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Powertrain Innovations for Future
Vehicles – an ARPA-E Perspective
Chris Atkinson, Sc.D.
Program Director
Advanced Research Projects Agency-Energy
US Department of Energy
June 3, 2015
ERC – 2015 Symposium
ARPA-E Advanced Research Projects Agency-Energy
Recommendations
Base on DARPA to be lean and
agile organization
Support creative “out-of-the-box”
transformational energy research
History
2006 Conceived by National Academies
ARPA-E Mission
Catalyze the development of transformational,
high-impact energy technologies
Ensure the U.S. maintains a lead in the development
and deployment of advanced energy technologies
Electrofuels BEEST
PETRO MOVE AMPED
REACT
SBIR/STTR
HEATS BEETIT GRIDS
ADEPT GENI
Solar
ADEPT
TransportationStationary
IMPACCT
Focused Programs 2010-2015: $1,100M, 25 programs
Technology Acceleration Model
time
cost
performance
What does ARPA-E look for?
Steam-powered Cugnot
(1769)
Benz Motorwagen
(1885)
Ford Model T
(1914)
Technologies that lead to new adoption pathways
What Makes an ARPA-E Project?
BRIDGE‣ Translates science into breakthrough technology
‣ Not researched or funded elsewhere
‣ Catalyzes new interest and investment
IMPACT‣ High impact on ARPA-E mission areas
‣ Credible path to market
‣ Large commercial application
TRANSFORM‣ Challenges what is possible
‣ Disrupts existing learning curves
‣ Leaps beyond today’s technologies
TEAM‣ Comprised of best-in-class people
‣ Cross-disciplinary skill sets
‣ Translation oriented
9
A personal note……
Model-Based Control,
Calibration & Optimization of
High Efficiency EnginesChris Atkinson, Sc.D.ATKINSON LLC
SAE 2014 High Efficiency IC Engine Symposium
TRANSIENT CYCLE REQUIREMENTS
BASELINE CALIBRATION
TRANSIENT CONTROL INPUTS
TARGET WEIGHTING & OPTIMIZATION
EMISSIONS, PERFORMANCE AND FUEL CONSUMPTION
TARGETS
SYSTEM AND OPERATING
CONSTRAINTS
INVERSE DYNAMIC DATA-DRIVEN CONTROL MODEL
FORWARD PREDICTIVE DATA-DRIVEN ENGINE
MODEL
ENGINE
MODEL-BASED CONTROL SYSTEM
ENGINE AND SYSTEM
DEVELOPED OFF-LINE
REAL-TIME, ON-LINE
IMPLEMENTATION
ATKINSON LLC 11
12
US Department of Energy SuperTruck Program 2010-2015
Daimler Trucks NA/Freightliner/Detroit Diesel
13
For the Freightliner SuperTruck,
Detroit Diesel and Atkinson LLC developed and implemented
• a fully model-based engine control system,
• using data-driven methods,
• that includes real-time, on-board optimization of fuel
efficiency,
• subject to emissions and performance constraints.
• Results include 12.2 MPG with +115% improvement
in freight efficiency
• With 50.2% peak brake thermal efficiency.
ARPA-E’s energy mandate
‣ Reduce energy imports.
‣ Improve the efficiency of energy generation, storage,
transmission, distribution and usage.
‣ Reduce energy-related emissions including CO2.
‣ Promote US innovation and hence competitiveness in the
energy arena.
– A direct match for automotive engine and powertrain
efficiency.
Total Oil Use
Imported Oil
Total Gasoline Use
Domestic Production
Total Middle Distillate Use
Zero imports with 40% increase in
LD and HD powertrain efficiency
3 overarching energy trends in the automotive
area
– Reduce imported oil and GHGs;
• 90+% of future vehicles will be either conventional or
hybrid vehicles (DOE, EIA, EPA, NRC);
– Vehicle connectivity (V2V, V2I, V2X) advances;
– Vehicle autonomy (of varying degrees).
The Automotive Industry
‣ Is a very mature, conservative industry dominated by
– Regulation (safety),
– Regulation (emissions),
– Customer preferences,
– While meeting strict cost and price constraints.
And hence has been considered ripe for disruption – cf.
Tesla, Apple, Google…
‣ The “precautionary principle” has been replaced by the Wild
West – “permission-less innovation”.
The motivation for new ARPA-E program
area
‣ Target automotive engine and powertrain technologies
beyond those proposed for 2025.
‣ Look for substantial fuel consumption and CO2 emissions
reductions beyond those currently expected.
‣ Take advantage of proposed peripheral or tangential
technologies – connectivity and autonomous operation.
– ARPA-E looks for transformational technologies and
does not fund incremental improvements.
