Global EV Outlook 2019 |
3. Outlook |
Figure 3.5. Increased annual demand for materials for batteries from deployment of electric vehicles by scenario, 2018-30
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Cobalt |
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Lithium |
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600 |
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600 |
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(kt) |
500 |
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500 |
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400 |
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400 |
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demand |
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300 |
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300 |
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Metal |
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200 |
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200 |
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100 |
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100 |
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0 |
NPS |
EV30@30 |
0 |
NPS |
EV30@30 |
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2018 |
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2030 |
2018 |
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2030 |
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Manganese |
Nickel class I |
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2 500 |
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2 500 |
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(kt) |
2 000 |
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2 000 |
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demand |
1 500 |
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1 500 |
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Metal |
1 000 |
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1 000 |
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500 |
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500 |
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0 |
NPS |
EV30@30 |
0 |
NPS |
EV30@30 |
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2018 |
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2030 |
2018 |
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2030 |
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Historical |
Central estimate |
Variability for chemistry |
Current supply |
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Notes: Future demand for materials for battery manufacturing relative to the scenario projections is based on the global battery capacity shown in Figure 3.4 and the following assumptions of the shares for cathode chemistries in LDVs. For the central estimate: 10% NCA, 40% NMC 622 and 50% NMC 811. For the high cobalt chemistry (upper range in the figure): 10% NCA and 90% NMC 622. For the low cobalt chemistry (lower range in the figure): 10% NCA and 90% NMC811. The share of cathode chemistries for heavyduty vehicles is assumed to be 20% NMC 622 and 80% NMC 811. The share of metals in the battery for the types of chemistries analysed is indicated in Table 6.1 in the Global EV Outlook 2018 (IEA, 2018a). The current supply of nickel refers to class I nickel.
Sources: IEA analysis developed with the IEA Mobility Model (IEA, 2019a). Current material supply for cobalt and lithium is based on USGS (2019), manganese supply is from International Manganese Institute (2018) and class I nickel demand in 2018 is from BNEF (2019)
The demand for cobalt and lithium are expected to significantly rise in the period to 2030 in both scenarios. Cobalt demand has the largest variation to the type of cathode chemistry. Cobalt and lithium supply needs to scale up to enable the projected EV uptake.
Charging infrastructure
The deployment of EV supply equipment (including both private and publicly accessible chargers) needs to proceed in parallel, and sometimes (i.e. highway chargers) anticipate that of the EV stock.
PAGE | 133
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Global EV Outlook 2019 |
3. Outlook |
This section projects the private and public charging infrastructure needs to power LDVs and public buses over the outlook period, taking into account structural drivers and policy objectives.15
•Structural drivers typically reflect consumer preferences and technical requirements. For example, charging practices for passenger car owners are largely reliant on slow charging at home or workplace; buses tend to have access to fast chargers at privately owned facilities; LCVs may rely largely on private slow or fast charging infrastructure; trucks need high power charging; and most vehicles need some degree of access to publicly available chargers.
•The key policies and targets related to deployment of EV charging infrastructure for China and the European Union – leaders in the transition to electric mobility – are summarised in Table 3.3. The target ratios for the number of chargers per vehicle of both China and the European Union are assumed to be stable in both scenarios (based on available information).
Table 3.3. Key government policy measures and targets for development of charging infrastructure
Country/region
Asia
China
Europe
European Union
Key policy measures and targets
Target of 4.3 million private chargers (0.9 chargers per EV), 500 000 publicly accessible chargers (0.1 chargers per EV) and 12 000 battery-swapping stations for 5 million EVs by 2020.
Requires governments to deploy an appropriate number of publicly accessible chargers by 2020 and includes an indicative number of 1 publicly accessible charger per 10 electric cars.
Announced (year) Source
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2015 |
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Government of China |
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(2015) |
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2014 |
European Commission |
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(2014) |
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Notes: There are also charging infrastructure targets in California (State of California, 2018), New York (New York State, 2019), India (Government of India, 2019), New Zealand (Government of New Zealand, 2017), Japan and Korea (APEC, 2017). Due to structural differences of how targets are set (e.g. only a specific type of charger or only targets for specific distances) and limited geographical scope, these targets are not explicitly included in the scenario projections.
Box 3.3 considers the implications for deployment of charging infrastructure due to the transition to a higher reliance on electricity in trucks, despite a significant amount of
15 From a methodological perspective, it is worth noting that countries with high urban density (e.g. China and Japan) are subject to different assumptions in this assessment compared to the rest of the main global economies (having comparatively lower urban density). This analysis also includes estimates of installed capacity per charging type to improve the assessment of charging services based on recharging times.
PAGE | 134
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