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www.caeconference.com
Engine Virtual Calibration Platform Using
Physical Real-Time Integrated Models
Dr. Giulio Boccardo
Guido Giardino
Diego Zanella
www.caeconference.com 235th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Introduction
▪ Control system development within the automotive industry is evolving rapidly due to
three main drivers (in addition to the evergreen cost-reduction):
Regulatory Pressure
• Pollutants (EU6d w/ RDE)
• CO2 emissions (CAFE)
Shorter Time-to-Market
• Shorter lifecycle
• More differentiation
Control System Complexity
• Vehicle Electrification
• More DoFs
www.caeconference.com 335th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
CAE in the Control Development
▪ Virtualization of the product development process (V-Cycle) becomes mandatory,
simulation is used throughout to replace the plant (prototypes):
Functions
Specification
Controller
Design
SW Calibration, ValidationV-Cycle
HiL
SiL
MiL
• Reduced need for
(costly) experimental
tests
• Shorter lead time for
DoEs, optimizations
(scalability)
V-Cycle
Testing
Matrix
• Control system
development moved
earlier in the process
www.caeconference.com 435th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Hardware-in-the-Loop Simulations
Functions
Specification
Controller
Design
SW Calibration, ValidationV-Cycle
HiL
SiL
MiL
Vehicle Input Signals
Actuator Signals
ECU
HiL HW
Actuators
RT Simulation
FRMs
▪ HiL is a fundamental enabler for control Virtual
Calibration and Validation
→ SHORTER TIME-TO-MARKET
• HiL requires Real-Time (RT) Engine/Vehicle
plant models
→ FAST-RUNNING MODELS
www.caeconference.com 535th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Fast-Running Fully-Physical Engine ModelDetailed model: 191 volumes 0D FRM: 18 volumes
▪ GT-SUITE 1D fluid-dynamics engine models a de-facto standard in automotive industry▪ Detailed models ~50x slower than RT but can be
simplified into fully physical 0.5xRT FRMs
Tra
de-O
ff be
twee
n ac
cura
cy
and
com
puta
tiona
l effi
cien
cy
▪ RT-Capable GT-POWER FRMs still based on the very same templates and fluid-dynamic solution
→ HIGHLY PREDICTIVE
Detailed Model already
present within OEMs!
Efficient Re-Use of
Available Information
“Development and assessment of a Fully-physical 0D Fast Running Model of an E6 passenger car Diesel engine for ECU testing on a Hardware-in-the-loop system” SIA Conference, 2015, PWT - FCA
www.caeconference.com 635th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
▪ Albeit very computational efficient,
FRMs are still very accurate
▪ Predictive and highly flexible, no need
to rebuild them when changes occur
▪ Can be run in steady-state and
transient conditions
Fast-Running Fully-Physical Engine Model
10
10
10
10
10
10
10
10
101010
20
20
20
30
30
4040
2020
10
10
10
10
50
10
10
10
20
Engine Speed [RPM]
Lo
ad
[%
]
1500 2000 2500 3000 3500 4000 45000
10
20
30
40
50
60
70
80
90
100
0
5
10
15
20
25
30
35
40
45
50
Exhaust Manifold Temp
Absolute error [°C]
4
4
4
4
4
444
4
4444
8
8
8
4
4
8
812
8
4
88
Engine Speed [RPM]
Lo
ad
[%
]
1500 2000 2500 3000 3500 4000 45000
10
20
30
40
50
60
70
80
90
100
0
5
10
15
2
2
2
2
2
2
2
2
2
2
2
2
2
22 2
2
2
4
4
2
22
4
44
46
4
4
2
6
8 6
Engine Speed [RPM]
Lo
ad
[%
]
1500 2000 2500 3000 3500 4000 45000
10
20
30
40
50
60
70
80
90
100
0
5
10
15
4
4
4
4
812
4
Engine Speed [RPM]
Lo
ad
[%
]
1500 2000 2500 3000 3500 4000 45000
10
20
30
40
50
60
70
80
90
100
0
5
10
15
Turbine Inlet Pressure
Relative percentage error [%]
Air flow
Relative percentage error [%]
BSFC
Relative percentage error [%]
Average error:
2.0 %Average error:
2.1 %
Average error:
4.9 %
Average error:
10.8 °C
“Development and assessment of a Fully-physical 0D Fast Running Model of an E6 passenger car Diesel engine for ECU testing on a Hardware-in-the-loop system” SIA Conference, 2015, PWT - FCA
www.caeconference.com 735th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Simulink 3
Aftertreatment GT-RT
