discussed. Special attention is given towards the benefits and detriments associated with
reformer size and catalyst loading in the context of fuel cell system incorporation. For
this purpose three general reformer length with the same non-dimensional conduction
were compared based on their reformate quality.
Transient Efficiency
Case 1 - Infinite Reformer
Figure 5-1 shows predicted transient changes in reformer efficiency for various
changes in non-dimensional fuel flow rates for the infinite reformer. This figure shows
how increasing fuel flow results in an immediate drop in reformer efficiency followed by
a gradual approach to the steady-state efficiency. Figure 5-2 shows the same effects on
the reformer efficiency in terms of the efficiency difference variable, refη~ , defined as
..,~
PSrefrefref ηηη −= (5-1)
The variable ηref,S.P. is the set point efficiency, which is the steady-state efficiency
at a certain flow rate. In other words, for any steady flow rate the difference efficiency is
equal to zero.
The magnitude of the initial efficiency overshoot is summarized in Table 5-1. It is
notable that the magnitude of the efficiency-overshoot increases with increased change in
65
66
non-dimensional flow. However, if the change in non-dimensional flow remains constant,
changes between smaller non-dimensional flow quantities results in less overshoot. The
magnitude of the drop in efficiency before reaching steady-state is also recorded. This is
called an efficiency undershoot. High overshoot magnitudes reduced the extent of the
efficiency undershoot.
Table 5-1. Case 1: Summary of the transient response of the infinite reformer to changes in fuel flow rate
Flow ND Initial Final
Change in ND Flow Overshoot
1.10 2.20 1.10 0.019% 2.20 3.31 1.10 0.027% 3.31 4.42 1.10 0.046% 4.42 5.52 1.10 0.064% 5.52 6.63 1.10 0.072% 1.10 6.63 5.53 0.260%
Infinite Reformer Transient Efficiency
122.6
122.7
122.8
122.9
123.0
123.1
123.2
123.3
0 20 40 60 80
Run Time (s)
Effic
ienc
y (%
)
100
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW50 to 60kW 10 to 60kW
ND Flow Key:10kW: 1.10%20kW: 2.20%30kW: 3.31%40kW: 4.42%50kW: 6.63%
Figure 5-1. Case 1: Infinite reformer operation when undergoing step variations in fuel
flow rate
67
Infinite Reformer Transient Efficiency
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0 20 40 60 80 100
Run Time (s)
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW50 to 60kW 10 to 60kW
ND Flow Key:10kW: 1.10%20kW: 2.20%30kW: 3.31%40kW: 4.42%50kW: 6.63%
Figure 5-2. Case 1: Reformer efficiency changes due to change of fuel flow rate for the
infinite reformer
Case 2 - The Medium Sized Reformer
As with the infinite reformer, the medium sized reformer was subjected to transient
variations in fuel flow. The changes in efficiency of the reformer are depicted in Figure
5-3 and 5-4. Figure 5-4 shows these changes in terms of the efficiency difference
variable. Table 5-2 summarizes these results. As with the infinite reformer, large changes
in non-dimensional flow result in large overshoots, and changes between lower non-
dimensional flows results in lower overshoots.
The magnitude of the efficiency undershoots for the medium reformer were
significantly lower than those of the infinite reformer. In addition, as changes in non-
dimensional flow rates occurred between higher non-dimensional flow rates, the
efficiency undershoot was decreased and even disappeared.
68
Table 5-2. Case 2: Summary of the transient response of the medium size reformer to changes in fuel flow rate
Flow ND Initial Final
Change in ND Flow Overshoot
2.22 4.43 2.22 0.066% 4.43 6.65 2.22 0.129% 6.65 8.87 2.22 0.211% 8.87 11.08 2.22 0.292% 11.08 13.30 2.22 0.372% 2.22 13.30 11.08 1.406%
Medium Reformer Transient Efficiency
121.4
121.6
121.8
122
122.2
122.4
122.6
122.8
123
123.2
123.4
0 20 40 60 80
Run Time (s)
Effic
ienc
y (%
)
100
10 to 20kW 20 to 30kW 30 to 40kW40 to 50kW 50 to 60kW 10 to 60kW
ND Flow Key:10kW: 2.22%20kW: 4.43%30kW: 6.65%40kW: 8.87%50kW: 11.08%60kW: 13.30%
Figure 5-3. Case 2: Transient efficiency of the medium size reformer under transient load
changes
Case 3 - The Short Reformer
As with the infinite and medium sized reformer, the short reformer was run under
transient load conditions as shown in Figure 5-5 and 5-6. In contrast with the larger
reformers, the short reformer did not exhibit efficiency undershooting, except between
step changes in non-dimensional flow between 4.44% and 8.88%. Besides this effect, the
69
results follow a similar pattern to those obtained for the infinite and medium reformers.
