Powertrain Control (1)/50
Anna G. Stefanopoulou, Powertrain Control Laboratory
University of [email protected]
National Science FoundationUS Department of Energy, ARPA-E,
US Army with
Bosch, Daimler, Ford, Toyota
Thanks to the
Engine Control At the Rugged Edge of
High Efficiency
IFAC- AACAdvances in Automotive Control, Kolmarden, June 2016
Powertrain Control (2)/50
1
2
4610
20
4060
100
200
400
1900 1920 1940 1960 1980 2000 2020 2040 2060
FUELECO
NOMY[m
pg]
YEAR
1921ModelT(CITYONLY) HybridsCarisetal.560010(ADJ) TCDiesel(GasolineEq.)AustinandHellman730790 TCGasolineEPAFETrends2013 FED.STDS.2017-2025
BASICCOMB.,(DESIGN,FUEL,OCTANE,CR)
EMISSIONS
CAFE– FE–CO2CATALYSTS
FED.STD.2017-2025
CITY/HWY(Unadjusted)3,750lb.TestWt.
G. Lavoie. "Reflections on the Evolution of Ideas and Technology in SI Engine Combustion" Oral Presentation - ICEF2014-5703. ASME 2014 Internal Combustion Engine Division Fall Technical Conference, October 19-22, 2014, Columbus, IN.
Light Duty Fuel Economy Trends Over the Last 100 Years
Powertrain Control (3)/50
History Lessons (US-focused)Slow ..? Slender … ?
Powertrain Control (4)/50
Slow ..?
No .., just better!
Slender … ?
Powertrain Control
12V BAS Micro-HEV
**
Cost effectiveness
TRBDS--1
GDIVVL
VVTFR
PHEV MPG
DIESEL
HEV
PHEV MPGeEV (estimated)
Data Sources: 1. Assessment of Fuel Economy Technologies for Light-Duty Vehicles (2011) National Research Council2. * www.fueleconomy.gov DOE & EPA website (MPGe : 1 Gallon of Gasoline = 33.7 kWh)3. **MPG baseline 2008 midsize cars. NHTSA stats (2014)
2025 Target
Powertrain Control
12V BAS Micro-HEV
**
Cost effectiveness
TRBDS--1
GDIVVL
VVTFR
DIESEL
HEV
Data Sources: 1. Assessment of Fuel Economy Technologies for Light-Duty Vehicles (2011) National Research Council2. * www.fueleconomy.gov DOE & EPA website (MPGe : 1 Gallon of Gasoline = 33.7 kWh)3. **MPG baseline 2008 midsize cars. NHTSA stats (2014)
2025 Target TWC
SCR+…$...$
Exhaust After-
Treatment
Powertrain Control (7)/50
Efficiency Improvement: Turbo-Downsizing (TRBDS)
270
270
400
600
300
255
255
BSFC 3.6L V6 [g/kWh]
Engine Speed [RPM]
270
270
300
600
400
300
FTP−75
Engin
e L
oad
[N
m]
1000 1500 2000 2500 3000 3500
50
100
150
200
250
300
350
0−5
−15−20
−10−5
−25
−5
0
Engine Speed [RPM]
rel. BSFC 2.0L I4 − 3.6L V6 [%]
−25−25
−5
−5
0
5
−10−5
10
−5
−10
−20−15
0
−15
FTP−75
Engin
e L
oad
[N
m]
1000 1500 2000 2500 3000 3500
50
100
150
200
250
300
350
20%
10%
5%
Efficiency Improvements %
Worst
Controlling the Dynamics
Original 3.6L V6
Turbocharged2.0L I4
5. Cnv4. v/eTC3. thr/wg2. TC-Dnsz1. Dnsz
Powertrain Control
12V BAS Micro-HEV
**
Cost effectiveness
TRBDS--2
TRBDS--1
GDIVVL
VVTFR
2025 Target
PHEV MPG
DIESEL
HEV
PHEV MPGeEV (estimated)
Powertrain Control (9)/50
9
Naturally Aspirated
TurbochargedTurbocharged+eEGR
Low-pressure Exhaust Gas
Recirculation (eEGR)
Technologies with Large Tradeoff between Fuel Efficiency & Transient Response
Turbo-Downsizing + Cooled Low Pressure EGR (TRBDS-2)
Powertrain Control
12V BAS Micro-HEV
**
Cost effectiveness
TRBDS--2
TRBDS--1
GDIVVL
VVTFR
2025 Target
PHEV MPG
DIESEL
HEV
PHEV MPGeEV (estimated)
?
