The Automotive Industry to 2025 and Beyond

The Automotive Industry to 2025 and Beyond

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Description: Fuel efficiency improvements will be achieved by vehicle light-weighting, reducing aerodynamic drag and tire rolling losses, engine downsizing, boosting, improved transmissions, increased electrification, hybridization, waste energy recovery, and reductions in friction and parasitic losses. Future vehicles will display greater levels of automation from L0 (no automation) to L1 & L2 advanced driver assistance systems (ADAS) to L3 automation (automated operation with a driver present) and L4 (full automation no driver required).

 
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Contents:
The Automotive Industry
to 2025 (and beyond)
Chris Atkinson, Sc.D.
Program Director
Advanced Research Projects Agency-Energy
2016 EIA Energy Conference
July 11, 2016

ARPA-E Mission

1

Evolution of ARPA-E
500+

39
Awards
Announced

Programs
To Date

2007
Rising Above the
Gathering Storm
Published
America
COMPETES Act
Signed

32
37

1

2009

7

2010

American
Recovery &
Reinvestment Act
Signed

$400 Million
(Recovery Act)

16

12

2011

2012

20

2013

23

2014

2015

America
COMPETES
Reauthorization
Signed

$180 Million $275 Million $251 Million
(FY2011)
(FY2013)
(FY2012)

2016
Anticipated

$280 Million
(FY2014)

$280 Million
(FY2015)

$291 Million
(FY2016)

2

Focused Program Portfolio
ELECTRICITY
GENERATION

ALPHA

FOCUS
SOLAR ADEPT

IMPACCT

GENSETS

REBELS

ELECTRICAL GRID
& STORAGE

GENI

BEETIT

ADEPT

NODES

HEATS

GRIDS

EFFICIENCY
&
EMISSIONS

BEEST

ELECTROFUELS

REACT

METALS

SWITCHES

AMPED

PETRO

2010 - 2012

GRID DATA
IONICS

CHARGES

DELTA

ARID

REMOTE

2013-2014

ROOTS

TRANSNET

RANGE

MOVE

ENLITENED

SHIELD

MONITOR

TRANSPORTATION
& STORAGE

MOSAIC

NEXTCAR

REFUEL

TERRA

2015

2016

3

Energy Consumed by Transportation

Light-, medium and heavy-duty vehicles consume ~11 million barrels per day oil
equivalent, totaling 81% of transportation sector energy consumption, or
~23% of the US primary energy usage.

3 Significant Trends in Automotive Transportation

5

Trend 1 – Fuel Economy
‣ Future fuel economy of the light-duty vehicle fleet will be required to be
significantly higher than today (54.5 mpg CAFE by 2025).

‣ Heavy-duty fuel economy regulated by EPA/NHTSA Phase 2 GHG rules.
Fuel efficiency improvements will be achieved by vehicle light-weighting, reducing
aerodynamic drag and tire rolling losses, engine downsizing, boosting, improved
transmissions, increased electrification, hybridization, waste energy recovery, and
reductions in friction and parasitic losses.
6

Trend 2 – Vehicle Connectivity
‣ Future vehicles will utilize greater levels of connectivity – V2V, V2I, V2X
– this trend is driven primarily by road traffic safety considerations.

7

Connected Vehicles – V2V, V2I, V2X.

DENSO, 2015

Trend 3 – Vehicle Automation
‣ Future vehicles will display greater levels of automation – from L0 (no
automation) to L1 & L2 advanced driver assistance systems (ADAS) to
L3 automation (automated operation with a driver present) and L4 (full
automation – no driver required).

