THE INFLUENCE OF POTENTIAL RAW MATERIAL SHORTAGES … · 2013-11-10 · Global Lithium Market...
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© Fraunhofer ISI World Conference on Transport Research WCTR13 in Rio de Janeiro, July 2013 Johannes Hartwig, André Kühn, Simon Glöser THE INFLUENCE OF POTENTIAL RAW MATERIAL SHORTAGES ON THE MARKET PENETRATION OF ALTERNATIVE DRIVES
Transcript of THE INFLUENCE OF POTENTIAL RAW MATERIAL SHORTAGES … · 2013-11-10 · Global Lithium Market...
© Fraunhofer ISI
W o r l d C o n f e r e n c e o n T r a n s p o r t R e s e a r c h
W C T R 1 3 i n R i o d e J a n e i r o , J u l y 2 0 1 3
J o h a n n e s H a r t w i g , A n d r é K ü h n , S i m o n G l ö s e r
THE INFLUENCE OF POTENT IAL RAW MATER IAL SHORTAGES ON THE MARKET PENETRAT ION OF ALTERNAT IVE DR IVES
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Introduction
Technology description
Model description
Simulation results
Raw material consumption
Agenda
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Worldwide car sales will grow in future
BRICS-countries will dominate the car market after 2015
Raw material consumption will also be driven by the growing number of car sales
In t roduct ion
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Car sa
les
in m
illio
n v
hc
TRIADE
BRICS
prognosis
Source: Frost & Sullivan
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Dr ive Technologies in the Pr ivate Car Sector
Battery ElectricVehicle
(BEV)
Fuel CellElectric
Vehicle(FCEV)
Internal Combustion Engine
(ICE)
Hybrid Drive Plug-In HybridElectric Vehicle
(PHEV)
Depending on usage and technology price a wide range of different drives will be offered in future:
Especially battery-driven technologies and fuel cells depend on very specific raw materials
(cobalt, lithium for batteries – platinum for fuel cells – copper & rare earths for electric engines)
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Overv iew of the Globa l Mobi l i ty Model (GloMo)
economy
population
new cars
# new cars
segment & technology choice
fleet
disposable income
age cohorts # cars
# new cars
gdp growth
gdp
+
+
population
population
growth
wealth
Income
growth
+ +
-
national income
growth
+
disposable income
per capita
-
population
population
income
wealth
fleet
growth
+
+
-
-
energy costs
purchase price+
total cost of
ownership
acteptance
technology
share
+
+
purchased
cars
+
fleet growth
+fleet
+ scrapped
cars
+
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Feedback Loops wi th in the Car F leet Module
new cars
+
car stock
energy consumption
+
energy price
+
--
new cars
+ new cars
price per car
+- -
1
2
Feedback loops as a typical element of system dynamics modelling
Highly increasing number of new cars leads to higher prices due production shortages
A growing car stock leads to higher energy consumption and increasing fuel prices
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Strong technology progress
Low technology prices
High oil price
Scenar ios of A l ternat ive Dr ive Di ffus ion
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bal
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FCEV
BEV
PHEV
Hybrid
ICE
scenario 1: strong diffusion scenario 2: weak diffusion
Weak technology progress
High technology prices
Medium oil price
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Bas ic Raw Mater ia l s for L i th ium Ion Batter ies : L i th ium & Cobal t
Vo
lta
ge
me
asu
red
ag
ain
st L
i m
eta
l (V
)
3-V System
4-V System
3
2
1
0
4
5
Li - Metal
Graphit
Amorphous carbon
LiSi
LixV3O4 Li4Ti5O12
MnO2
LiFePO4
LiNO
LiMn2O4
LiCoO2
Ca
tho
de
ma
teria
l
42
% o
f m
ate
ria
l co
sts
An
od
e M
ate
ria
l
11
% o
f m
ate
ria
l co
sts
Potential cathode materials for large scale batteries for electric vehicles:
LiCoO2 (lithium cobalt oxide), LiMnO2 (lithium manganese oxide), LiNiO (lithium nickel oxide), LiFePO4 (lithium iron phosphate) mixed oxides such as Li(Ni0,85Co0,1Al0,05)O2 or Li(Ni1/3Co1/3Mn1/3)O2
Sources: Fraunhofer ICT (TÜBKE 2011)
KIT (KETTERER 2009)
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The L i fe Cyc le of Coba l t wi th in a Sys tem Dynamics Model
