Platinum Supply and the Growth of Fuel Cell
Vehicles
Justin Boudreau, Eugene Choi, Ravindra Datta, Oljora Rezhdo, Khalid Saeed
Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609-2280, USA
Abstract
This report addresses problems associated with U.S. fuel cell vehicle production and a limited platinum
supply. Polymer Electrolyte Membrane (PEM) fuel cells, which use a platinum catalyst, could place strain
on the platinum market if fuel cell vehides are widely produced. We developed a dynamic hypothesis,
identified causal relationships, and created a system dynamics model in iThink. Based on this model, we
found platinum prices would likely reach $50,000 per kilogram in 30 years and the cost of platinum for a
fuel cell vehide would be $2,500. At this price, the platinum barrieris surmountable if the cost of other
FCV components is drastically reduced. If a world FCV market takes hold, it was concluded that only
about 15% global market penetration is feasible.
1: Introduction and Background
1.1: Introduction
Oil plays a pivotal role in today’s world, accounting for around 36% of worldwide energy use [1].
Unfortunately, many nations have already reached peak oil production and are now producing less and
less oil per year. The United States is an excellent example; in 1970, the U.S. oil production peaked at
just below ten million barrels per day [2]. Ever since, U.S. oil production has been decreasing; in 2007, oil
production was just five million barrels per day. While the U.S. is still a significant oil producer, it is also
the largest oil consuming nation on Earth. The United States consumed an astonishing 23.9% of the
world’s supplied oil in 2007; for comparison, China, the second most oil consuming nation, only had
9.3% [3]. While oil production and consumption is a worldwide issue, it is of particular importance to the
United States. Consuming nearly a quarter of the world’s oil and faced with depleting oil production,
energy has become one of the most important problems facing the nation.
In addition to concerns over depleting oil production, there are environmental issues to consider. One of
the largest concerns is the effect of greenhouse gasses on global warming. In the 2006 U.S. Climate
Action Report, it was reported that U.S. CO, emissions for 2004 was 7,074.4 Tg (707 million metric tons).
This was a 15.8% increase from 1990. The report attributed the rise in emissions to increases in
electricity demand, expanding industrial production, and increased travel [4]. With more vehicles on the
road emitting carbon dioxide, it is becoming more important to consider the environmental impacts of
conventional internal combustion engines.
One plan to reduce oil dependency and carbon emissions is to replace internal combustion engine
vehicles with fuel cell vehicles (FCVs). These vehicles are more efficient (30% wells-to-wheel efficiency
compared to a 15% wells-to-wheel efficiency for internal combustion engine vehides [5]). Polymer
Exchange Membrane (PEM) fuel cells are currently regarded as one of the most viable types of fuel cells
for automotive use due to their low operating temperature (only around 80°C [6]). The automotive
industry has already begun producing FCVs on a small scale for testing purposes and to raise public
awareness. Some manufacturers have gone further; in the summer of 2008, Honda began tolease a
small number of FCVs to the public in California. In addition to automotive developments, the
infrastructure necessary to support FCV fleets is being established in Norway with the HyNor project and
in California with the Califomia Hydrogen Highway Network (CaH,Net).
While these projects have provided useful information on the small scale development of fuel cell
vehicles, many concerns still exist, especially when considering large scale market penetration of FCVs.
Some of these concerns are currently being addressed; for example, the storage of hydrogen is
improving with stronger tanks capable of storing hydrogen at 10,000 psi [6], the public is becoming
increasingly aware of fuel cell technology and the benefits it offers, and infrastructure is being
developed in selected areas. However, some concems still need further investigation.
In particular, a limited platinum supply needs to be taken into account when considering the
development of fuel cell vehicles. Currently, fuel cells have a platinum loading of about 0.5 to 0.6
mg/cm? wea (on an experimental level, loadings have been as low as 0.25 mg/ cm’ wea) and a power
density around 0.9 W/cm’ mea [7]. This translates to 0.6 to 0.67 mg/W; from this result, a 100 kW FCV
would require 60 to 67 grams of platinum. In November of 2008, the average price of platinum was
$844.21 per troy ounce ($24.31 per gram) [8]. For a 100 kW vehide, the cost of the platinum catalyst
alone would be $1,600. Other components of the fuel cell, such as the Nafion membrane, will drive the
cost even further. To put this in perspective, a complete internal combustion engine costs about $2,500
to $3,500 [9]. The cost of platinum alone is approximately half the cost of a fully functional internal
combustion engine. While the costs for fuel cells may go down due to technological advances that result
in a smaller platinum loading, the price of platinum may increase as FCVs are introduced. In addition to
price, there are other concerns such as limited platinum reserves. Platinum, being one of the rarest
metals on Earth, is difficult to mine. For every 7 to 12 tons of ore mined, only about one ounce of
platinum is produced [10]. Due toits extreme rarity, there is the possibility that the amount of mineable
platinum could dramatically decrease in the future.