9

HD fleet annual fuel consumption (predominantly diesel fuel)
Annual HD fleet fuel consumption [gal/year] =
fleet size [vehicles] x average VMT [miles/year] / average fuel economy [mpg]





Subtract effect of biofuels (minimal)
Reductions due to FE improvements (significant, 50% reduction possible)
Reduction due to freight efficiency improvement (significant)
VMT changes due to economic activity (varies with industrial, agricultural and
retail activity) and intermodal shifts
– Increases due to fleet size increase (small)
– Reductions due to EV, PHEV, FCEV contributions (minimal)

LD fleet annual fuel consumption (predominantly gasoline)
‣ A first order approach (actually a naïve engineer’s view):
Annual LD fleet fuel consumption [gal/year] =
fleet size [vehicles] x average VMT [miles/year] / average fuel economy [mpg]







Subtract effect of biofuel addition (due to RFS)
Reductions due to FE improvements, including HEVs (significant)
Changes due to fleet mix variations (significant)
VMT changes due to economic activity (varies – now significant)
Increases due to fleet size increase (small)
Reductions due to EV, PHEV, FCEV contributions (currently small)

US Light-Duty
Vehicle Sales

US Light-Duty Vehicle Sales – 2015
‣ US passenger car and light truck sales are a strong function of
– Household income (steady – mean $72,641, median $51,939).
– Unemployment rates (actually workforce participation) (down to
5.4% average across 2015).
– Interest rates (steady and low – prime rate in 2015 was 3.50%).
– Fuel prices (below $2.00/gal – average in 2015 $2.40/gal).
‣ 57% of sales are now pickup trucks, SUVs, crossovers and minivans.
‣ Record 2015 sales for Audi (202k), BMW (346k), Jeep (865k), Honda
(1,409k), Hyundai (762k), Land Rover (71k), Kia (626k), Mercedes Benz
(373k), Nissan (1,351k), Porsche (52k) and Subaru (583k).
‣ Average LD vehicle age is now 11.4 years (Polk).

Sources: EIA, Polk, US Census, Automotive News.

US Light-Duty Vehicle Miles Traveled – VMT

NHTSA, 2015

Vehicle Ownership and Economics
‣ Average vehicle purchase price $34,428 (Dec. 2015) (NADA).
‣ Average loan term 67 months (30% of all loans are 74-84 months) at
$482/month with $28,936 financed (Experian).
‣ Average vehicle miles traveled (VMT) per year is now 12,700 (per
vehicle) and 9,500 (per capita) (NHTSA).
‣ Car total cost of ownership is on average around $0.60/mile (vehicle
cost, financing, insurance, fuel cost).
‣ Total VMT is 3.1T miles (NHTSA).
The road transportation industry is a $3.0T per year business in the US
alone!

Sources: NHTSA, NADA, Experian.

Light-Duty Vehicles – Meeting CAFE in 2025
• OEMs will meet 2025 standards
through a combination of
technology and fleet mix, adjusting
sales of BEVs, PHEVs, HEVs,
(FCVs), diesel and conventional
cars and light trucks.
• They will also pursue ‘extra credits’
and ….

[Remember:
Monroney sticker fuel economy ≠ CAFE ≠ Real world fuel efficiency (calculated from fuel use and VMT)]

Light-Duty Vehicles – Meeting CAFE in 2025
• OEMs will meet 2025 standards
through a combination of
technology and fleet mix, adjusting
sales of BEVs, PHEVs, HEVs,
(FCVs), diesel and conventional
cars and light trucks.
• Beyond 2025……..?
• And what about the effect of
connectivity and automated
vehicle operation? This is not
reflected in regulations.

Fleet-Averaged Light-Duty Fuel Economy – Sales Weighted
(UMTRI)

Vehicle Safety
‣ Road safety – 32,675 fatalities in 2014 (1.07 per 100M VMT)
with 2.31 million injuries in 6.06 million crashes (1.65 million
with injuries, or 53 crashes with injury per 100M VMT).
‣ Has relied to date on passive safety – expensive and costly in
weight.
‣ New active safety mechanisms – ACC and AEB through radar.
‣ Vehicle connectivity will allow for further advances in safety –
DSRC (dedicated short range communications) will broadcast
the actions of all vehicles in a 150m radius.
‣ The effect of automated vehicles?

Sources: NHTSA, industry.