The results of the transient run of the short reformer are given in Table 5-3.
Medium Reformer Transient Efficiency
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0 20 40 60 80
Run Time (s)
100
10 to 20kW 20 to 30kW 30 to 40kW40 to 50kW 50 to 60kW 10 to 60kW
ND Flow Key:10kW: 2.22%20kW: 4.43%30kW: 6.65%40kW: 8.87%50kW: 11.08%60kW: 13.30%
Figure 5-4. Case 2: Reformer efficiency changes due to change of fuel flow rate for the
medium size reformer
Table 5-3. Case 3: Summary of the transient efficiency response of the short reformer to changes in fuel flow rate
Flow ND Initial Final
Change in ND Flow Overshoot
4.44 8.88 4.44 0.36% 8.88 13.31 4.44 0.73% 13.31 17.75 4.44 1.06% 17.75 22.19 4.44 1.27% 22.19 26.63 4.44 1.29% 4.44 26.63 22.19 9.33%
70
Short Reformer Transient Efficiency112
114
116
118
120
122
124
0 20 40 60 80
Run Time (s)
Ref
orm
er E
ffici
ency
(%)
100
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW50 to 60kW 10 to 60kW
ND Flow Key:10kW: 4.94%20kW: 8.88%30kW: 13.31%40kW: 17.75%50kW: 22.19%60kW: 26.63%
Figure 5-5. Case 3: Transient efficiency of the short reformer under transient load
changes
Carbon Monoxide Concentration
Generally, temporary increases in CO concentration in the reformate gas occurred
during periods of increased premix flow rates. This phenomenon occurs because lower
fuel flow into the reformer leads to higher average steady-state temperature. This increase
in temperature results from less fuel being reformed, thus lower overall associated
endothermicity. High temperatures promote greater CO and water formation in the water
gas shift reaction. High temperatures typically occur near the exit of the reactor. When
there is an increase in fuel flow into the reformer, the average temperature of the reactor
does not drop immediately and this contributes to better transient conversion (i.e.
increased efficiency), and higher transient CO concentrations. As time progresses the
average temperature of the reactor drops because of the increased endothermicity
71
associated with the increased level of methanol reacted. Eventually the lower average
reformer temperature results in a lower steady-state CO level at higher fuel flow rates.
An off-steady-state CO concentration is defined as
[ ] [ ] [ ]steadysteadyOff COCOCO −=− (5-2)
Short Reformer Transient Efficiency
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 20 40 60 80
Run Time (s)
100
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW 50 to 60kW
ND Flow Key:10kW: 4.94%20kW: 8.88%30kW: 13.31%40kW: 17.75%50kW: 22.19%60kW: 26.63%
Figure 5-6. Case 3: Reformer efficiency changes due to change of fuel flow rate for the
short reformer
Figures 5-7 through 5-13 show the transient CO concentrations and off-steady-state
CO concentrations for the infinite, medium, and short reformer triggered by step changes
in fuel flow into the reformer.
The CO spike is defined as the initial increase in CO concentration that occurs after
a step increase in fuel flow occurs. This spike occurs before there is a gradually
decreasing approach of the transient CO concentration towards the steady-state CO
concentration. In all instances, the larger the non-dimensional flow change the greater the
72
CO spike. However, between equivalent changes in non-dimensional flow, larger CO
spikes occurred between lower non-dimensional flows. For example, in the infinite
reformer, a CO spike 328 ppm larger is recorded for a change in non-dimensional flow
from 1.10% to 2.21% as compared to a change from 2.21% to 3.31%.
CO spikes, as defined here, are a measure of the transient deviation of the CO
concentration as compared to the steady-state condition for the same flow. This deviation
was highest for small reformers, which in order to obtain a certain steady-state hydrogen
flow rate required a large change in non-dimensional flow. However, if Figures 5-8, 5-10
and 5-12 are examined it can be seen that the off-steady-state CO concentration also
includes the unsteady, smooth drop in CO concentration associated with the increased
fuel flow into the reformer. Changes in flow between low non-dimensional flows caused
greater disruptions to this smooth drop. In a fuel cell system these flow changes may
cause variations in fuel cell performance and a degree of CO poisoning during the
transient event if appropriate actions are not taken. From this standpoint, fuel flow
variations in reformers operating with high non-dimensional flows (i.e. small reformers)
should exhibit greater linearity in power output during load changes. The short reformer,
the change of non-dimensional flow from 22.19% to 26.63% exhibited a very mild CO
drop disruption.