Opportunities for maximizing vehicle efficiency
via connectivity and autonomous operation
‣Powertrain
architecture and
hardware
‣Powertrain control
technologies
0
50
100
150
200
250
300
350
400
0
10
20
30
40
50
1970 1980 1990 2000 2010 2020 2030
FuelEconomy[M
PG]
Year
Technology and fuel efficiency trends
Fuel Economy
Horsepower
Computational
power
ECU introduction
0
50
100
150
200
250
300
350
400
0
10
20
30
40
50
1970 1980 1990 2000 2010 2020 2030
FuelEconomy[M
PG]
Year
Opportunity to use connectivity &
autonomy to increase individual vehicle
fuel economy?
?
Fuel Economy
Horsepower
Computational
power
ECU introduction Connectivity
State of the Art Peak Engine Efficiency
‣ SI NA ~38.5% (Toyota Prius)
‣ CI LD ~42% (VW TDI)
‣ CI HD ~47% (Cummins and Daimler – without WHR)
Why aren’t we there yet?
CITY
HIGHWAY
Advancements in peak engine efficiency
20
30
40
50
60
70
80
90
100
50 100 150 200 250 300 350 400 450
FUELECONOMY(m
pge)(FROMCONVEN
TIONAL
VEH
ICLEDATA
)
WHEELENERGY(Wh/mile)
Advancements in peak engine efficiency
20
30
40
50
60
70
80
90
100
50 100 150 200 250 300 350 400 450
FUELECONOMY(m
pge)(FROMCONVEN
TIONAL
VEH
ICLEDATA
)
WHEELENERGY(Wh/mile)
20%
25%
30%
35%
40%
45%
50% 100%
VW Golf Diesel ~42% BTE
Real life ~24% η
Toyota Prius~38% BTE
Real life ~34% η
Advancements in peak engine efficiency
10
20
30
40
50
60
70
80
90
100
25 75 125 175 225 275 325 375 425
FUELECONOMY(m
pge)(FROMCONVEN
TIONAL
VEH
ICLEDATA
)
WHEELENERGY(Wh/mile)
2012 Chrysler 300
3.6L V-6
2013 VW Jetta
TDI 2.0L I-4
2010 Toyota Prius
~38% BTE
~42% BTE
Advancements in peak engine efficiency
10
20
30
40
50
60
70
80
90
100
25 75 125 175 225 275 325 375 425
FUELECONOMY(m
pge)(FROMCONVEN
TIONAL
VEH
ICLEDATA
)
WHEELENERGY(Wh/mile)
20%25%
30%35% 40%
45%50%
100%
2012 Chrysler 300
3.6L V-6
2013 VW Jetta
TDI 2.0L I-4
2010 Toyota Prius
~38% BTE
~42% BTE
Topic Areas of Interest
‣A – Reducing fuel consumption by improving
powertrain control through connectivity.
‣B – Improving future autonomous vehicle fuel
efficiency via new engine and powertrain
technologies.
Reducing Fuel Consumption through
Connectivity
Advanced Information and Communication Technologies (ICT)
Vehicle Connectivity + Autonomous Driving = EVs?
Vehicle Connectivity + Autonomous Driving = EVs?
Not if 90+% of vehicles will continue to be
conventionally powered or hybrids, even after 2030.
(cf. DOE, NRC, EPA, EIA)
Vehicle Connectivity is a secular trend.
‣ Vehicles will become increasingly connected, to each other
(V2V), to the infrastructure (V2I), and to the “cloud” (V2X).
‣ Vehicles will display increasing degrees of autonomy in their
operation –
– Advanced driver assistance systems
– Semi-autonomous
– Fully autonomous
Connected vehicles – V2V, V2I, V2X
DENSO, 2015
OTA
Fuel properties
Look ahead data
OTA
Fuel properties
Predictive control
Platooning
ITS
Eco-routing
GPS
Collision avoidance
Eco-Routing
V2V
V2I
V2X
What are the enabling opportunities for
increasing individual vehicle fuel efficiency?
Actuators &
sensors
Self-
awareness
Driver input
Autonomous
calibration
New powertrain systems
Self driving
Self parking
Steering
Cruise
Brakes
L1, L2
L3, L4
System level Individual vehicle
Future fuel efficiency potential with V2X?
On an individual vehicle basis
‣ Real-time optimization of powertrain control – on-board or
off-board.
– What can be done with 1000x real-time computational
capability?
– What can be done with more knowledge and
information?
– Supercomputer in the cloud?
– OTA updates of engine control and calibration?
– Bespoke, fully customized individual vehicle calibration
optimization?
What are the fuel efficiency margins due
to…
‣ Variations in fuel composition.
‣ Engineering and emissions margins.
‣ Variation in actuators and sensors, and ageing.