Advanced Driver Assistance Systems (L1-L2)
‣ ACC – adaptive cruise control (accelerator, brake).
‣ LKA – lane keeping assist (steering).
‣ AEB – advanced emergency braking (brake) (standard by 2022).
‣ FCW – forward collision warning.
‣ Parking assistance/pilot.
‣ Alerts – blind spot assist, cross-traffic alerts, rear-view cameras.
‣ Semi-autonomous (MB, Volvo, Subaru, Infiniti, Nissan, Honda, …) and now
essentially autonomous (Tesla Autopilot [L3] and Google car [L4])

L4 Vehicles will demonstrate far higher energy efficiency
‣ Intrinsically safe vehicles “won’t crash”.
‣ Significant reductions in vehicle mass possible due to reduction in safety
equipment required.
‣ Large weight de-compounding effects, also allowing for the use of lighter
materials – CF, plastics, light metals?
‣ Opportunity for xEVs? Reduced energy storage requirements for same vehicle
range.
‣ Automated vehicles will have more/less opportunity for recharging?

Chris Atkinson, Program Director ARPA-E

Connectivity and Automation
‣ Facilitates collaborative vehicle behavior (requires V2V communication)
– Platooning, congestion mitigation, CACC
‣ Facilitates interaction with infrastructure (requires V2I communication)
– SPaT – signal phase and timing
– Eco-approach and departure
‣ Facilitates congestion mitigation (requires V2X, cellular, satellite communication)
– Eco-routing

The 10 Rules of Driving
1. Keep right, keep to the road, avoid on-coming traffic and stay centered within the driving lane.
2. Travel at the minimum of {the speed limit; the prevailing traffic speed; an appropriately safe

speed dictated by road conditions, traffic and environmental conditions}.
3. Stop when required by traffic signals, traffic signs, traffic officers, stationary traffic ahead or
obstacles or debris in the road.
4. Maintain a safe following distance (and do not follow too closely or run into vehicles ahead).
5. Come to a stop, stand or park only when safe and appropriate to do so and in a manner that
will not impede traffic.
6. Adjust speed and merge in turn into traffic with suitable clearance at ramps, stops and merges.
7. Take turns at unregulated stops or merges.
8. Avoid obstacles (stationary and moving) with sufficient clearance to allow for directional
changes (pedestrians, other road users, animals, debris, road repairs etc.)
9. Pass only where safe and do not obstruct or impede other (oncoming) traffic.
10. Drive defensively and predictively, and not selfishly (use common sense, be alert, be predictive
and not merely reactive).

Chris Atkinson, Program Director ARPA-E

Fully Automated Driving – requires 100 million LOC?
Fully automated driving requires the following:
‣ Mapping (“refer”) – refer to pre-developed 3D maps of fixed features, together with
overlays of temporary or moving obstacles for navigation.
‣ Machine vision (“see”) – inputs from multiple sensors including vision, radar, LIDAR,
acoustics/ultrasonics to sense proximity, localization, displacement and velocity of
vehicles, obstacles, roadway etc.
‣ Sensor and data fusion (“recognize”) – fuse inputs and data from machine vision
and mapping (on and off-board) to create a comprehensive visual ‘map’.
‣ Connectivity (“integrate”) – access additional information or data from off-board the
vehicle and to coordinate with other vehicles (V2V, V2X).
‣ Decision making (“think”) – computational capability and advanced decision-making
(not just rule-based).
‣ AI (“decide”) – artificial intelligence (of which ‘deep learning’ is a part) allows for
learning and adaptation.
‣ Automation (“respond”) – control the vehicle in a safe and predictable fashion.
Requires the 99.9999th percentile safety solution (currently at the 99th percentile?
Chris Atkinson, Program Director ARPA-E

Future Potential with Vehicle Autonomy?

Source: Autonomous Vehicle Technology – A Guide for Policymakers – Anderson et al., RAND Corporation, 2014

The Automotive Industry
‣ Is a very mature, conservative industry dominated by





– Regulation (safety),
– Regulation (emissions [optional] and now fuel efficiency),
– Customer preferences,
– While meeting strict cost and price constraints.
To date regulation, incumbency and cost has protected the industry from extreme
disruption.
Industry has always been alert to ‘head-on’ threats
But now there are a new generation of disrupters –
cf. Tesla, Apple, Google, Uber, …

Will electrification, connectivity and automated operation, and new models of
ownership and usage facilitate or accelerate the disruption of the industry?