1.2: Background
Past studies on the interrelation between the platinum and FCV market have been incondusive. Some
studies, such as those by TIAX LLC and R.J. Spiegel have concluded that it is feasible for an FCV market to
develop. However, a study by Robert H. Borgwardt suggested that it platinum was a limitation on FCV
market growth.
TIAX, a technology processing company, has done extensive research on the prediction of FCV growth
with the U.S. Department of Energy. With scenarios based on different levels of FCV market penetration,
TIAX conduded that when 50% of new vehide sales are occupied by FCVs, the increase in FCV demand
can be supported by the world platinum supply [11]. Industrial experts and the Department of Energy
(DOE) suggest that the rate of increase in platinum demand on the order of 12Mg/year is feasible [11].
The increase in demand has been about 6Mg/year for past years since 1988 [12], and with the scenario
of 50% market penetration by year of 2050, the sharpest increase will occur in 2030, lasting for about 15
years with a demand growth rate of 12Mg/year [11]. The model predicts that eventually the demand
will remain at about 700Mg/year with no increase in the rate of demand growth.
However, supply isn’t the only consideration; the change in the price of platinum due toincreased
demand needs to be considered. One study suggests that the highest increase in price for platinum will
not exceed 12.5% [13]. The model assumes a 95% rate of recycling, a platinum loading of 20g per
vehicle, and the eventual decrease in platinum demand with the advance of technology. While the
experimental results corroborate very high recycling rate from used fuel cells [14], the assumption of a
significant decrease in demand within two decades seems to be overly optimistic. It is known that there
is currently no viable alternative to platinum as a catalyst for fuel cells in vehicles [15]. Palladium may be
able to substitute some portion of platinum demand, but it offers little advantage in terms of cost and
availability [15].
Other studies have noted the optimistic assumptions used in past models. In fact, most analysis based
on information reflecting the current level of technology show that the supply may not be sufficient to
meet worldwide platinum demand. The alternative assumptions include: [15]
e South African supply (80% of world platinum production) can only be increased by 4% per
annum instead of 5%.
e Jewelry demand grows at more than 2% per annum — it is either assumed to remain constant or
decrease as the platinum demand by FCV increases.
e Fuel cell stacks require more than 20g Pt/vehide — this is less than half of the amount that is
currently being used.
e The demand for cars grows by more than 55% per decade, instead of 45-50%.
The high sensitivity of the results from past models is due to the absence of feedback loops within the
model. Without important feedbacks, the model can’t respond to changes within the system, resulting
in high sensitivity. With these models, results have largely been incondusive, with large variations in
results among different studies. It should be noted, however, that many models make condusions based
on relaxed constraints, despite the sensitivity of the model to those constraints. Also, most analysis does
not reflect practical market penetration, as they do not include the response of FCV production to
platinum prices. The uncertainties presented due to the relaxation of constraints suggest that the future
research should focus on assessing costs associated with increasing platinum production and platinum
market dynamics [16].
In a 2001 study from the US Environmental Protection Agency, authored by Robert H. Borgwardt [12], it
was estimated that platinum could dramatically inhibit the production of fuel cell vehides. The report
also found that it would take an estimated 66 years and a total 10,800 tons of platinum to convert the
entire US fleet to fuel cell powered vehides. This conclusion was based on the assumption that US
platinum consumption was at 48% of the worldwide supply. If US platinum consumption was at 16%
(the percentage consumed in 2001) then it was concluded that it would take 146 years for complete
conversion. In a 2004 study [17], also from the US Environmental Protection Agency, a different
conclusion was reached. Under the authorship of R.J. Spiegel, the study found that only 4% of the
world’s platinum supply is needed to meet fuel cell vehicle demand until 2035.
While these studies are informative and supply valuable data and predictions, the large variation among
studies prevents one from arriving at any solid conclusion about platinum supply and fuel cell vehicle
production. In addition, previous models often did not consider the interactions among variables which
give rise to important behavior. The system dynamics model used in this report takes these
interrelations into account, providing a more detailed picture of the possible consequences of an FCV
market.
2: Methodology and Analysis
Modeling complex problems, such as the issue of platinum limitations in an emerging FCV market,
requires a model that considers feedback effects and how these effects reverberate through the model.
System dynamics takes important feedback loops and interrelations into account, resulting in a more
realistic model.
2.1: Establishing Reference Modes: The Computational Model
Before developing the system dynamics, a computational model was developed as a reference mode.
The purpose of the computational model is to obtain a qualitative understanding of how the platinum
market will behave under the strain of FCV production.