In Figure 5-13, the CO concentrations associated with a similar change in reformate
hydrogen power output, namely from 40 kW to 50 kW (lower heating value based), is
depicted. For this case, the short reformer produced a lower steady-state and transient CO
concentration change than the larger reformers. This occurs because the catalyst
73
effectiveness of the small reformer is much higher than for the larger reformers, which
leads to lower average catalyst bed temperatures.
Infinite Reformer Transient CO Concentration
0.0170
0.0175
0.0180
0.0185
0.0190
0.0195
0 20 40 60 80
Run Time (s)
CO
(wet
frac
tion)
100
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW50 to 60kW 10 to 60kW
ND Flow Key:10kW: 1.10%20kW: 2.20%30kW: 3.31%40kW: 4.42%50kW: 6.63%
Figure 5-7. Infinite reformer transient CO concentrations for various for changes in
power output
Infinite Reformer CO Spikes
-500
0
500
1000
1500
2000
0 20 40 60 80 100 120 140
Time (s)
CO
Con
cetr
atio
n (p
pm)
50 to 60kW 40 to 50kW 30 to 40kW 20 to 30kW10 to 20kW 10 to 60kW
ND Flow Key:10kW: 1.10%20kW: 2.21%30kW: 3.31%40kW: 4.42%50kW: 5.52%60kW: 6.63%
Figure 5-8. Infinite reformer transient off-steady-state CO concentrations for various
changes in reformer power output
74
Medium Reformer Reformate CO Concentration
0.0165
0.0170
0.0175
0.0180
0.0185
0.0190
0.0195
0.0200
0 20 40 60 80 100 120 140
Time (s)
CO
Con
cent
ratio
n (w
et fr
actio
n)
10 to 20kW 20 to 30kW 30 to 40kW40 to 50kW 50 to 60kW 10 to 60kW
ND Flow Key:10kW: 2.22%20kW: 4.43%30kW: 6.65%40kW: 8.87%50kW: 11.08%60kW: 13.30%
Figure 5-9. Medium reformer transient CO concentrations for various changes in power
output
Medium Reformer CO Spikes
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140
Time (s)
CO
Con
cent
ratio
n (p
pm)
10 to 20kW 20 to 30kW 30 to 40kW40 to 50kW 50 to 60kW 10 to 60kW
ND Flow Key:10kW: 2.22%20kW: 4.43%30kW: 6.65%40kW: 8.87%50kW: 11.08%60kW: 13.30%
Figure 5-10. Medium reformer off-steady-state CO concentrations for various changes in
reformer power output
75
Short Reformer Transient CO Concentration
0.015
0.0155
0.016
0.0165
0.017
0.0175
0.018
0.0185
0 20 40 60 80 100 120 140Time (s)
CO
Con
cent
ratio
n (w
et fr
actio
n)
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW 50 to 60kW
ND Flow Key:10kW: 4.94%20kW: 8.88%30kW: 13.31%40kW: 17.75%50kW: 22.19%60kW: 26.63%
Figure 5-11. Short reformer transient CO concentrations for various changes in power
output
Short Reformer CO Spikes
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140Time (s)
CO
Con
cent
ratio
n (p
pm)
10 to 20kW 20 to 30kW 30 to 40kW 40 to 50kW 10 to 60kW
ND Flow Key:10kW: 4.94%20kW: 8.88%30kW: 13.31%40kW: 17.75%50kW: 22.19%60kW: 26.63%
Figure 5-12. Short reformer off-steady-state CO concentration for various changes in
reformer power output
76
Comparison of CO Concentrations for Different Size ReformersOperated Between 40 to 50kW Steady State Power Outputs
0.0155
0.016
0.0165
0.017
0.0175
0.018
0 20 40 60 80 100 120 140
Run Time (s)
CO
Con
cent
ratio
n (p
pm)
Medium CO Short CO Infinite CO
ND Flow ranges:Short Reformer: 17.75% to 22.19%Medium Reformer: 8.87% to 11.08%Infinite Reformer: 1.10% to 6.63%
Figure 5-13. Transient CO comparison of various size reformers operating between 40 and 50 kW hydrogen power output
Hydrogen Concentration
Transient and steady-state changes in hydrogen concentration for all reformers
were such that the performance of PEMFCs or PAFCs should not be drastically affected.