Chris Atkinson, Program Director ARPA-E

The Disrupters
‣ Have incredibly deep pockets –






– Apple has $220B in cash, which dwarfs the market capitalization of Ford
($54B), GM ($50B), VW ($63B), Tesla ($31B) and is greater than Toyota
($164B).
– Uber (private) has a $50B value – greater than FedEx.
– Bear in mind that the traditional automotive industry operates on very thin
margins, and is the “world’s greatest destroyer of capital”.
Traditional barriers to entry:
– Regulation – Silicon Valley has never acknowledged regulation as a
barrier to doing business.
– Capital – Apple alone has 10x the capital required to succeed.
– Engineering – not an issue with less complex powertrains (although the
battery? Hence Tesla’s Gigafactory).
SV operates on its own time scales (~1-2 years vs. 6-10 years of the
automotive industry).
Tremendous market pull for high technology products.
Chris Atkinson, Program Director ARPA-E

Requirements for commercial success
Any new powertrain technology should be comparable to or better than the baseline in:

Criterion

Explanation

Power

Power density (or energy density including the fuel/energy
storage capacity) ⇒ Customer acceptance

Efficiency

Fuel economy (over real-world dynamic driving) ⇒
Regulation
Energy efficiency

Emissions

Regulated criteria pollutants (and now CO2) ⇒ Regulation

Cost

Total cost of ownership (including capex and energy cost)

Reliability

Mean time between failures, maintainability

Utility

Acceleration, driveability, NVH, cold or off-cycle operation,
ease of use, transparency to the user, and acceptable range

Fuel acceptability Use a readily available fuel or energy source.

Chris Atkinson, Program Director ARPA-E

Huge Foundational Shifts in the Automotive Industry
Old Model
▸ Vehicle hardware as the differentiating
factor
▸ Complex powertrain
▸ Long development cycles
▸ Human operator, stand-alone
▸ Single vehicle with a single user
▸ Owner is driver and user
▸ OEMs are foremost
▸ Tightly controlled supply chain
▸ “One sale, once”
▸ OEM profitability required or at least
desired
Chris Atkinson, Program Director ARPA-E

Huge Foundational Shifts in the Automotive Industry
Old Model
▸ Vehicle hardware as the differentiating
factor
▸ Complex powertrain
▸ Long development cycles
▸ Human operator, stand-alone
▸ Single vehicle with a single user
▸ Owner is driver and user
▸ OEMs are foremost
▸ Tightly controlled supply chain
▸ “One sale, once”
▸ OEM profitability required or at least
desired

New Paradigm
▸ Software as the differentiating
factor
▸ Simplified powertrain – electric?
▸ Short development cycles
▸ Automated operation, connected
▸ New models of usage –
ridesharing
▸ New models of ownership
▸ Suppliers now hold the keys
▸ Electronics, electrics & batteries
▸ New models of monetization
▸ No requirement for immediate
profitability

Chris Atkinson, Program Director ARPA-E

But be wary of non-linear thinking
‣ Vehicle ownership – there is no clear threat to the traditional model. Millennials
have merely delayed purchases for several reasons (city dwellers, high debt
loads, disinterest) but as soon as they move to the suburbs….
‣ Vehicle purchase – leasing and other new models will emerge.
‣ Vehicle usage – ride-sharing versus car sharing.
‣ Disruption – Uber has disrupted the taxi industry (at $1.50 to $2.00 per mile), but
not the passenger car industry (with total cost of ownership at $0.60 per mile).
‣ Economics – vehicles are currently bought, sold, paid for and operated on a VMT
basis. If total VMT does not decrease, it is not at all clear that sales will drop, or
usage change significantly.
‣ Fuel consumption – future vehicles will be significantly more fuel efficient than
today, with no other changes in regulation or economics.
Chris Atkinson, Program Director ARPA-E