Establishing possible scenarios concerning platinum supply limitations involves developing numerous
assumptions. These assumptions must take many factors into account, such as the predicted number of
FCVs to be produced within the next few decades, the platinum loading per vehide, and efficiency of
platinum recycling programs. The first assumption concerns the annual growth rate of the U.S. vehide
fleet. As of 2006, there were approximately 250 million vehicles on the road [18]. Data of US vehicle
sales were available from 1990 to 2007 by the U.S. Bureau of Transportation Statistics. For 2007,
approximately 8 million passenger vehicles were sold in the United States [19]. This value will provide
the market saturation point for FCVs.
The second assumption concerns the annual growth rate of platinum production. From 1985 to 2003,
the supply of platinum has increased by an average of 6,150 kg per year [20]. The USGS estimated that
the platinum supply could increase anywhere between five and fifteen thousand kilograms per year. For
the computational model, it was assumed that the platinum supply will increase by ten thousand
kilograms per year.
The third assumption is an estimate of the future market penetration of fuel cell vehicles. The estimates
that will be used for our modeling purposes will be the HyTrans model, developed by the U.S.
Department of Energy in 2005. Unlike many previous models, the HyTrans model incorporates
significant hindrances to the development of hydrogen fuel cell technology. The model takes into
account factors such as the lack of a strong market for hydrogen fuel technology, the expensive price of
fuel cells, and the need for development of economies of scale in vehicle production. The model itself is
based on a collection of more specific models. These models indude the DOE H2A Model for hydrogen
production and delivery, PSAT & ASCM Vehide Performance and Cost Estimates model, ORNL Vehicle
Choice model, ORNL Advanced Vehide Manufacturing Cost model, GREET GHG Emissions model, and
the NEMS AEO 2006 model [21]. The HyTrans model estimated FCV market penetration until 2025 under
three different scenarios. The results from the HyTrans model were qualitatively extended until market
saturation was achieved.
The final assumptions concern platinum loading for fuel cell vehides, the efficiency of platinum recovery
programs, and the average life of a fuel cell vehicle. In an article by Mark F. Mathias et al [7] , it was
reported that platinum loadings of 0.25 mg/cm’ were achieved on an experimental level. In addition to
breakthroughs in platinum loadings, power density has increased. The article cites power densities of
about 0.9 W/cm’. Using this information, it was determined that the average amount of platinum per
automobile would be about 22 g (for an 80 kW vehide). In a report by Stephen Grot and Walther Grot of
lon Power Inc. in conjunction with the US Department of Energy [22], a method of platinum recycling
was found to recover about 95% of platinum from a fuel cell. Articles published by Robert H. Borgwardt
[12] and R.J. Spiegel [17] use an average FCV lifespan of 15 years. This value far exceeds the current
lifespan of about 5 years [23] but is used in the ideal case where FCV life expectancy is increased
through technological breakthroughs. The average lifespan of a fuel cell vehicle is taken to be 15 years
for the computational model.
Using these assumptions, a rudimentary model was developed to give a better estimate of platinum
demand for FCVs in the future. The computational model suggests that platinum demand will increase
dramatically at the beginning. However, as recycling of platinum from old FCVs begins to take hold, the
demand for platinum would quickly decrease. Depending on the annual growth of the global platinum
supply, US FCV platinum demand could peak at 17 to 33% of world-wide platinum demand (see Figure
4).
—— Scenario 1
sp f XA.
40 / pee, \ —=— Scenario 2
ea \\ ——~ Scenario 3
CE as
US FCV Platinum Demand as a
Percentage of Annual World
Production (10,000 kg annual growth)
2010 2030 2050 2070
Year
Figure 1: US FCV Platinum Demand as a Percentage of Annual World Production (10,000 kg annual growth)
7
While the computational model does offer some insight on the problem at hand, there are limitations to
what can be extracted from the results. Firstly, many of the assumptions are based on ideal conditions.
For example, the FCV life that was used for the computational model (15 years) greatly exceeds the
current life expectancy of 5 years, but it was used under the assumption that the lifespan of FCVs would
increase over time. Another weakness of the computational model is that it does not take into account
feedback structures that could dramatically affect the outcome of the model. In this model, annual
world production is assumed to increase at a constant rate. In reality, world production is strongly
dependent on platinum demand. If there’s a large demand for platinum, world production could
decrease dramatically. If demand suddenly falls, so could world production. These causal links, which
have been neglected for the purpose of the computational model, are an integral part of the system
dynamics model.
2.2: Formulation of Dynamic Hypothesis
Using the reference mode and research that has already been done, it is possible to establish a dynamic
hypothesis. From the reference mode, it appeared that recycling will play an important role in the
model. If recycling is prominent enough, it could cause a “boom and bust” scenario for platinum mines.