Powertrain Control (11)/50
Homogeneous Charge Compression Ignition (HCCI)
Figure: Adopted from Edwards, D. in Dynamics Days, 2008, Knoxville, TN
Spark Ignition (Gasoline)• Spark ignites premixed fuel-air• Propagating flame
HCCI (Gasoline)• Spontaneous autoignition• Uniform combustion
Compression Ignition (Diesel)• Fuel injected into compressed air• Diffusion flame
SI HCCI CIPeak Temperature (K) >2000 1600 1800
NOx emission High Low MediumCombustion Duration (CAD) 40 2-10 40
Car Makers Seek New Spark In Gas Engines The Wall Street Journal 09/28/04“… engineers call homogenous-charge compression-ignition, or HCCI and expected to provide
80% of the efficiency of a hybrid or a diesel for 20% of the cost, …”
Too high pressure riserate at high Load
Powertrain Control (12)/50
Figure: Adopted from Edwards, D. in Dynamics Days, 2008, Knoxville, TN
Spark Ignition (Gasoline)• Spark ignites premixed fuel-air• Propagating flame
Auto-Ignition (HCCI-Gasoline)• Spontaneous autoignition• Uniform combustion
Compression Ignition (Diesel)• Fuel injected into compressed air• Diffusion flame
Fuel Injection
Gas
olin
e Diesel
Spark Ignition
Homogeneous Charge Compression Ignition (HCCI)
No DirectActuation
Controlled by Trapped Dilution
Powertrain Control (13)/50
Gasoline Systems - HCCIHCCI Actuators & Sensors (Cost)
VariableValve
Injector
In-cylinderpressure sensor
Controllerθ50ref
θ50
Combustion phasing controlled through
trapped dilutionAnd
mixture reactivity
Powertrain Control (14)/50
Homogeneous ChargeChemical Kinetics=Arrhenius Integral
-
Powertrain Control (15)/50
The importance of the Thermal Coupling
from Cycle-to-Cycle
Powertrain Control (16)/50
Stable, Unstable, and Limit Cycle Behavior
Automotive EngineeringSAE 2002-01-0111– LundRegions with Stable and Unstable operationASME ICE 2000– Caterpillar Limit cycle behaviorSAE 892068– Southwest Research InstituteVery Stable and Unstable behavior at different regions
Stability in auto-thermal reactors Heerden 1953, Liljenroth 1918
Breathing Combustion
Intake Temperature, Tivc (K)
Blow
Dow
nTe
mpe
ratu
re, T
bd(K
)
Early CombustionPhasing
Chiang, CDC 2004 Chiang, IEEE-TCST 2004
Powertrain Control (17)/50
Drive around Stable Points!Breathing Combustion
Intake Temperature, Tivc (K)
Early CombustionPhasing
Chiang CDC 2004 & Chiang, IEEE-TCST 2004
Clean or Efficient? An Engine Goes for ‘Both of the Above’
By LINDSAY BROOKEAugust 19, 2007
SAE-2009-01-1131
Powertrain Control (18)/50
Two Input Single Output (TISO) Controller
Powertrain Control (19)/50
TISO Controller & Load Governor
Powertrain Control (20)/50
Still a strange ringing
Powertrain Control (21)/50
The importance of the Chemical (Fuel) Couplingfrom Cycle-to-Cycle
Heat Release Analysis
Observations from the high variability operation
Detailed Heat Release Observations
Key factors for describing CVNonlinear coupling betweenØ the recycled thermal energyØ the recycled chemical energy in the unburned fuel
Powertrain Control (24)/50
Ø Period doubling bifurcations
Ø Thermal runaway
Ø Noisy simulations match the data
Model Predicts Global Behavior (2 nonlinear ODEs)
Powertrain Control (25)/50
E. Hellström, et al., Cyclic variability and dynamical instabilities in autoignitionengines with high residuals. IEEE Trans on Control Systems Technology, 2013.