▪ GT-SUITE FRMs are encapsulated into Simulink I/O masks, compiled and deployed onto HiL
Hardware (e.g. dSpace). Multi-Model and Multi-Core simulations are supported:
FRMs Deployment on HiL Machines
Simulink 1
Engine GT-RT
Engine Model to Core 2
EATS Model to Core 4
HiL System Services
plus Vehicle model to
Core 1
Simulink 2
Cooling GT-RT
www.dspace.com
“Multi-Core HiL Simulation of an Integrated Engine & Cooling Model” GT-SUITE European User Conference, 2015, PWT - FCA
ECU
Actuator Signals
Sensor Signals
HiL HW
Vendors
Cooling Model
to Core 3
www.caeconference.com 835th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
The problem of Engine CalibrationDiesel Engine
Injection Strategy:
▪ 2 → 4 Auxiliary injection events
▪ 2x Parameters Ɐ Injection event
▪ Pattern Positioning (SOI)
▪ Injection pressure
→ 10 Parameters only for injection pattern
Air Management Strategy
▪ Boost Pressure
▪ EGR level and split (Dual Loop Circuit)
▪ Swirl Flap
→ 4 Parameters
TOT: 14 Parameters → 3 levels Ɐ params → ~5 millions Combinations!
TARGET:
Optimization of
emissions and fuel
consumption
VIRTUAL TEST BENCH
huge saving potentials
Engine Performance
Engine Out Emissions
Tailpipe Emissions
www.caeconference.com 935th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Online Approach (HiL)0.8x FRM: TimeStep: ~0.30 ms; Flow Volumes: ~15
▪ Coarse gas dynamic
▪ Mapped Wall Temperatures
▪ Mapped Combustion
▪ Mapped or SP Emissions
EXP Data Needed: DoE (103)
Development Time: 3-6 Months
Virtual Calibration in a Nutshell
Offline Approach (SiL)5x FRM: TimeStep: ~0.05 ms, Flow Volumes: ~100
▪ Accurate gas dynamic
▪ Wall Temperature Solvers
▪ Predictive Combustion Models
▪ Predictive Emissions Models
EXP Data Needed: Engine Maps (102)
Development Time: 1-2 Months
www.caeconference.com 1035th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Online Approach (HiL)0.8x FRM: TimeStep: ~0.30 ms; Flow Volumes: ~15
▪ Coarse gas dynamic
▪ Mapped Wall Temperatures
▪ Mapped Combustion
▪ Mapped or SP Emissions
EXP Data Needed: DoE (103)
Development Time: 3-6 Months
Virtual Calibration in a Nutshell
Offline Approach (SiL)5x FRM: TimeStep: ~0.05 ms, Flow Volumes: ~100
▪ Accurate gas dynamic
▪ Wall Temperature Solvers
▪ Predictive Combustion Models
▪ Predictive Emissions Models
EXP Data Needed: Engine Maps (102)
Development Time: 1-2 Months
www.caeconference.com 1135th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
▪ Semi Predictive Emission Models
Light-duty Truck Diesel (Euro VI)
▪ Engine Map Results
Semi-Predictive Diesel Emissions
𝑁𝑂𝑥, 𝐶𝑂, 𝐻𝐶, 𝑆𝑂𝑂𝑇 = 𝑎0 ∗ෑ
𝑘=1
𝑝
𝑥𝑘𝑎𝑘
*Percentage error bands limited to 1% absolute error
▪ 𝑥𝑘 are the independent variables
▪ 𝑎𝑘 are the coefficients, result of the
calibration process
▪ 𝑝 is the number of regressors, index
of the model complexity
www.caeconference.com 1235th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Semi-Predictive Diesel Emissions▪ Semi Predictive Emission Models
▪ Medium-size passenger car Diesel (Euro VI)
▪ Emission maps tested on different Driving Cycles
EXPERIMENTAL: Driving cycle simulation with
experimental emission map
PREDICTED: Driving cycle simulation with emission
map evaluated via SP emission model
NOx - WLTC HC - WLTC- 0.31 %
0.89 %
www.caeconference.com 1335th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Online Approach (HiL)0.8x FRM: TimeStep: ~0.30 ms; Flow Volumes: ~15
▪ Coarse gas dynamic
▪ Mapped Wall Temperatures
▪ Mapped Combustion
▪ Mapped or SP Emissions
EXP Data Needed: DoE (103)
Development Time: 3-6 Months
Virtual Calibration in a Nutshell
Offline Approach (SiL)5x FRM: TimeStep: ~0.05 ms, Flow Volumes: ~100
▪ Accurate gas dynamic
▪ Wall Temperature Solvers
▪ Predictive Combustion Models
▪ Predictive Emissions Models
EXP Data Needed: Engine Maps (102)
Development Time: 1-2 Months
www.caeconference.com 1435th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
▪ Predictive Diesel Combustion Model: DI-Pulse
▪ Phenomenological combustion model developed by GT.