Even under the harshest transient conditions studied, in which a change in fuel flow was
induced to generate a steady-state hydrogen yield between 10 kW and 60 kW, the
reformers hydrogen yields did not deviate much more than 5% (Figure 5-14). The lowest
hydrogen concentration was slightly below 60% wet molar concentration, and
corresponded to the small reformer producing 60 kW hydrogen yield.
77
0.59
0.60
0.61
0.62
0.63
0.64
0.65
0.66
0 50 100 150 200 250
Run Time (s)
H2 C
once
ntra
tion
Infinite (10kW to 60kW) Medium (10kW to 60kW) Short (10kW to 60kW)
ND Flow Changes:Infinite: 1.10 to 6.63Medium: 2.22 to 13.30Short: 4.44 to 26.63
Figure 5-14. Comparison of transient changes in H2 concentration induced by step
changes in fuel flow corresponding to hydrogen yields from 10 to 60 kW (lower heating value based) for various size reformers
CHAPTER 6 CONCLUSIONS
Based on the experimental and modeling results presented in this study the
following conclusions may be expressed.
Steam Reformer Modeling
• A method of modeling a methanol steam reformer was proposed, demonstrated and compared to actual reformer performance
• The reformer model results matched general reformer behavior observed in actual reformers
• Based on this model formulation a new set of reformer similarity variables were proposed and the use of space velocity and aspect ratio as reformer design variables was demonstrated to be insufficient
Steady-state Reformer Operation
• Non-dimensional flow, catalyst effectiveness, and non-dimensional conduction were introduced as potential reformer similarity variables. These variables effectively characterized the steady-state reformer performance of reformers.
• Based on these variables, the results showed that the steady-state CO concentration decreases with increased non-dimensional flows
• The steady-state H2 concentration decreased with increased non-dimensional flows
• Higher non-dimensional flows resulted in decreased steady-state reformer conversion
Unsteady Reformer Operation
• Transient changes in fuel flow into steam reformers produced non-linear variations in hydrogen and CO concentration in the reformer outlet
• These variations are mostly caused by transient changes in reformer catalyst bed temperature
78
79
• Step increases in non-dimensional fuel flow produced a transient increase in CO concentration followed by an eventual drop in the CO concentration
• This transient increase in CO concentration was greater when large changes in non-dimensional flow occurred
• Step increases between large non-dimensional flows produced lower transient increases in CO concentration than the same step changes between lower non-dimensional flows.
The implications of the results and methodology presented in this study are that
steam reformer chemical behavior, in the transient and steady-state case, has been
expressed in mathematical, non-dimensional, terms. This leads to the proposal of
similitude expressions that can be used to better characterize, compare, understand and
design packed bed steam reformers. Also, this study demonstrates the mechanisms that
produce carbon monoxide spikes during period of flow changes.
Generally, from a design standpoint, there seems to exist a balance between the
design of an infinitely long reformer that would have excellent efficiency (conversion)
but would also have high outlet CO concentrations in the steady state and transient
regime, and a short and “stubby” reformer with low efficiency but low transient and stead
sate CO concentrations for the same fuel flow rate. The optimum point will depend on the
fuel cell and its tolerance of CO. Design should be made such that during the highest
changes in non-dimensional flow, the CO spike does not exceed a maximum
concentration that would drastically reduce fuel cell performance through poisoning.
CHAPTER 7 SUGGESTED FUTURE WORK
The analysis provided in this study is largely based on experimental results
obtained from a single diameter reformer (UC Davis reformer). The numerical models
developed generally matched the performance of this reformer. A greater body of
experimental data, with reformers of varying lengths and diameters should be obtained to
determine the practical limitations of the analysis presented here.
In addition, a set of non-dimensional performance variables has been introduced to
the field of reformer design and analysis. These variables worked extremely well at
describing reformer performance based on the models developed. A study should be
conducted to evaluate whether these variables (or a variation of these variables) are
capable of determining similarity between distinct reformers.
Expansion of this study into reformer controls design, fuel cell controls design, and
overall fuel cell system controls design is a logical expansion of this body of work.
Understanding the transient nature of fuel cell systems is critical to their effective control.
It is hoped that this work forms the foundation for the development of controllers that are
capable of producing fast transient load changes in future fuel cell systems with minimal
efficiency penalties.
