Denver, May 15th, 2015
Powertrain Control and
Optimization for Future Fuel
Efficiency
Dr. Dean Tomazic
EVP & CTO
FEV North America Inc.
Intersection of Powertrain Innovation for Improving Future
Vehicle Fuel Efficiency and Connected Autonomous Vehicles
© by FEV – all rights reserved. Confidential – no passing on to third parties
Powertrain Control and Optimization for Future Fuel Efficiency
Agenda
2
1. Introduction
2. Potential of Powertrain Technologies
3. Potential of Vehicle Connectivity
4. Summary and Outlook
5. Discussion
© by FEV – all rights reserved. Confidential – no passing on to third parties
Powertrain Control and Optimization for Future Fuel Efficiency
Key Drivers
3
Fuel Economy and CO2 Emissions Downsizing, Downspeeding, GTDI, Friction Reduction, Combustion Optimization, etc.
Fuels Increased Share of Biofuels (e.g., Ethanol (Corn, Algae, Cellulosic), Biodiesel, CNG, etc.)
Reliability and Affordability TCO for Consumer
Emissions SULEV Average w/ Stoichiometric and (Stratified) Lean-Burn Combustion Systems
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U.S. – Passenger Cars and Light Trucks (GVW < 6,000lbs)
Source: Delphi, FEV Research
2005 06 07 08 09 2010 11 12 13 14 2015 16 17 18 19 2020 21 22 23 24 2025
Fuel mpg
CO2 g/mi
NOx g/mi
CO g/mi
PM g/mi
NOx
g/mi
CO g/mi
PM g/mi
PC: 33.8 39.5
LT: 25.7 28.8
From 0.2 (Bin 8) - 0.02 (Bin 2) Phase-In
Tier II
U.S.
Federal
California
Fuel
Economy
U.S. CAFE Standards
PC 27.5mpg / LT 22.2 mpg
Tier III – Phase
In
0.02 (Bin 7-8) - 0.01 (Bin 1-6)
4.2 (Bin 5-8) - 2.1 (Bin 2-4)
0.07 (LEV, ULEV) - 0.02 (SULEV) Combined NMOG&NOx limit ramp down
4.2 (LEV), 2.1 (ULEV), 1.0 (SULEV)
0.01
PM ramp down
Tier III
0.07g/mi NOx fleet average
Phase-In
LEV II LEV III – Phase In
Durability Increase to 150k mi
+ 3 new low emission categories
SULEV-level
emission average
FE I FE 2
Combined Fleet Average
PC: 5% p.a./LT: 3.5%-5%p.a. 35.5 54.5
PC/LD1: 323 205
LD2/MDPV: 439 332
California AB 1493
PC: 5% p.a./LT: 3.5%-5%p.a. 163
Coordinated Approach Minimum ZEV Requirements:
MY 15-17: 14%, MY18+: 16%
0.03 NMOG+NOx
0.003
NHTSA
EPA
0.03 NMOG+NOx
0.003
1.0
LEV III
CO limit ramp down
0.001
Combined NMOG&NOx limit ramp down
CO limit ramp down 1.0
Tier III
emission average
PM ramp down
250
Powertrain Control and Optimization for Future Fuel Efficiency
U.S. Emissions, FE and CO2 Legislation
© by FEV – all rights reserved. Confidential – no passing on to third parties
Powertrain Control and Optimization for Future Fuel Efficiency
Agenda
5
1. Introduction
2. Potential of Powertrain Technologies
3. Potential of Vehicle Connectivity
4. Summary and Outlook
5. Discussion
© by FEV – all rights reserved. Confidential – no passing on to third parties 6
Example:
Three-Cylinder GTDI
• Best in class BSFC
• Variable valve lift
• Friction optimized
• State-of-the-art combustion
• Optimized air and exhaust
management
norm. to calor. val.=42.5 MJ/kg
- SI engines- Production state- Model year > 1997
Brake Specific Fuel Consumption
2000 rpm / BMEP = 2 bar
BS
FC
/ (
g/k
Wh)
260
280
300
320
340
360
380
400
420
440
460
480
Engine displacement / cm³
0 1000 2000 3000 4000 5000 6000
Scatter bandFEV
Friction optimized + VVL
Benchmark
Friction optimized
Friction optimized + CVVL + Miller
Scatterband includes CDA
B
S
F
C
BS
FC
/ (
g/k
Wh)
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Gasoline Engines
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eccentric lever
support rod
(mass forces)
support piston
(mass forces)
support rod
(gas forces)
shift valve
check valve
check valve
Working Principle:
support piston
(gas forces)
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Variable Compression Ratio (VCR)
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Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Variable Compression Ratio (VCR)
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0
20
40
60
80
100
120
140
160
180
200
220
0
40
80
120
160
200
0 200 400 600 800 1000 12000
350
700
1050
1400
1750
2100
2450
CO
2 e
mis
sio
ns /
g/k
m
Vehic
le s
peed (
NE
DC
) /
km
/h
Vehicle class D - large cars
Vehicle class E - executive cars
Vehicle class J - SUV
Fuel consumption simulation
1.8 l 4-cyl TGDI engine