There’s the initial mining boom due to increased consumption, but as old FCVs are recycled, secondary
platinum is introduced into the market causing a bust for the platinum mining industry. These two
competing forces form two of the model’s most important feedback loops, seen in Figure 2.
Pt Invento:
: ry.
Pt Consumption
Recycling Pt - G *
+ AR) Price of Pt The Consumption
Loop
The Recycling Loop
Pt in Decomissioned
Vehicles +
Pt Used in FCV
Production
Figure 2: The Recycling and Consumption Feedback Loops
As FCV production increases, platinum consumption will increase. The increase in consumption will
reduce the amount of platinum available on the market. The price of platinum will increase due to
limited supply. The rise in platinum prices will then cause a decrease in FCV production. This logic
comprises a balancing feedback loop (the Consumption Loop).
The Recyding Loop is a reinforcing feedback. As FCV production increases, the platinum in
decommissioned vehicles increases. However, there is a delay from newly produced FCVs to
decommissioned vehicles due to the lifespan of the FCV. The increase in platinum from decommissioned
vehicles results in an increase in platinum recycling. With more recyding, the platinum available on the
market increases. Since there is an increase in platinum supply, the price of platinum falls. The reduction
in platinum prices encourages more FCVs to be produced.
2.3: Creating the Simulation Model
The next step in developing this model is to translate the qualitative representation of the problem seen
in the Causal Loop Diagram to a quantitative representation that uses mathematical equations to
represent causal links and the transportation of ideas and materials through the system. The simulation
model structure can be seen in Figure 3.
10
Normal Recycling
FracionWasted Fraction
Recycling
Effect of Resenes
on Mining Costs
Effect of mertory
Ratio on indicated Price
Fraction Wasted
Normal Faction
eracted Pq Year
Normal Other Pt
Demand
Pt Usedin ICEV Praduction
ring Costs
Average Life
of ICEVs
Effect of
on Mining
Ptrice
Pervear
PtinolaF cvs
Be)
Effect of
Other PtObemard
PrinMiddleAged FC Vs
PtinNew FCVs
from DecomissionedICEVS
PrinICEVs
Tota VeticlePemard
PrUsedin ICEVP reduction
FCV Life Expectancy
Figure 3: The iThink Model
FCV Platinum
Loading
Scenario
inital PtPrice
Scenario2
Scenario
The first flow, “Pt Used FCV Production” is defined by FCV Production and platinum loading. FCV
Production is defined by three different scenarios which are in the form of graphical functions and itis
affected by price through a graphical function; this function is a representation of elasticity of demand
for FCVs. These three scenarios are based off past research; in particular the results from the HyTrans
model (see Table 3) are fit to a Gompertz function. These three scenarios capture different levels of FCV
market penetration (half a million, one million, and 2.5 million per year by 2025 for each scenario
respectively). FCV platinum loading is multiplied by FCV Production to give the amount of platinum used
in FCVs per year. The next three stocks and their respective flows represent the lifecyde of an FCV. It is
expanded as a third-order material delay in order to achieve a more discrete delay.
After the lifecycle of the FCV is completed, the FCV is recyded for valuable material. However, not all the
platinum can be recyded. Some of it is lost due to inefficiencies during the recycling process. This is
represented by “Fraction Wasted”. In addition to FCVs, there are also internal combustion engine
vehicles (ICEVs) to consider. ICEV production is modeled as a function of Total Vehicle Demand and FCV
Production. As established in the computational model, Total Vehicle Demand is assumed to remain at
about 8 million vehicles per year. ICEV production is this value minus the FCV production (for each FCV
produced, there is one less ICEV that would have been produced). The FCV and ICEV platinum loadings
are used to convert the number of ICEVs to an equivalent value in kilograms of platinum. Due to the
small amount of platinum in catalytic converters, the delay due to lifespan is just represented as a first-
order delay. For this model, the average lifespan for ICEVs was assumed to be 12 years [24].
Recycle is determined simply by subtracting the Fraction Wasted from 1. In addition to the recyde
entering the inventory, there is the platinum from mining and the initial value for the platinum
inventory. For 2007, approximately 200,000 kg of platinum was mined [25]; this value was used for the
initial platinum inventory. Platinum mining is a function of the reserves and price. Price effects mining
through a graphical function and models the elasticity of supply. The auxiliary “Normal Fraction
Extracted per Year” is the fraction extracted relative to the reserves. The initial value for the reserves is
based on a reportin the South African Journal of Science by R.G. Cawthorn that estimates 48,000,000 kg
of platinum exists worldwide [26]. Using the initial values for the platinum inventory and reserves, the
normal fraction extracted per year was determined to be 0.00417. In addition to the effects of price,
mining is defined as the reserves multiplied by the normal fraction. Since the reserves have no inflow
(limited by what’s in the Earth), the depleting reserves reduce the amount mined as time goes by.