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APPENDIX A COPY OF FEMLAB SOLUTION REPORT
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84
85
86
87
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89
90
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92
93
94
95
96
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APPENDIX B PRELIMINARY LOAD FORECASTING STUDY
The lose of efficiency due to the sluggish response of the fuel cell system when
operating in a transient load environment may be mitigated by the capability to preempt
the onset of large changes in load. For a vehicle this may be achieved by “learning” the
driving style of the vehicle driver such that periods of increased acceleration may be
anticipated. Figure B-1 shows a typical load profile for a drive cycle. This load profile
was obtained by driving TBB-2 in actual traffic conditions.
Transient Load Profile for TBB-2 under the UFFL driving cycle-10
0
10
20
30
40
50
0 100 200 300 400 500 600 700
Run Time (s)
Pow
er (k
W)
Figure B-1. Transient load profile for TBB-2 under the University of Florida Fuel Cell
Lab driving cycle data obtained on 4-2-2004.
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100
In order to test this hypothesis TBB-2 was driven under a standard route (UFFL
cycle) and the transient load, L(t), was obtained. Given this load a power change index,
PCI(t), was defined (Equation B-1).
)()()()(
ottLtLtLtPCI
−+= (B-1)
In Equation B-1, to is the sample interval in time. Thus L(t-to) represents the
previous load data. For the data obtained from TBB-2, to equaled 1 second. Notice that
PCI is equal to 0.5 if there is no load change and that its value is bound between 1 and -1.
PCI for TBB-2 under UFFL driving cycle-1
-0.75
-0.5
-0.25
0
0.25
0.5
0.75
1
0 100 200 300 400 500 600 700
Run Time (s)
PCI
Figure B-2. Power Change Index (PCI) for TBB-2 under UFFL driving cycle data
obtained on 4-2-2004.
By looking at Figure B-2 it is evident that most of the time PCI oscillates slightly
from 0.5, meaning that relatively small variations in load are occurring. Furthermore it is
shown that large fluctuations in the value of PCI occur in a recognizable pattern. That is,
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every large decrease in the value of PCI (from breaking or stopping), there is almost
always a consequent large increase in the PCI value.
f(net)
f(net)
f(net)
f(net)
Hidden LayerInput Layer
f(net)
f(net)
f(net)
f(net)
Output Layer
x (t-20)x (t-19)x (t-18)x (t-17)
x (t-0)
y1
y2
y3
yN
f(net)
f(net)
f(net)
f(net)
Hidden LayerInput Layer
f(net)
f(net)
f(net)
f(net)
Output Layer
x (t-20)x (t-19)x (t-18)x (t-17)
x (t-0)
y1
y2
y3
yN
Figure B-3. Multi-layer Perceptron.
Out of ten runs PCI data from one of the runs was used to train a multilayer
perceptron (MLP) whose input were 20 PCI data points. The MLP used had 10 output
processing elements, whose output should approximate PCI(t+to), PCI(t+2to),
PCI(t+3to), …, PCI(t+10to). Figure B-3 shows a diagram of the MLP used. The output of
each processing element (PE) is the hyperbolic tangent of the sum of the multiplication of
the inputs to a gain or weight (Equation B-2). See Figure B-3.
⎟⎠
⎞⎜⎝
⎛= ∑
ijiij wxPE ,tanh (B-2)
Therefore, the output of an output layer processing element can be written as
shown below, where k is the output index, i is the input data index, and j is the hidden
processing element index (Equation B-3).
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⎟⎟⎠
⎞⎜⎜⎝
⎛⎟⎠
⎞⎜⎝
⎛= ∑ ∑ kj
k ijiikoutput wwxPE ,,, tanhtanh (B-3)
Training of the MLP was done using the error back propagation algorithm. An
error was defined as the difference between the MLP output and the desired MLP output
(Equation B-4). For the purposes of these experiments, the desired output was the future
data, x(t+kto) that the kth output of the P.E.should approximate.
koutputoik PEkttxE ,, )( −+= (B-4)
From this error definition a mean squared error (J) can also be defined (Equation B-
5).
∑∑= =
=N
i
M
kikE
NJ
1 1
2,2
1 (B-5)
In Equation B-5 N represents the number of data points introduced into the MLP
(for our purposes N=20). M represents the number of output processing elements in the
MLP (in our case 10). The mean squared error is used as a cost function whose minimum
is found with respect to the weights using a gradient descent algorithm. The algorithm
chosen was the error back propagation algorithm.
The trained MLP was tested with new data obtained by driving TBB-2 under the
same UFFL route but on a different day and under different traffic conditions. Figure B-4
shows the performance of the MLP as a load predictor. Generally, the trained MLP was
able to predict large increases in load.