Model Validation: Predict the onset of CV
Controlling Combustion at its Limit
InjectionTiming (usoi)
CombustionPhasing (θ50)
HCCI Control Toolbox~T
orqu
ePh
asin
g
Powertrain Control (28)/50
Controls Overview
[1]Jade,Dissertation,2014[2]Larimore,Dissertation,2014[3]Ravietal.,JDSMC,2012[4]Gorzelic,Dissertation,2015[5]Zhangetal.,DSCC,2014[6]Nuesch,Dissertation,2015
SI/HCCI switching controlsObjective: • Short• Torque• Low penalty
HCCI controls:Objective:• Torque
SI controls:Objectives:• Torque• Stoich. air-fuel ratiofuel
spark
throttle
fuel
valve timing
fuel
spark
throttle
2-stage cams
valve timing
SI/HCCI supervisory controlObjective: • Fuel economy• Emissions• Driveability
[1], [2], [3]
[4], [5]
StandardSwitch:
Yes or no?
Powertrain Control (29)/50
Mode TransitionsSignificant number of mode transitions during driving cycle!
During the 7-15 cycles of switching the efficiency is worst than SI.
Switch if you stay long enough in HCCI to pay for the switching penalty.
Powertrain Control (30)/50
0 500 1000 1500 0 500 0 5000
20
40
60
80
Velocity[m
ph]
Time [s]
FTP75 HWFET US06
Vehicle Model
City with cold start Highway Aggressive
0
10
20
30
Velocity[m
ph]
500
1000
1500
2000
2500
Enginespeed[R
PM]
0 5 10 15
0
50
100
150
Enginetorque[N
m]
Time [s]0 5 10 15
0
1
2
3
Fuelflow
[g/s]
Time [s]
Reference
Tolerance
Brake pedal
Clutch pedal
Gear
vAccel.
pedal
DriverRef. velocity
Ref. gear
Vehicle
Clutchtorque
Brake pedalClutch pedalGear
vAccel.pedal
DriverRef. velocity
Ref. gear
Clutch state
Vehicle
TireforcesDrive-
trainClutchtorque
Brake pedalClutch pedalGear
vTeAccel.pedal
DriverRef. velocity
Ref. gear
Clutch state
Vehicle
TireforcesDrive-
trainEngine
M
ωe
Clutchtorque
Brake pedalClutch pedal
Tcmd
Gearv
ECU
TeAccel.pedal
DriverRef. velocity
Ref. gear
Clutch state
Vehicle
TireforcesDrive-
trainEngineuphase / uswitch
M
ωe
0
10
20
30
Velocity[m
ph]
500
1000
1500
2000
2500
Enginespeed[R
PM]
0 5 10 15
0
50
100
150
Enginetorque[N
m]
Time [s]0 5 10 15
0
1
2
3
Fuelflow
[g/s]
Time [s]
Measurement
Simulation
Reference
Tolerance
0
10
20
30
Velocity[m
ph]
500
1000
1500
2000
2500
Enginespeed[R
PM]
0 5 10 15
0
50
100
150
Enginetorque[N
m]
Time [s]0 5 10 15
0
1
2
3
Fuelflow
[g/s]
Time [s]
Measurement
Simulation
Reference
Tolerance
0
10
20
30
Velocity[m
ph]
500
1000
1500
2000
2500
Enginespeed[R
PM]
0 5 10 15
0
50
100
150
Enginetorque[N
m]
Time [s]0 5 10 15
0
1
2
3
Fuelflow
[g/s]
Time [s]
Measurement
Simulation
Reference
Tolerance
Matlab / Simulink / StateflowParameterized for Cadillac CTSCurb mass: 1725 kg
Powertrain Control (31)/50
To Switch … or not to Switch
Powertrain Control (32)/50
To Switch … or not to Switch
Powertrain Control (33)/50
23.8
24
24.2
24.4
24.6
24.8
Fueleconomy[M
PG] FTP75
1) SI2) SI/HCCI inst.
38.5
39
39.5
40
HWFET
25.5
26
26.5
US06
−1
0
1
2
3
4
ImprovementoverSI[%
]
0
5
10
15
20
HCCIresidence[%
]
0
5
10
15
20
0
5
10
15
20
1) 2) 0
0.5
1
1.5
TRM
S[N
m]
1) 2) 0
0.5
1
1.5
1) 2) 0
0.5
1
1.5
23.8
24
24.2
24.4
24.6
24.8
Fueleconomy[M
PG] FTP75
1) SI2) SI/HCCI inst.