Platinum is added to the inventory through recycling and mining and itis removed through
consumption. Platinum consumption is defined as the summation of platinum for FCV production, for
ICEV production, and for all other sources. It is important to note that FCV and ICEV production is for the
U.S. only while other platinum demand is global (including ICEV production other than the U.S.). Other
platinum demand is defined by a normal demand and an elastidty of demand represented by a graphical
function. The normal demand is assumed to be 190,000 kg per year. This is slightly less than the 200,000
kg produced because U.S. ICEV platinum demand is considered separately. The platinum for ICEV
production is not influenced by price directly since catalytic converters have a small platinum loading
when compared to fuel cells.
One of the most vital components of the model is price. The initial value of price is set to $35,000 per kg,
based ona 5-year historical price [27]. It’s worth noting that mining costs are also initially set at $35,000
in order to start in equilibrium. The actual mining costs are very close to this value, around $33,000 for
the Anglo Platinum mining company based in South Africa [28]. Price is influenced by indicated price,
which is simply the mining cost multiplied by a graphical function of inventory ratio. The inventory ratio
is the inventory divided by the desired inventory. The desired inventory is defined as platinum
consumption multiplied by inventory coverage. The inventory ratio acts as a goal-seeking mechanism; if
13
the desired inventory is greater than the actual inventory, prices will increase until the actual inventory
is the same as the desired inventory. If the desired inventory is less than the actual inventory, prices will
decrease until to the goal (actual equals desired) is reached. However, the inventory does not directly
influence price. The ratio influences the indicated price through a graphical function. The indicated price
minus the actual price will be the change in price. By having platinum consumption and the platinum
inventory influence price through this mechanism, oscillations in price will be smoothed out, making the
results clearer to see.
Chapter 3: Results and Discussion
3.1: Model Limitations
One of the most important simplifying assumptions of this model is that the platinum market operates
under pure competition. The inventory mechanism that is used in the model is effective at emulating
supply and demand behavior but it does have limitations. The mechanism establishes goal -seeking
behavior that results in equilibrium when platinum price equals cost (where the cost indudes a normal
profit). Under these conditions, an economic profit is never sustained. In other words, the mechanism
replicates a purely competitive market. Unfortunately, the platinum market is not likely to be purely
competitive. Only a few mining companies operatingin South Africa are responsible for the majority of
the world’s platinum production. With so few companies having such a large market share, itis likely
that a cartel could develop. Instead of a purely competitive market, the market is most likely to be
dominated by an oligopoly of platinum mining firms. Increasing platinum demand due to FCVs may
result in these companies participating in price fixing schemes to increase profits. This is one of the
larger weaknesses of the model and could be improved upon in future work.
3.2: Scenario Analysis
14
Three scenarios were established for this model; these scenarios were designed to cover a wide range of
assumptions. The values for all three scenarios are summarized in Table 1.
Table 1: Scenario Analysis
Worst Case Middle Ground Best Case
Normal Change in FCV | Scenario 3 (rapid Scenario 2 (steady Scenario 1 (slow
Population growth) growth) growth)
FCV Platinum Loading | 0.100 kg 0.050 kg 0.020 kg
FCV Life Expectancy 12 years 8 years 5 years
Fraction Wasted 0.15 0.10 0.05
It is worth noting that the “best” and “worst” case scenarios are defined as the best and worst case
scenarios for platinum prices. Forexample, the “best” case has an average FCV lifespan of only 5 years.
Looking at the bigger picture, such a short lifespan is detrimental to the development of FCVs. However,
in terms of platinum price, a short lifespan means a shorter delay in platinum recycling; this reduces the
price of platinum. While the best and worst case scenarios are not very realistic, they provide a lower
and upper bound on platinum price.
The results from the simulations show quite a large diffe rence between the worst and best case
scenarios (see Figure 4). Under the worst case scenario, prices skyrocket to $78,724 per kg in the first 30
years. Afterwards, recycling begins and the price falls. Prices start to increase again as reserves diminish
and it becomes more difficult to mine. The best case scenario has very little impact on the price. Instead
of jumping to nearly $79,000, the price gradually rises to $41,967 in the first 30 years. Then the price
rises even more gradually, starting to approach the “No FCV Production” line. The middle ground
scenario has a noticeable increase in price by the year 30. At this point, the price is $50,146. For
comparison purposes, the “No FCV” case has a platinum price of $39,433 per kilogram at year 30.