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MLP Performance Test-1
-0.75
-0.5
-0.25
0
0.25
0.5
0.75
1
0 100 200 300 400 500 600
Run Time
PCI
Actual Run Prediction (t+10s)
Figure B-4. The MLP performance as a 10 second PCI predictor.
APPENDIX C PHYSICAL DESCRIPTION OF THE UC-DAVIS REFORMER
The following is a physical description of the UC-Davis reformer test rig. Part of
the information presented in this Appendix was provided and prepared by UC-Davis
students and Dr. Paul Erickson, director of the UC-Davis Hydrogen Production and
Utilization Laboratory (HYPAUL).
The UC-Davis methanol-steam reformer used for the experimental portion of this
study can be divided into subassemblies as shown in Table C-1. Figure C1 shows a
general process diagram of the UC-Davis reformer.
Table C-1. UC-Davis reformer subassemblies Methanol Steam Reformer Elements Subassembly Premix Reservoir, Pump, Scale Pumping 3-Stage Vaporizer, Super-heater Vaporizer Steam Reforming Reactor Catalyst Bed Housing Condenser, Condensate Trap Condensing Unit
General Description
A premixed concentration of methanol in water is mounted on a scale. This
premixed fuel is pumped through three stage vaporizers which ensure only vapors are
introduced into the reformer tube at the user specified temperature. In order to ensure this
a superheater is also inline. The superheater ultimately controls the fuel temperature
before introduction into the reformer catalyst bed.
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105
Figure C-1. General process diagram of the UC-Davis reformer
After passing through the catalyst bed, the gaseous species were directed into two
tubes via a system of valves. One route was for analysis and the other was for exhausting
the reaction products, reformate. Both routes lead to the condensing unit where the
reformate temperature is reduced in order to separate liquid water and unreacted
methanol from the gas mixture. A condensate trap is used for this purpose. The generally
dry reformate gas is then routed to the gas analyzer.
The system also includes the capability to drain the catalyst bed through a series of
drain valves and allow for carbon monoxide purging and preservation of the catalyst bed.
An air purge was adapted after the catalyst section to ensure retrieval of all condensed
species in the condensate trap.
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Pumping Subassembly
The pumping subassembly (Figure C-2) is initially composed of a 4 liter (1 gal.)
polyethylene carboy reservoir containing a user prepared molar concentration of
methanol in water. For the experiments conducted a methanol concentration of 1.5 moles
of water per mole of methanol was used. The tank was allowed to rest at room
temperature. Appropriate premix concentration was verified through the use of hand-held
specific gravity sensor (Anton Parr - model 35n with a resolution of 0.0001 g/cm3).
The premix reservoir rested upon a 4100 gram-Ohaus scale with a 0.1 gram
resolution. The scale had a 9 pin bidirectional RS-232 port, which allowed the user to
electronically record the scale reading during operation. The premix was then drawn out
of the reservoir by way of a gear pump through a 0.635 cm (0.25 in) I.D. vinyl tube. The
gear pump head (model EW-07002-25) and driver (model A-75211-30) was
manufactured by MicroPump and enabled the user a resolution of 0.1 ml/min with a
premix flow rate range from 2.6 to 85 ml/min. The pump driver was equipped with a
frequency output signal, which allowed the user to correspond a frequency (or gear pump
RPM) to a flow rate. The user can then electronically record the instantaneous flow rate
and control the pump with a voltage signal during operation. Calculations for the mass
flow rate could be verified by both the recorded pump flow rate and by recording the
change in mass of the scale divided by the time the experiment ran (both were recorded
via the computer control program).