RON 95, CR = 9.3
RON 102, CR =11.5
Cum
ula
ted C
O2 e
mis
sio
ns /
g
Time / s
Vehicle CO2 emissions can be reduced by ~ 3 – 5 % with high octane fuels and
adapted engines with increased compression ratio
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – VCR and RON Potential
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C1/Port #2 C2/Port #4
360 450 540 630 720-3
-2
-1
0
1
2
690 700 710 720-1.0
-0.8
-0.6
-0.4
-0.2
0.0
Chrysler Voyager
6000 rpm, WOT
port TC 1
port TC 2
port TC 3
port TC 4
crank angle/ °
Tum
ble
/ -
6000 WOT
crank angle/ °
360 450 540 630 720-3
-2
-1
0
1
2
690 700 710 720-1.0
-0.8
-0.6
-0.4
-0.2
0.0
Chrysler Voyager
6000 rpm, WOT
port TC 1
port TC 2
port TC 3
port TC 4
crank angle/ °
Tum
ble
/ -
6000 WOT
crank angle/ °
C1/Port #1
C1/Port #2
C1/Port #3
C2/Port #4
Decreased mass
flow over the
backside of the
valve (better
separation of the
flow)
@460 °CA
High mass flow
over front side
following head
contour
Robust
tumble
structure
0 150 [m/s]
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Combustion System Development (CMD Process)
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Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Closed Loop Combustion Control (CLCC)
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Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Closed Loop Combustion Control (CLCC)
US06 - Combustion control effect on engine out
emissions
0.680.46
3.16
0.67 0.53
3.86
0.0
0.8
1.6
2.4
3.2
4.0
4.8
NOx THC CO
Em
iss
ion
s [
g/m
ile
] Combustion control ON
BASE - No combustion control
Fuel Economy [miles/gallon]
29.09
28.02
26.0
26.5
27.0
27.5
28.0
28.5
29.0
29.5
30.0
FC [mpg]
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FTP75 and US06 are more wide spread compared to NEDC.
The WLTP is closer to US cycles.
Pow
er
[kW
]
-60
-40
-20
0
20
40
60
80
100
120
NEDC
Pow
er
[kW
]
-60
-40
-20
0
20
40
60
80
100
120
FTP75
Pow
er
[kW
]
-60
-40
-20
0
20
40
60
80
100
120
Engine Speed [rpm]
500 1000 1500 2000 2500 3000 3500
WLTPP
ow
er
[kW
]
-60
-40
-20
0
20
40
60
80
100
120
Engine Speed [rpm]
500 1000 1500 2000 2500 3000 3500
US06
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Standard Test Cycles vs. Real World
Real
World
Driving?
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Vehicle Emission Testing: FTP 75 C/H, Exhaust Temperatures
3.0L, Stratified Lean 3.0L, Turbo DI
[de
g C
]
0
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
Time [s]
0 60 120 180 240 300 360 420 480 540 600
Exhaust Port, Turbine Inlet Temperatures
Turbine Inlet Temp, Bank 1 (3.0L turbo DI) Turbine Inlet Temp, Bank 2 (3.0L turbo DI) Exhaust Port 1 Exhaust Port 2 Exhaust Port 3 Exhaust Port 4 Exhaust Port 5 Exhaust Port 6
1st stratified operation: 265 sec.
Vehicle Emission Testing: FTP 75 C/H, Exhaust Temperatures
3.0L, Stratified Lean 3.0L, Turbo DI
[de
g C
]
0
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
Time [s]
0 60 120 180 240 300 360 420 480 540 600
Exhaust Port, Turbine Inlet Temperatures
Turbine Inlet Temp, Bank 1 (3.0L turbo DI) Turbine Inlet Temp, Bank 2 (3.0L turbo DI) Exhaust Port 1 Exhaust Port 2 Exhaust Port 3 Exhaust Port 4 Exhaust Port 5 Exhaust Port 6
1st stratified operation: 265 sec.
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – FTP-75 Exhaust Gas Temperatures (Gasoline)
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2.3L PFI, T/C - Tier 2, Bin 5 / LEV-II ULEV3.0L Stratified Lean - Euro 42.4L GDI, N/A - Tier 2, Bin 5 / LEV-II ULEV2.0L GTDI, T/C - Tier 2, Bin 5 / LEV-II ULEV1.8L PFI, N/A - Tier 2, Bin 5 / LEV-II ULEV
[º C
]
0
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
Time [s]
-5 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120
Close-Coupled Catalyst Temperatures (Midbed)
3.0L Stratified Lean CCC (front bank) 2.4L GDI, N/A 2.0L GTDI, T/C 2.3L PFI, T/C CCC Brick 1 1.8L PFI, N/A
Vehicle Cold Start Testing: FTP 75 C/H, 25º C
Dotted - InletSolid - Midbed
2007 2.3L PFI, T/C - CCC+UBC2008 3.0L Stratified Lean - CCC+UBC2011 2.4L GDI, N/A - UBC Only2011 2.0L GTDI, T/C - UBC Only2012 1.8L PFI, N/A - UBC Only
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Cold Start Exhaust Gas Temperatures (Gasoline)
Factor 10 !!!