Simulation of global material flows from mining over production and fabrication to end-use applications
Stock in use over the porduct lifetime (lifetime distributions)
Simulation of waste management and recycling
Identification of cobalt demand by sector regarding primary (from mining) and secondary (from recycling) production
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Deve lopment of Market Shares in Dur ing the Prev ious Decade
Cobalt:
Rapid increase of demand for Electrodes during the last decade – particularly due to lithium-ion cells in electronic products
Current share of vehicle batteries around 5%
Lithium:
Rapid increase of demand for Lithium-ion cells during the last decade – particularly due to batteries in electronic products
Current share of vehicle batteries around 5%
Ceramics and glass46%
Batteries electronics and
machinery6%
Greases
11%
Aluminium11%
Air treatment
6%
Continuous casting
4%
Rubber and thermoplastics
4%
Pharmaceuticals
1%
Other
10%
Battery vehicles≈0%
Ceramics and glass28%
Batteries electronics and
machinery24%
Greases
13%
Aluminium5%
Air treatment6%
Continuous casting
4%
Rubber and thermoplastics
3%
Pharmaceuticals2%
Other10%
Battery
vehicles5%
2000 2012Ceramics and glass
46%
Batteries electronics and
machinery6%
Greases
11%
Aluminium11%
Air treatment
6%
Continuous casting
4%
Rubber and thermoplastics
4%
Pharmaceuticals
1%
Other
10%
Battery vehicles≈0%
Ceramics and glass28%
Batteries electronics and
machinery24%
Greases
13%
Aluminium5%
Air treatment6%
Continuous casting
4%
Rubber and thermoplastics
3%
Pharmaceuticals2%
Other10%
Battery
vehicles5%
2000 2012
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Scenar ios of A l ternat ive Dr ive Di ffus ion
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FCEV
BEV
PHEV
Hybrid
ICE
scenario 1: strong diffusion scenario 2: weak diffusion
Hybrid: 1.5 kWh
PHEV: 15 kWh
BEV: 25 kWh
490 g/kWh Cobalt
160 g/kWh Lithium
For further calculation concerning raw material consumption of electric vehicles, the following battery sizes are used:
decreasing over time due to higher raw material efficiency and substitution of cobalt by LiFePO4
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Cobalt market effects:
Severe effect of the strong diffusion scenario: ≈50% of demand caused by automobile industry, 70% by total electrode production
Negligible share of automobile industry in the weak diffusion scenario
High uncertainty of market development
High dependence of future demand on automobile industry
High risk for investments in mining and production facilities
Effect of the Two Scenar ios on the Globa l Coba l t Market
0
100
200
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400
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600
2000
2002
2004
2006
200
8
201
0
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2
2014
2016
2018
2020
2022
2024
2026
2028
2030
Co
bal
t use
by
sect
or
in k
ilo t
on
s
Electrodes vehicles
Superalloys
Speciality chemicals
Pigments
Other
Magnetic alloys
Hard metals
Electrodes electronics and machinery
Catalysts
Total cobalt production
12%
21%
3%1%
3%2%1%
8%
49%
0
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0
Co
bal
t use
by
sect
or
in k
ilo t
on
s
Electrodes vehicles
Superalloys
Speciality chemicals
Pigments
Other
Hard metals
Magnetic alloys
Electrodes electronics and machinery
Catalysts
Total cobalt production
22%
41%
5%
2%
5%
3%
3%
16%
3%
Strong Diffusion
Weak Diffusion
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Lithium market effects:
Severe effect of the strong diffusion scenario: ≈40% of demand caused by automobile industry, 60% by total electrode production
Negligible share of automobile industry in the weak diffusion scenario
High uncertainty of market development
High dependence of future demand on automobile industry
High risk for investments in mining and production facilities
Effect of the Two Scenar ios on the Globa l L i th ium Market
Strong Diffusion
Weak Diffusion
10%
17%
9%
1%5%
3%1%4%7%
43% Strong Diffusion
17%
28%
15%
2%
8%
5%
3%
7%
12%
3%
0