15
Legend:
SD vrprice: 1-2. 3- 4-
it
90000 4
1 30000 r 1
000 5.00 50.00 75.00 10000
Pagel Years 302PM_ Tue,).an13,2009
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Figure 4: Platinum Price at Best through Worst Cases
Line 1: No FCV Production Line 2: Worst Case Line 3: Middle Ground
Line 4: Best Case
3.3: Other Scenarios
Four other scenarios were tested using this model. The scenarios are as follows: improvements in
platinum loading as price rises, the discovery of new mineable platinum reserves, a limitation on
platinum mining, and a worldwide FCV population.
3.3.1: Improvements in Platinum Loading
This scenario operates under the assumption that as prices increase, there is more incentive to develop
technologies that can reduce the amount of platinum needed per vehide. In other words, as the price of
platinum increases, the amount of platinum needed per vehide decreases. This will decrease the
demand of platinum and decrease the price of platinum, forming a balancing loop. The scenario
parameters are seen in Table 2.
16
Table 2: Improvements in Platinum Loading
Variable Value
Normal Change in FCV Population Scenario 2
FCV Platinum Loading Initially set at 50 grams (0.05 kg)
FCV Life Expectancy 8 years
Fraction Wasted 0.10
The results of the simulation can be seen in Figure 5. Price has little effect on the platinum loading
during this period. However, as platinum prices continue to rise due to platinum reserves’ depletion, the
loading should become much smaller as new technologies are developed.
® rrerrice: 1-2-3
z T0000 ap one ence ttentnn penne nntiennnnnnnpnntnnnnnnnntitnenstnntnnntnncnnnnns
L 30000 r r r 1
000 2.00 50.00 75.00 100.00
Page 1 Years 3:15PM Tue,).an13, 2009
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Figure 5: Platinum Price when Pt Loading Decreases with Price
Legend: Line 1: No FCV Production Line 2: Constant FCV Loading (0.05 kg Pt)
Line 3: Price/Loading Relation (0.05 kg initial loading)
17
3.3.2: The Discovery of New Platinum Reserves
In this scenario, new platinum reserves are discovered. The parameters for this scenario are the same as
the previous scenario except that FCV platinum loading remains constant at 50 grams. It is assumed that
50,000 kg of platinum will be discovered per year. As can be seen from the results of Figure 6, when new
Pt discoveries are made, the price increases less dramatically.
® wrerice 1-2-3
it
N00 oa ee ee ee
1 30000
000 25.00 50.00 75.00 100.00
Pagel Years 320PM Tue,).an13,2009
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Figure 6: Effect of New Constant Yearly Reserve Discoveries on Pt Price
Legend: Line 1: No FCV Production Line 2: No Reserve Discovery
Line 3: Reserve Discovery
3.3.3: Limitations on Platinum Mining
In January of 2008, a major power crisis hit South Africa. South Africa’s state-owned power supply
company could not meet the electricity demand of the nation. As a result, many platinum mines were
operating significantly below operating capacity or even not producng for extended periods of time.
The result was a skyrocketing platinum price (see Figure 7).
18
JM Base Prices Platinum From: 01 Jan 2006
US$ Daily To: 23 Nov 2008
2400 ———
2250 N
2100
1950
1800
1650
1500
1350
3200
080 |
2006 2007 2008
Platinum Period Average $1364.04
Figure 7: Platinum Price since 2006 [27]
Since then, prices have leveled off and then dramatically dedined. However, what would happen if there
was another power crisis (or any crisis that produced similar results) ? What would happen if this crisis
were to occur during peak FCV production? This is the focus of the next simulation.
In order to simulate a drastic drop in production and then a drastic increase in production once the crisis
is resolved, two step functions were used in an auxiliary (called “Capacity Utilization”). The auxiliary is
seen in equation 1.
Capacity Utilization = 1 — [STEP(0.5,10) — STEP(0.5,12)] (1)
The auxiliary was then multiplied by the Pt Mining stream. This results in a sudden decrease to half the
normal capacity utilization for two years. At the end of the two years, capacity utilization jumps back to
normal.
The results of the model show similar results to real life. When production was drastically reduced in
January of 2008, prices soon shot up. A few months later, in July, the price began to fall as platinum
19
mines began to utilize more of their capacity. The resulting flux of platinum on the market reduced
prices. The model shows a similar spike in prices. After this initial jump, the price oscillates until it
eventually follows the case where there was no crisis. In the long run, such an event would not have a
significant impact on price, however, in the short run, there are dramatic price fluctuations. The results
from the model can be seen in Figure 8.