▪ Designed to handle modern multi-pulse injection
▪ Multi-zone approach (3 zones per pulse)
▪ Improved thermal description of in-cylinder phenomena
▪ Improved results of emissions models
▪ Combustion rate is predicted based on injection rate &
in-cylinder conditions:
▪ Injection timings and profiles
▪ Pressure and temperature
▪ Mixture composition (fresh air, fuel, EGR/residuals)
Physical Diesel Emissions Modeling
Courtesy of Gamma Technologies
ሶ𝑚𝑎ሶ%𝐸𝐺𝑅
𝑅𝑃𝑀
𝑝𝑐𝑦𝑙𝐼𝑀𝐸𝑃𝑇𝑜𝑟𝑞𝑢𝑒…
www.caeconference.com 1535th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Physical Diesel Emissions Modeling▪ Predictive Diesel Combustion Model: DI-Pulse
Medium-size passenger car Diesel Engine (Euro VI) with predictive combustion.
“Set-up and Validation of an Integrated Engine Thermal Model in GT-SUITE for Heat Rejection Prediction” SAE Paper 2019-24-0078, PWT – Jaguar Land Rover
www.caeconference.com 1635th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
91%81%
73%
20% 10% 5%
% o
f P
oin
ts
Tolerance*
N. of OP within error bands:
*Percentage error bands limited to 10ppm absolute error
Physical Diesel Emissions Modeling▪ Predictive Diesel Emission Model: NOx
Medium-size passenger car
Diesel Engine (Euro VI) with
predictive combustion.
www.caeconference.com 1735th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Aftertreatment Modeling▪ Physical Catalyst modeling:
▪ Requires dedicate testing of a Lab-Scale reactor sample on a synthetic flow bench.
▪ Real time and fully predictive
▪ Ex: Physical Model of a SCR on Filter
Millo F., Rafigh M., Fino D., Miceli P. , Application of a global kinetic model on an SCR coated on Filter (SCR-F) catalyst for automotive applications, Fuel Volume 198
www.caeconference.com 1835th INTERNATIONAL CAE CONFERENCE AND EXHIBITION 2019, 28 - 29 October G. Boccardo - Engine Virtual Calibration Platform
Conclusions▪ Control system
development within the automotive industry is evolving rapidly towards an ever-increasing complexity.
▪ A process was identifiedwhich consents the virtualization of the engine control development andcalibration reducing the need for testing and making an extensive re-use of available resources.
▪ This process relies heavily on state-of-the-art CAE simulation of theengine gas-exchange, combustion and pollutant emission formation torealize a digital-twin of an engine test bench which can be used foronline and offline control calibration and optimization.
www.caeconference.com
THANK YOU FOR YOUR ATTENTION
Any Question?POWERTECH ENGINEERING S.R.L.
Via C. Invernizio 6, 10127 Torino, IT
www.pwt-eng.com
Giulio Boccardo
+39 011 3036481