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250
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Lith
ium
use
by
sect
or
in k
ilo t
on
s
Battery vehicles
Other
Pharmaceuticals
Rubber and thermoplastics
Continuous casting
Air treatment
Aluminium
Greases
Batteries electronics and machinery
Ceramics and glass
Total lithium use
Weak Diffusion
0
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2000
2002
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2010
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2014
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2020
2022
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Lith
ium
use
by
sect
or
in k
ilo
to
ns
Battery vehicles
Other
Pharmaceuticals
Rubber and thermoplastics
Continuous casting
Air treatment
Aluminium
Greases
Batteries electronics and machinery
Ceramics and glass
Total lithium use
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Future Work and Improvements of the Model
Mining Recycling
Demand (Dt) – Supply (St)
Economy Driven Demand: Technology Driven Demand:
Substitution / Efficiency Effects:
Economy Driven Demand =
F(GDP)Technology Driven Demand =
F(Sectoral Market Development –
Substitution Effects)Substitution Effects =
F(Price, Temporal Delay)
Theoretical Demand
Total Supply
ΔPrice/Δt = F(Dt-St)P(t)
Metal Price level
Dynamic raw
material cycles
Global GDP
GDP Emerging
Markets
(country level)
World population,
Prosperity share
Economy driven
component
Auxiliary variables
(functional mechanics)
Te
ch
no
log
y D
rive
Technology driven
component
Auxiliary variables
(functional mechanics)
ΔSectoral market development/Δt
ΔSectoral mass flows (%)
- Δ Sectoral Market Development (%)
= ? Substitution Effects
Auxiliary variables
(functional mechanics)Temporal delay
Raw Material Market Model [RaMa] (individual model for each metal):
Combined Structural Equation and System Dynamics Model
Global Mobility Model [GloMo]:
Combined Structural Equation and System Dynamics Model with a
Logit-Desicion-Model for discrete technology choice on the micro level
economy
population
new cars
# new cars
segment
& technology choice
fleet
disposable income
age cohorts # cars
# new cars
gdp growth
gdp
+
+
population
population
growth
wealth
Income
growth
+ +
-
national income
growth
+
disposable income
per capita
-
population
population
income
wealth
fleet
growth
+
+
-
-
energy costs
purchase price
+
total cost of
ownership
acteptance
technology
share
+
+
purchased
cars
+
fleet growth
+ fleet + scrapped
cars
+
Feedback of price level on the raw material demand
0
5
10
15
20
25
30
35
40
2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030
Ch
ine
se a
uto
mo
tive
mar
ket:
car
sal
es
in m
illi
on
car
s
FCEV
BEV
PHEV
Hybrid
Conventional
-
-
Diffusion of electromobility
Feedback of raw material prices
on battery costs
GloMo
GloMo:
Improved statistical correspondances
Raw Material Market Model:
Higher detail in modeling other raw material demendent sectors in order to get a better understanding of potentials of substitution in cases of raw material scarcity and high pricing
More detail in modeling future future battery technology development
Linkage of the models:
Joint exogenous variables such as economic development
Improved feedback mechanism of high pricing on technological development
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Forecast of worldwide cars sales per drivetrain technologies is volatile and strongly depends on the development of framework conditions (technology availability, oil price,…)
Uncertainty in forecasting battery technology: Raw materials, particularly cobalt are likely to be substituted in the long term
High planning uncertainties and market risks both mining companies and battery or car producers are confronted with
Market penetration of BEV and PEV depends on supply with lithium and cobalt which both have high geological reserves, thus the potential depletion of the materials is not relevant
High lead times and planning periods of mining projects (5-10 years):
Are today‘s investments in mining and production facilities able to meet future demand?
Conc lus ions