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Figure C-2. Premix reservoir and gear pump
Figure C-3. Vaporizer design
The vaporizer subassembly, composed of a 3-stage vaporizer and a superheater, is
shown in Figure C-3 and Figure C-4, respectively. The premix exited the gear pump
through a 0.635 cm (0.25 in) O.D. stainless-steel tube (0.124 cm (0.049in) wall thickness)
and then entered the first vaporizer of the 3-stage vaporizer. All 3 vaporizers were built
with identical dimensions. Each vaporizer was made of a 20.3 cm (8 in) stainless-steel
pipe (nominal ½” Dia., schedule 40) threaded at both ends. Caps for the pipes were
machined to adapt a 0.635 cm (0.25 in) tube on the top end and a 0.635 cm (0.25 in)
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cartridge heater on the bottom end. The energy for vaporization was supplied from 120V
cartridge heaters. The first vaporizer contained a 24.1 cm (9.5 in), 525W cartridge heater,
while the last two stages contained 12.7 cm (5 in), 400W cartridge heaters. Each
vaporizer was monitored for temperature by two, stainless-steel-sheathed, ungrounded K-
type thermocouples. The temperatures of the cartridge heaters were monitored by a 0.025
cm (0.010 in) diameter-thermocouples. These thermocouples were located external to the
flow, attached to the base of the cartridge heater (Figure C-3). The exit temperature of
each vaporizer was monitored by a 0.159 cm (0.0625 in) thermocouple. These
thermocouples were located internal to the flow, at the joint union between each stage
(Figure C-3). At the exit of the second vaporizer a 0-103.4 kPa (0-15psi) pressure gauge
(identified as PT in Figure C-3) was installed to monitor the pressure near the beginning
stage of the reformer. Several stainless-steel, high temperature quarter-turn valves were
installed throughout the vaporizer subassembly. At the inlet to the first vaporizer, a valve
was adapted to drain the condensate in the subassembly when necessary and at the exit of
the first vaporizer a valve permitted an inlet for catalyst reduction gas. When the
vaporized premix was not up to temperature, an exhaust valve at the exit of the 3-stage
vaporizer prevented the flow from entering the superheater and catalyst bed housing, as
shown in Figure C-4. A CO2 purge and check-valve were located at this position as well,
to purge vaporized premix out of the reactor and lock oxygen out when not in operation.
The superheater housing material was a 30.5 cm (12 in) stainless-steel pipe
(nominal ¾” Dia., schedule 40) threaded at both ends. Caps for the pipes were machined
to adapt to 0.635 cm (0.25 in) tubes and could be removed. To prevent condensation
build-up on the bottom of the superheater, which would funnel the liquid premix directly
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into the reactor (thus damaging the catalyst); a recessed tube was inserted approximately
7.6 cm (3 in) inside the superheater. All pipes were sealed on the vaporizer subassembly
by either welding or a sealant (Resbond 907GF), which was capable of withstanding
temperatures up to 1288oC (2350oF). All tubes were sealed using Swagelok compression
fittings. External heating was applied to the superheater using four nozzle band heaters
(2.5cm (1in) I.D., 5.1 cm (2in) width), each with a 120V, 275W rating. To evenly
increase the temperature distribution throughout the superheater, a highly thermal
conductive aluminum tape was wrapped around the exterior. Three 0.159 cm (0.0625 in),
stainless-steel-sheathed, ungrounded K-type thermocouples were strategically adapted to
the superheater to monitor performance. Two thermocouples were integrated inside the
superheater to monitor superheater internal and exit (just before the reactor) temperature.
A third was placed externally on a nozzle band heater, permitting the user to monitor the
temperature of the heat source. Insulation for both the 3-stage vaporizer and superheater
composed of an alumina-silica material capable of withstanding temperatures up
to1260oC (2300oF). Because the superheater utilized external heating, it required extra
insulation composed of inorganic-volcanic rock fiber capable of withstanding
temperatures up to 649oC (1200oF).
Catalyst Bed Housing Subassemblies
The housing material for the reactor was a 61 cm (24 in) stainless-steel pipe
(nominal ¾ in Dia., schedule 40) threaded at both ends, as shown in Figure C5. The
upper cap was machined to adapt a 0.635 cm (0.25 in) tube, as well as a 0.635 cm (0.25
in) MNPT pipe on the side. The MNPT pipe created a pathway to a Kistler pressure
transducer. The cap at the exit of the reactor was a specially machined reducing “T”
fitting. One end of the “T” attaches to a 0.635 cm (0.25 in) tube, while the other attaches
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to the 1.9 cm (0.75in) pipe. External heating was applied to reactor A using eight nozzle
band heaters (2.5cm (1in) I.D., 5.1cm (2in) width), each with a 120V, 275W rating. In a
similar fashion as the superheater, a highly thermal conductive aluminum tape was
wrapped around the exterior of the pipe to evenly increase the temperature distribution
throughout the reactor. An array of seventeen 0.159cm (0.0625in) Dia. stainless-steel-
sheathed, ungrounded K-type thermocouples was used to monitor the temperature within
the reactor. The thermocouples were attached to the reactor housing using 0.32cm
(0.125in) MNPT to 0.32cm (0.125in) pipe fittings by Swagelok. All fittings were sealed
using a chemical resistant-Teflon tape or by welding.