38.5
39
39.5
40
HWFET
3) SI/HCCI NoP
4) SI/HCCI PeP
25.5
26
26.5
US06
−1
0
1
2
3
4
ImprovementoverSI[%
]
0
5
10
15
20
HCCIresidence[%
]
0
5
10
15
20
0
5
10
15
20
1) 2) 3) 4)0
0.5
1
1.5
TRM
S[N
m]
1) 2) 3) 4)0
0.5
1
1.5
1) 2) 3) 4)0
0.5
1
1.5
23.8
24
24.2
24.4
24.6
24.8
Fueleconomy[M
PG] FTP75
1) SI2) SI/HCCI Inst
38.5
39
39.5
40
HWFET
3) SI/HCCI NoP
4) SI/HCCI PeP
25.5
26
26.5
US06
−1
0
1
2
3
4
ImprovementoverSI[%
]
0
5
10
15
20
HCCIresidence[%
]
0
5
10
15
20
0
5
10
15
20
1) 2) 3) 4)0
0.5
1
1.5
TRM
S[N
m]
1) 2) 3) 4)0
0.5
1
1.5
1) 2) 3) 4)0
0.5
1
1.5
23.8
24
24.2
24.4
24.6
24.8
Fueleconomy[M
PG] FTP75
1) SI2) SI/HCCI inst.
38.5
39
39.5
40
HWFET
3) SI/HCCI NoP
4) SI/HCCI PeP
25.5
26
26.5
US06
−1
0
1
2
3
4
ImprovementoverSI[%
]
0
5
10
15
20
HCCIresidence[%
]
0
5
10
15
20
0
5
10
15
20
1) 2) 3) 4)0
0.5
1
1.5
TRM
S[N
m]
1) 2) 3) 4)0
0.5
1
1.5
1) 2) 3) 4)0
0.5
1
1.5
Drive Cycle Results: Penalty and Prediction
Penaltyleads tofueleconomyreduction
Prediction reducesuneccesary switches.
Reduction inHCCIresidencetime
Largereduction indrivertorqueviolations
*Nueschetal.,Isiteconomicalto ignorethedriver?Acasestudyonmultimodecombustion,DSCC2015
Powertrain Control (34)/50
24
24.5
Fueleconomy[M
PG] FTP75
−1
0
1
2
3
4
ImprovementoverSI[%
]
1) SI
2) SI/HCCI inst.
3) SI/HCCI NoP
4) SI/HCCI PeP
0
10
20
HCCIresidence[%
]
1) 2) 3) 4) 0
1
2
TRM
S[N
m]
Ignore the Driver
34
24
24.5
Fueleconomy[M
PG] FTP75
−1
0
1
2
3
4
ImprovementoverSI[%
]
1) SI2) SI/HCCI inst.3) SI/HCCI NoP
4) SI/HCCI PeP
5) SI/HCCI ignore
0
10
20
HCCIresidence[%
]
1) 2) 3) 4) 5)0
1
2
TRM
S[N
m]
1000 1500 2000 2500 3000 3500
0
50
100
150
Engine speed [RPM]
Enginetorque[N
m]
Tim
e (
FT
P75)
[%]
0.0001
0.001
0.01
0.1
1
10
1000 1500 2000 2500 3000 3500
0
50
100
150
Engine speed [RPM]
Enginetorque[N
m]
Tim
e (
FT
P75)
[%]
0.0001
0.001
0.01
0.1
1
10
HCCI
Ignore excursions
Significant impact on driveability
Extended residence time
*Nueschetal.,Isiteconomicalto ignorethedriver?Acasestudyonmultimodecombustion,DSCC2015
Powertrain Control
An electric motor can extend HCCI residence time!
“Thegreaterthehybridization, thelowerthefuelconsumptionreductioninHCCIvehicles.”
[1]
[1]Delormeetal.,EvaluationofHCCIenginesforvariouselectricdriverpowertrains,EVS,2010[2]RickandSisk,Asimulationbasedanalysisof12Vand48Vmicrohybridsystemsacrossvehiclesegmentsanddrivecycles,SAE,2015
• ResidencetimeinHCCIlow• Manymodeswitches
48Vmildhybridelectricvehicleshowgreatpotentialatrelativelylowcost
[2]
HCCI mild-Hybrid
Powertrain Control (36)/50
24
25
26
27
0%
5%
Fuel
economy[M
PG]
FTP75Conv.
1) SI
2) SI/HCCI inst.