Figure 8: Pt Price as a Consequence of a Platinum Crisis
Legend: Line 1: No FCV Production Line 2: No Limits on Production
Line 3: Two Year Crisis Resulting in Half the Normal Production
20
3.3.4: Worldwide FCV Population
The previous scenarios operated under the assumption that only the United States would adopt Fuel
Cell technology, which based on population constitutes only 4.6% of the entire world population. In
reality, it is likely that other nations will use fuel cell technology. To consider worldwide demand of
FCVs, slight alterations to the model were made. The total vehide demand was changed from 8 million
vehicles per year to 53 million vehicles per year [29].
With the model adjusted for a worldwide scenario, five different runs were considered. It was noticed
that the platinum price would increase dramatically the first 25 years and then it would level off as soon
as the recyding feedback begins to gain strength. These results are shown in Figure 9.
Ss PtPrice: 1- 2- 3- 4- 5-
1 100000 ~~
1 30000 r 1
000 25.00 50.00 75.0 10000
Pagel Years 336PM Tue,).an13,2009
aaF ? Untited
Figure 9: Pt Price based on different percentages of worldwide technology adoption
Legend: Line 1. 100% worldwide adoption. Line 2. 75% worldwide adoption.
Line 3. 50% worldwide adoption. Line 4. 25% worldwide adoption.
Line 5. 15% worldwide adoption.
21
Chapter 4: Conclusions and Recommendations
Six different scenarios were tested using the model. These scenarios varied from generic “best” and
“worst” case scenarios to specific circumstances and events that may have an effect on platinum and
FCV market. It is important to note that the worst and best case scenarios do not reflect realistic
outcomes; instead, they determine the maximum and minimum price range that can be expected.
Depending on the conditions, it may or may not be feasible to develop fuel cell vehides in the United
States.
4.1: Worst Case
In the worst case scenario, there is a large platinum loading (100 grams) and an inefficient recycling
process (85% efficent). In addition, the lifespan of FCVs is assumed to be just as long as ICEVs (12 years).
This creates a longer delay before recyding begins to flood the platinum market. As a result, prices stay
higher for a longer period of time. Finally, it is assumed that the growth of the FCV market is quite rapid.
Under these extreme conditions, the price of platinum rises quite dramatically to nearly $79,000 per kg
by the year 30 (2038). The price then falls due to recycling. However, by 2060, prices begin to rise again
due to ashrinking reserve. Platinum reserves decrease from 48 million kg to around 17.2 million kg over
the course of 100 years. In addition, the price of platinum reached $85,000 per kg by the year 100.
By 2038 (30 years), with the price of $78,724 per kg of platinum and a loading of 100 grams, the cost of
platinum for a fuel cell vehide would be $7,872. This is around three times the cost of a complete
internal combustion engine. The costs due to platinum alone would inhibit the development of fuel cell
vehicles. The decrease in reserves is also concerning. Within 100 years, the platinum reserves would be
depleted by 64% from 2008. However, most of the depletion would be caused by other sources of
demand since FCV recyding would largely be self-sustaining. The worst case scenario is infeasible; the
cost of platinum is too high and there is a large decrease in platinum reserves.
22
4.2: Middle Ground
In the middle ground scenario, there is a platinum loading of 50 grams per vehicle, a more realistic
lifespan of 8 years, a 90% efficent recyding process, and steady market growth. Compared to the worst
case scenario, the price of platinum is only about $50,146 by 2038 instead of $78,724. At this price and
at a loading of 50 grams per car, the cost of platinum per vehicle would be $2,507. This cost is
comparable to a complete internal combustion engine. While it is still expensive, it is much more
feasible than the worst case scenario. If the other components of the fuel cell, particularly the Nafion
membrane, decrease in price due toincreased production efficiency, then it could be possible to
overcome the platinum price barrier. The reserves also depleted less quickly than the worst case
scenario. Instead of decreasing to 17.2 million kg, the reserves decreased to 24 million kg. However, in
100 years, the price of platinumis quite high, near $65,000 per kg. By then, however, new technology
could dramatically change the nature of FCVs or there could be a completely different alternative to
FCVs. Overall, the middle ground scenario is feasible only if the other components of an FCV have
dramatic reductions in price.
4.3: Best Case
For the best case scenario, the platinum loading is only 20 grams per vehicle, recycling is efficient at
95%, the lifespan of FCVsis short, resulting in a smaller delay before recycling takes effect, and FCVs are
slowly introduced to the market. With these parameters, the price of platinum only reaches about
$42,000 by 2038. Using the 20 gram loading, the cost of platinum per FCV is only $840. While still a
significant component of the cost, it probably won’t inhibit the development of FCVs, espedally when
considering likely price reductions in Nafion. The platinum reserves decreases to 28 million kg within 100
years; this difference is not as significant as the difference between the worst case and middle ground,
but it is still worth mentioning. In 100 years, the price of platinum would be about $54,500. At a 20 gram
23
loading, the price per vehide is still reasonable at $1090. The best case scenario is feasible at these
conditions.