To observe the temperature of the heat bands, eight 0.025 cm (0.010 in) Dia.,
ungrounded K-type thermocouples were placed between the heat bands and the exterior
reactor wall. The reactor pressure was monitored using a 0-103.4kPa (0-15psi) pressure
gauge and was located at the exit of the reactor (Figure C5). Insulation for the reactor was
composed of a 3” thick calcium silicate material with a temperature tolerance of 649oC
(1200oF).
In both reactors, a stainless-steel mesh (256 squares per inch, 0.015in wire
diameter) was placed at the bottom of the reactor to provide a base for the palletized
catalyst. The catalyst used in this study was a pelletized commercial-grade copper-zinc
catalyst on an alumina substrate. This catalyst (FCRM-2) was manufactured by Sud-
Chemie and is recommended for an operating temperature range of 250-280oC (482-
536oF). Stored in an oxidized state, the catalyst needed to be reduced before steam
reformation could occur. Reduction was done by flowing diluted concentrations of
hydrogen in nitrogen for a period of 10 hours. Successful reduction was accomplished
111
once temperature variations within the reactor were negligible. Information including the
mass of catalyst loaded and the length of filled catalyst bed housing was recorded. The
catalyst was cylindrical in shape and had dimensions consisting of 0.47 cm (0.187 in)-
diameter and 0.25 cm (0.100 in)-thickness, as stated by the manufacturer.
Schedule 40 SS Pipe0.824” ID, ¾” Nominal12” Length, Threaded Ends
Figure C-4. Superheater design
Condensing Unit Subassembly
The condenser housing consisted of a modified 113liter (4.0 ft3) refrigerator
manufactured by Haier. The condenser was designed with two intakes, one for reactor
exhaust and the other for analysis. To increase conduction and gas path length, the
reacted species or exhaust entered into 0.635cm (0.25 in)O.D. copper tube coiled inside
10.2cm (4in) PVC canisters (2 canisters on the analysis side).
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Figure C-5. The UC-Davis reactor design
Here, water from an ice bath doused the coils via a submersible pump; lowering the
gas temperature from 250oC (482oF) to 0oC (32oF). The decrease in temperature promotes
a phase change, causing water, methanol and other relevant species to condense.
The condensate was then “trapped” in the container. The condensate from the
exhaust side was removed from the trap via a drain located on the outside of the
condenser. To acquire the condensate from the reactant species for analysis, the container
was removed from the unit. The dry product gas on the analysis side was then routed to
the gas analyzer, while the exhaust gas was directed to the fume hood. Two 0.159cm
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(0.0625in), stainless-steel-sheathed, ungrounded K-type thermocouples monitored the
condensing unit temperatures, one inside the condenser, and one located directly in the
flow at the exit of the analysis gas side.
LIST OF REFERENCES
[1] M. Cooper, Fuel Cell Market: Light Duty Vehicles, Fuel Cells Today, London, U.K., 2003.
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[3] G. Thomas, Hydrogen Storage Overview, Sandia National Laboratory, N.M., 2003. (http://www.eere.energy.gov/hydrogenandfuelcells/pdfs/bulk_hydrogen_stor_pres_sandia.pdf)
[4] F. Barbir, Clean Energy Research Institute, University of Miami, Coral Gables, FL.
[5] T. Springer, T. Rockward, T. Zawodzinski, S. Gottesfeld, J. Elect. Soc., 148(1) (2001) A11-A23.
[6] Office of Fossil Energy, Today’s Hydrogen Production Industry – Aug. 1st 2005, U.S. DOE, 2005. (http://www.fe.doe.gov/programs/fuels/hydrogen/currenttechnology.html)
[7] V.P. Roan, D.A. Betts, K. Dinh, A. Twining, T. Simons, U.F., An Investigation of the Feasibility of Coal-Based Methanol for Application in Transportation Fuel Cell Systems, Advanced Vehicle Development Program, Georgetown University, Washington, D.C., 2004.
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[14] Horng, R., Ener. Conv. Manag., 46 (2005) 1193-1207.
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BIOGRAPHICAL SKETCH
Daniel Augusto Betts Carrington is the son of Dr. Claudio Daniel Betts and
Carmen Alicia Carrington Betts. He was born in Panama on August 7, 1975. Daniel
graduated with a B.S. in mechanical engineering from the George Washington University
in 1997, and obtained his masters degree in mechanical engineering (thermal sciences
concentration) from the University of Florida in 2000. Daniel is married to Erica Eva
Carr-Betts, and they have a beautiful and intelligent daughter, Matilda Eva Carr-Betts,
who was born on September 28, 2004.
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