‣ Environmental conditions.
‣ Off-cycle operation.
‣ Driver behavior.
Future potential with Vehicle Autonomy?
‣ Advanced driver assistance systems vs. semi-autonomous
vs. fully autonomous vehicles.
‣ Autonomous EVs offer little potential for efficiency
improvement over non-autonomous EVs – aerodynamics,
weight and cabin loads dominate.
‣ Autonomous engine-powered vehicles offer significant
potential for efficiency improvements.
– Reduction in driver’s expectation of performance.
– Removing the driver from the loop.
Future potential with Vehicle Autonomy?
Autonomous Vehicle Technology – A Guide for Policymakers – Anderson et al., RAND Corporation, 2014
Improving Future Vehicle Fuel Efficiency
via New Engine and Powertrain
Technologies
Possible technology solutions
‣ Progression of existing technologies –
– downsizing and boosting, (or upsizing and NA)
– ultra-lean operation facilitated by new boost, fueling and ignition systems,
– dilution with air or EGR
– variable (high) compression ratio engines,
– Otto and Diesel cycle convergence,
– very high compression engines with knock mitigation,
– LTC, dual fuel or reactivity controlled combustion,
– friction, pumping loss and auxiliary load reduction,
– thermal loss reductions (reduced surface area available for heat transfer),
– stop/start,
– waste heat recovery, hybridization and direct energy recovery systems.
‣ New engine architectures – such as
– free piston engines,
– split-cycle engines,
– entirely new thermodynamic and combustion cycles.
‣ New engines and powertrain operating systems –
– variable displacement engines, or
– intermittent operation engines,
– Integration with electric machines or other hybrid systems.
Any new powertrain technology has to 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
Emissions Regulated criteria pollutants (and now CO2) Regulation
Cost Total cost of ownership (including capex and fuel cost)
Reliability Mean time between failures, maintainability
Utility Acceleration, driveability, NVH, cold start, off-cycle operation,
ease of use, transparency to the user, and acceptable range
Fuel acceptability Use a readily available fuel or energy source.
An Automotive Industry Comparison
Mid-size
Conventional Mid-size Hybrid Tesla Model S
Tesla:Mid-
size
Power (hp) 240 200+ 500 2.0X
Emissions
(Tailpipe) ULEV ULEV ZEV 0.0X
Cost ($) $32,000 $35,000 $95,000 3.0X
Range (mi) 540 540 265 0.5X
Refueling Rate
(MW) 20 20/0.01 0.02 0.001X
Sales Volume
(per yr) 2,500,000 250,000 20,000 0.01X
IAV 2+2 Engine (2014)
Displacement on demand:
• Electro-mechanical
decoupling of 2 cylinders
to reduce frictional losses
and pumping loss, and to
match engine output to
demand.
• Increase BMEP of each
cylinder
Claim: +14% fuel economy
over NEDC drive cycle
Toyota R&D (2014)
10 kW free piston
engine generator
42% BTE claim
Advantages: very high
CR, low friction
Achates Power opposed piston 2 stroke compression ignition engine
(2012)
Advantages: reduced heat rejection, high CR, Diesel cycle
EcoMotors 2 stroke opposed piston, opposed cylinder
compression ignition engine (2010)
Advantages: reduced surface area for heat loss, combustion
phasing, reduced pumping losses (unthrottled 2 stroke cycle,
lean)
Scuderi Split-Cycle engine (2010)
Advantages: over-expansion, reduced thermal losses,
regeneration, combustion phasing
LiquidPiston (2012)
40 hp multifuel
capable rotary
design. Unique
thermodynamic cycle.
Efficiency claims:
58% peak BTE
50% part load
Other new (or old) thermodynamic cycles?
51
Entirely New Engine Concepts?
‣ Develop an entirely new class of modular “cylinder on
demand” engines with integrated hybrid architectures, that
allow the engine to operate at peak efficiencies even under
part load conditions, suitable for conventional and
autonomous operation (at various levels).
A Notional Concept for a Highly Efficient New
Class of Engines
53
TRANSMISSIONCYL1 CYL3CYL2
EM1
C1EM2
C2
EM3
C3
Conclusions
‣ The automotive industry is considered ripe for disruption –
perhaps it is time for engine design to be disrupted.
‣ Peak engine efficiency should be de-emphasized for highly
transient operation, and part-load efficiency improved.
‣ Connectivity can offer engine control, calibration and
optimization advantages.
‣ Autonomous operation takes the driver out of the loop, and
full autonomy removes the driver’s expectations for
performance – and can enable new high efficiency engine
and powertrain options.
Chris Atkinson, Sc.D.
Program Director
Advanced Research Projects Agency-Energy
US Department of Energy