The Future Vehicle Industry Landscape
‣ OEMs – e.g. GM, Ford, BMW….
‣ Ride-sharing companies – e.g. Uber, Lyft, GETT, Didi….
‣ “Mobility as a Service” providers.
‣ New ‘dark horses’.
‣ And so now we have
– GM investing in Lyft (OEM+RS).
– Uber looking to develop automated vehicles (RS=OEM).
– Apple looking to develop an EV (‘Project Titan’) (new OEM).
– Google developing automated vehicles (CAV OEM+mapping).
– Ford Smart Mobility (OEM=RS).
Just for a start…..
Chris Atkinson, Program Director ARPA-E

The Future of the OEMs
‣ BMW – Harald Krueger, CEO – March 16, 2016
"The iNext will cover all aspects relevant in the future: autonomous
driving, digital connectivity, intelligent lightweight construction, a
trendsetting interior and the next generation of electro-mobility.“

‣ VW will become a “new mobility company”
‣ Ford will become a “new mobility company”
‣ Toyota Research Institute - $1B for robotics research
‣ New alliances
– DeepDrive – machine learning and AI – Ford, Toyota, VW,
Nvidia, Qualcomm, Panasonic at UC Berkeley
An enormous amount of activity……
Chris Atkinson, Program Director ARPA-E

The Probable Pathway to 2025 and Beyond
‣ Vehicle powertrain technology – more electrification, hybridization, downsizing, waste energy









recovery, 48V systems?
Vehicle structures – vehicle downsizing, weight reduction, more use of light-weight materials.
Vehicle ownership – how will the 84 month ownership cycle be reconciled with 1-2 year product
cycles?
Ride-sharing, car-sharing – new ownership and usage models.
OEMs – the center of gravity of the high-technology components of the vehicle has shifted to
suppliers both old (Bosch, DENSO, Continental, Delphi) and new (Mobileye, Cruise Automation).
ADAS systems will proliferate, leading to L3 automation (such as the Tesla Autopilot) being
essentially standard (L3 is a suite of technologies).
L4 automation requires or facilitates new vehicle architectures (electrification?) but will probably
be slow in penetrating the full market.
Regulations?
The implication for energy usage – energy usage in the LD fleet will almost certainly be reduced
by 2025. After that timeframe, it is not clear.

Chris Atkinson, Program Director ARPA-E

Welcome to the Future.
Chris Atkinson, Sc.D.
Program Director, ARPA-E
chris.atkinson@hq.doe.gov

Chris Atkinson, Program Director ARPA-E

ARPA-E Recruitment Opportunities
ARPA-E is currently hiring new Program Directors
What makes an ideal candidate?
Roles, Responsibilities, and Attributes
Program Development
‣ Perform technical deep dive to solicit input from multiple stakeholders in the R&D community
‣ Present & defend program concept in climate of constructive criticism
Active Project Management
‣ Actively manage portfolio projects from merit reviews through project completion
‣ Extensive “hands-on” work with awardees
Thought leadership
‣ Represents ARPA-E as a thought leader in the program area

‣ R&D experience; intellectual integrity & flexibility; technical breadth; commitment to energy;


communication skills; leadership; and team management
Confidence, but not arrogance

If you are interested in applying or learning
more, please contact a current ARPA-E Program
Director or email arpa-e-jobs@hq.doe.gov

38

TESLA SEC Filing, 2015
Chris Atkinson, Program Director ARPA-E

Consider the Tesla Model S compared to the
Mercedes Benz S-Class:
Criterion
Safety

Compared to Mercedes S-Class
1x

Regulation

0.5x

Emissions

0x (really?)

Engineering Effort

0.5x

Reliability

0.5x

Utility

Economics

Performance 2x
Range 0.5x
Refueling Rate 0.01x
Price 1x, Sales 1x, Profitability 0x

The Tesla Model S should never have been a success. Evidence of a
significant shift in consumer expectations – or just a function of the vehicle
class (a rarefied atmosphere)? Model X and Model 3 sales will tell.
Chris Atkinson, Program Director ARPA-E