39
40
41
42
43
44
45HWFET
Conv.
0%
2.5%
3) SI/HCCI
26
27
28
29
US06Conv.
0%
2.5%
1) 2) 3) 0
20
40
60
HCCIresiden
ce[%
]
1) 2) 3) 0
20
40
60
1) 2) 3) 0
20
40
60
24
25
26
27
0%
5%
0%
5%
Fuel
economy[M
PG]
FTP75Conv. HEV
1) SI
2) SI/HCCI inst.
39
40
41
42
43
44
45HWFET
Conv. HEV
0%
2.5%0%
2.5%
3) SI/HCCI
26
27
28
29
US06Conv. HEV
0%
2.5%
0%
2.5%
1) 2) 3) 1) 2) 3)0
20
40
60
HCCIresiden
ce[%
]
1) 2) 3) 1) 2) 3)0
20
40
60
1) 2) 3) 1) 2) 3)0
20
40
60
Drive Cycle Results: HEV
MildHEVoffersgreatsynergieswithHCCIduringFTP75dueto:• Severalregenerativebraking
periods(≠HWFET)• Frequentlowloaddemand
(≠US06)
• ElectrictorqueassistleadsinsignificantincreaseinHCCIresidencetime
Powertrain Control (37)/50
24
25
26
27
0%
5%
0%
5%
Fuel
economy[M
PG]
FTP75Conv. HEV
1) SI
2) SI/HCCI inst.
39
40
41
42
43
44
45HWFET
Conv. HEV
0%
2.5%0%
2.5%
3) SI/HCCI No storage
26
27
28
29
US06Conv. HEV
0%
2.5%
0%
2.5%
1) 2) 3) 1) 2) 3) CS+0
+20
+40
+60
TailpipeNO
x[m
g/mi]
1) 2) 3) 1) 2) 3) 0
20
40
60
1) 2) 3) 1) 2) 3) 0
20
40
60
24
25
26
27
0%
5%
0%
5%
Fuel
economy[M
PG]
FTP75Conv. HEV
1) SI
2) SI/HCCI inst.
39
40
41
42
43
44
45HWFET
Conv. HEV
0%
2.5%0%
2.5%
3) SI/HCCI No storage
4) SI/HCCI Fil l & deplete
26
27
28
29
US06Conv. HEV
0%
2.5%
0%
2.5%
1) 2) 3) 4) 1) 2) 3) 4)CS+0
+20
+40
+60
TailpipeNO
x[m
g/mi]
1) 2) 3) 4) 1) 2) 3) 4)0
20
40
60
1) 2) 3) 4) 1) 2) 3) 4)0
20
40
60
Drive Cycle Results
• LongHCCIresidencetimeresultsinlargeNOxquantities
• SignificanttailpipeNOx
LEVIII SULEV20 & EPA Tier 3 Bin20: 20 mg/mi NOx + NMOG (incl. cold start)
Powertrain Control (38)/50
HCCI Operation with mild-HEV
1000 1500 2000 2500 3000
0
5
10
15
HCCI
Conventional SI/HCCI I
Engine Speed ωe [RPM]
SI min
SI max
BMEP
[bar]
1000 1500 2000 2500 3000
HEV SI/HCCI IV
Engine Speed ωe [RPM]
Tim
e [%
]
0.0001
0.001
0.01
0.1
1
10
FTP75
• ReductioninengineoperationrightaboveandbelowHCCIregime
Powertrain Control (39)/50
We…Ø AFRislowØ EfficiencybenefitsdiminishØ NOx is“high”
Ø BreakthroughsoccuranywayØ Depletionisexpensive
• usedaTWCwithgenerousO2-storagetopreventNOxbreakthroughs
• pushedHCCItohigherloads
Ø Reduceregimetolowload
Ø ReducesizeofO2-storage
Bigger always better?
*Nueschetal.,Mild HEV with Multimode Combustion:Benefits of a Small Oxygen Storage,IFAC-AAC2016
Powertrain Control (40)/50
FRVVT
VVLGDI TRBDS-1
TRBDS-2
TRBDS-3
DIESEL
HEV
xEV MPGe(estimated)
2025 Target
Technology Cost Effectiveness
?
-- Highly Diluted e/iEGR-- Stoichiometric (TWC)-- Spark Assisted HCCI (SACI)
High CV and misfires areChallenges!!