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Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Lambda Control (Gasoline)
Lambda Control Conclusion
Lambda controller typically consists
of a feed forward controller
combined with a feedback loop
control principle
As the closed loop part is driven by
deviation, an error has to occur
before corrective measures are
taken
The integrated absolute deviation
between target lambda and actual
lambda shows performance of the
lambda controller, ideal this would
be zero
Better open loop control could
reduce the CO2 emissions
Sp
eed
[km
/h]
0
25
50
75
100
time [s]
0 100 200 300 400 500 600
Inte
gra
ted
lam
bd
a d
iff.
[-]
075
150225300375450525600675750825
lam
bd
a [
-]
0.7
0.8
0.9
1.0
1.1
1.2
1.3
time [s]
0 50 100 150 200 250 300 350 400 450 500 550
lam
bd
a [
-]
0.7
0.8
0.9
1.0
1.1
1.2
1.3
time [s]
340 350 360 370
actual lambda target lambda
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Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Thermal Management Options (Gasoline)
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… Battery Electric
Vehicles
Micro
Hybrid
Mild Hybrid Full Hybrid Plug-In Hybrid
Hybrid Electric Vehicles
Gear Box
Fuel Tank
Conventional
Vehicles
Transmission Impact
Increasing electrical power
Start-Stop & Intelligent Energy Management
+ Kinetic Energy Recovery & Boosting
+ Electric Drive
+ Plug-In/REX
Complexity Transmission Complexity ICE
Downsizing
Diesel and
Gasoline
NA Engine, Atkinson Battery size/price CO2-Emissions
Gasoline Atkinson Gasoline NA
Battery
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends - Hybridization
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Introduction to Waste-Heat Recovery Technologies
Thermoelectric
Generator (TEG) Turbocompound
Organic Rankine
Cycle (ORC)
The Rankine Cycle
is a thermodynamic
cycle that converts
heat into work
The heat is
supplied externally
to a closed loop,
which uses water or
another fluid as
working fluid.
A turbine recovers
energy from the
exhaust gas
Three main forms:
Mechanical
Turbocompound,
Electric
turbocharger,
Turbogenerator
Temperature
difference between
the hot and cold
surfaces of the
thermoelectric
module(s)
generates electricity
using the Seebeck
Effect
Powertrain Control and Optimization for Future Fuel Efficiency
Development Trends – Waste Heat Recovery
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Powertrain Control and Optimization for Future Fuel Efficiency
Agenda
20
1. Introduction
2. Potential of Powertrain Technologies
3. Potential of Vehicle Connectivity
4. Summary and Outlook
5. Discussion
© by FEV – all rights reserved. Confidential – no passing on to third parties 21
Powertrain Control and Optimization for Future Fuel Efficiency
Potential of Vehicle Connectivity
Potential Scenario and Benefits:
Establish intelligent connection unit/service (iCU/iCS)
Cloud services for different applications
Collection of data from various vehicles
(swarm intelligence) predictive behavior
Intelligent algorithms to combine different data
sources incl. potential updates over V2X
Added value for driver, infrastructure and society
Cloud data iCS
Smart
Driving
iCS
Smart
Logistic iCS
Smart
City
V2V
V2V
DSRC
Vehicle data
iCU iCU
LTE / 5G
Vehicle data
GPS
ECU
TCU
ESP
BMU
ADAS
GPS
ECU
TCU
ESP
VCU
Vehicle data ADAS
Source: DAF, BMW
© by FEV – all rights reserved. Confidential – no passing on to third parties
Powertrain Control and Optimization for Future Fuel Efficiency
Agenda
22
1. Introduction
2. Potential of Powertrain Technologies
3. Potential of Vehicle Connectivity
4. Summary and Outlook
5. Discussion
© by FEV – all rights reserved. Confidential – no passing on to third parties
Powertrain Control and Optimization for Future Fuel Efficiency
Summary and Outlook
23
• Significant improvement of fuel economy and emissions based on legislation
are impetuous yet mandatory.
• Engine technologies in combination with advanced controls in the field of
engines, transmissions, aftertreatment, hybridization, thermal management,
etc., offer significant potential for improvement beyond the current state-of-the-
art allowing to meet the legislated targets for 2025.
• In addition, vehicle connectivity provides additional potential which, when
properly applied, further improves vehicle fuel economy while simultaneously
improving driving comfort and vehicle/passenger safety.
• More work in the area of powertrain and vehicle connectivity is required to not
only achieve improvement in their corresponding fields but also to connect the
two with each other allowing to maximize the gain in overall vehicle fuel
economy.