4.4: Other Scenarios
In addition to the best through worst case scenarios, a few other scenarios were investigated. These
scenarios include improvements in platinum loading with price, the discovery of new platinum reserves,
and a supply crisis where platinum mines only produce half normal output due to a disaster.
Improvements in platinum loading with price are based on the notion that the higher the price of
platinum, the more incentive there is to develop technology that reduces the platinum required. This
scenario is largely dependent on defining factors such as the elasticity of technological breakthroughs
and imposing technological limits: after a certain point, it becomes impossible to make improvements
due to physical constraints. For this model, a graphical function was defined so that when the price of
platinum is twice its initial cost, the platinum loading will be reduced by almost half. The effect of this
scenario is noticeable but not very dramatic.
The discovery of new platinum reserves has a large impact on the model. In particular, the discovery of
new reserves would significantly reduce the depletion of the reserves. Assuming a constant discovery of
50,000 kg per year, the reserves would only be reduced to 28.6 million kilograms after 100 years. This is
comparable to the “best case” scenario, where the reserves were depleted to 28 million. The platinum
price by 2038 would be $49,000 which is alittle less than the middle ground scenario. A steady
discovery of new reserves would result in a more sustainable scenario.
The third scenario is the platinum crisis; a situation where platinum mining is reduced due to a natural
or man-made disaster. In an event similar to the power crisis in South Africa, the price of platinum
would experience dramatic fluctuations in price over the course of the crisis and even a few years
beyond the crisis. However, in the long-run, prices returned to the control case where there was no
24
disaster. Therefore, such a crisis would probably have little effect on FCV market, especially in the long
run.
The fourth scenario, worldwide production was used to see how the market would respond to global
FCV adoption. With 100% global adoption, the price of platinum reached $93,500 per kilogram within 30
years. It wasn’t until a market penetration of 15% was modeled that the scenario started to look
feasible. At 15%, this price reached $50,000 within 30 years, proving much more feasible, but still a
significant challenge.
4.5: Recommendations
After developing the system dynamics model and establishing several scenarios, it is clear that the
development of fuel cell vehicles in the United States is largely dependent on factors such as platinum
loading, FCV life expectancy, recycling efficiency, and how rapid FCVs are introduced to the market.
Under the worst conditions, the development of the FCV market seems infeasible as the price of
platinum per FCV is more than twice that of a conventional internal combustion engine. However, the
FCV market isn’t heavily limited by platinum in the middle ground scenario. It is still expensive, butit
could be overcome by declining prices for other fuel cell components such as Nafion.
The middle ground scenario provides a basis for establishing goals with regard to fuel cell technology. If
platinum loadings are 50 grams or lower, the average life is around 8 years, recycling efficiency is able to
achieve 90% or better, and FCVs are not rapidly introduced into the market, then the platinum barrier
can be surmounted as long as the price of other FCV components is reduced.
Worldwide production of FCVsis possible, but only on a small scale. FCV market penetration can only
reach about 15% of global vehide production before the price of platinum severely hinders production.
25
Appendix
Establishing FCV Production
Current sources regarding FCV Production are limited in their predictions. The research that currently
has been done usually only considers FCV production in the next 20-30 years. Unfortunately, this time
frame is not large enough to reach market saturation. As a result, current estimates had to be
extrapolated to saturation. Future FCV market penetration was estimated by fitting a Gompertz function
to available estimates from the HyTrans model (see Table 3). The Gompertz function is defined in
equation 2.
ct
y(t) = ae~Pe™ (2)
The function behaves in a similar manner to that of a logistic function.
Table 3: HyTrans Model Predictions
Scenario 1 Scenario 2 Scenario 3
500,000 FCVs/year by 2025 1,000,000 FCVs/year by 2025 | 2,500,000 FCVs/year by 2025
Using this data, a Gompertz function was used to fit the points for each scenario. The resulting
equations can be seen in equations 3 through 5 (also see Figure 10).
—owsrters
Scenario 1: y(t) = 8,000,000 e-* (3)
Scenario 2: y(t) = 8,000,000 e~e**"*F* (4)
Scenario 3: y(t) = 8,000,000 e~e ™4"*F* (5)
26
9000000
8000000 foo
7000000 7 tf
6000000 7 //
5000000
/ ‘Fi — Scenario1
4000000
/ // — Scenario2
L/T/ —— Scenario 3
2000000 L/
1000000 / A
0 + :
0 20 40 60 80 100
FCVs/year
3000000
Time (years)
Figure 10: Predicted Annual FCV Growth Based on the HyTrans Model Fit to the Gompertz Function
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