Powertrain Control (41)/50
SparkAssistedCompression Ignition
Powertrain Control (42)/50
SACI combustion: Random High CV
Powertrain Control (43)/50
Spark Ignition at High DilutionRandom High CV
The Cyclic Variability (CV) in spark ignition was fitted (brute force) but
it can also be modeled using kernel initiation physics!!
(ASME-ICEF2016)
H.Lian, et al: “Prediction of Early Flame Burning Velocity with High Exhaust Gas Recirculation (EGR) and Spark Advance, ASME-ICEF2016-9476
Implication:Control SI combustion at the limits of high EGR dilution (misfires).
Powertrain Control (44)/50
Several factors reduce previously stated SI/HCCI fuel economy benefits. Many opportunities ahead:1. Spark Assisted HCCI (Stoichiometric extension at high load)2. Mode switches with two valve lifts3. Some NOx aftertreatment
Results• Highlighted in 2014 DOE Merit Review and 2015 NRC Report
Highlights the importance of comprehensive system analysis when evaluating advanced engine concepts.
Contributions & Lessons Learnt
Powertrain Control (45)/50
[41] P. Gorzelic, et al, “A low-order adaptive engine model for SI-HCCI mode transition controlapplications with cam switching strategies”, International Journal of Engine Research, June 2015. DOI: 10.1177/1468087415585016[40] S. Nüesch, et al, “Accounting for Combustion Mode Switch Dynamics andFuel Penalties in Drive Cycle Fuel Economy”, International Journal of Engine Research, May 2015. [39] J. Larimore, et al, “Adaptive Control of a Recompression Four-Cylinder Engine”, IEEE Trans on Control Systems Technology, Mar 2015, DOI: 10.1109/ TCST.2015.2402235[38] S. Nüesch, et al, "Fuel Economy of a Multimode Combustion Engine with Three-Way Catalytic Converter", ASME Journal of Dynamic Systems, Measurement, and Control, v 137, i 5, p 051007, [37] S. Jade, et al. Controlled load and speed transitions in a multicylinder recompression hcci engine. IEEE Trans on Control Systems Techn, September 2014. [36] E. Hellström at al. Reducing cyclic variability while regulating combustion phasing in a four-cylinder hcciengine. IEEE Trans on Control Systems Tech, May 2014. [34] P. Gorzelic et alA low-order hcci model extended to capture si-hcci mode transition data with two-stage cam switching. In ASME Dynamic Systems and Control Conference (DSCC), San Antonio, October [33] E. Hellström et al. A linear least-squares algorithm for double-wiebe functions applied to spark-assisted compression ignition. Journal of Engineering for Gas Turbines and Power, 136(9), 2014. [ bi[32] J Larimore et al. Real-time internal residual mass estimation for combustion with high cyclic variability. International J of Engine Research, Cyclic Dispersion Special Issue, 2014. [ bib | DOI ][31] S Nüesch et al. Mode switches among si, saci, and hcci combustion and their influence on drive cycle fuel economy. In in Proceedings of American Control Conference (ACC) 4[30] S Nüesch et al. Methodology to evaluate the fuel economy of a multimode combustion engine with three-way catalytic converter. In ASME Dynamic Systems and Control Conference (DSCC), San Antonio, October 2014, DSCC2014[29] Sa P. Nüesch et al. Methodology to evaluate the fuel economy of a multimode combustion engine with three-way catalytic converter. Journal of Dynamic Systems Measurement and Control, 137(5), 2014. [ bib | DOI ][28] E. Hellström et al. Cyclic variability and dynamical instabilities in autoignition engines with high residuals. IEEE Transactions on Control Systems Technology, 21(5):1527[27] E. Hellström et al. A linear least-squares algorithm for double-wiebe functions applied to spark-assisted compression ignition. In ASME 2013 Internal Combustion Engine Division Fall Technical Confe[26] S. Jade et al Enabling large load transitions on multicylinder recompression hcciengines using fuel governors. In in Proc. American Control Conference, pages 4423[25] J. Larimore et al. 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Thanks toJason Martz, Huan Lian, Niket Prakash, Rasoul Salehi, Erik HellstromShyam Jade, Jacob Larimore, Sandro Nuesch, Pat Gorzelic (UMICH)
Dan Hussey, David Jacobson (NIST),
National Science FoundationUS Department of Energy,
ARPA-E,US Army
with Bosch, Daimler, Ford, Toyota
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