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18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 1
Institute for Internal Combustion Engines and Powertrain Systems, TU Darmstadt
Hauke Maschmeyer, M.Sc.; Prof. Dr. techn. Christian Beidl
Methodology Approaches for Real Driving
Emissions-Development at Engine Testbeds
Extended Version will be presented at:7th International Symposium on Development Methodology14th - 15th of November, 2017
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 2
RDE
Weather
Height
Route
Traffic
Road Signals &
SignsNot repro-
ducible
Loss of Compari-son Basis
Random-ness
Vehicle & Powertrain
Concept
Driver Behaviour
Darstellung: Welt.de
Real-world Road as new Reference System -RDE is Uncertainty and Randomness
Darstellung: Auto Bild
Darstellung: fotocommunity.de
Darstellung: haeusler-automobil-gmbh.de
Darstellung: faces.ch
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 3
Conclusion: Cycle-based vs. RDE-Legislation –Loss of a Clear Target
� How can be assured that RDE is passed? � How can system-robustness be achieved?
� When is the job finished? � What are suiting RDE KPIs? What is my engineering target?
� On what basis can I compare different concepts, functions & components in order to get a valid result for RDE? � What is RDE representative? What are RDE concept-KPIs?
� How can I consider and prioritize all realworld influences without being inefficient?
� How can Over-Engineering be avoided?
� How can new RDE-approaches be integrated into existing environments?
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 4
Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 5
� Goal: Avoidance of Over-Engineering
� Analysis of existing PEMS real-world testdrive data from Data Management
� Identification of relevant OPs and OP-Changes as well as their frequencies
� Programmed with Concerto-Script
Module Real-world Statistics –Operating Point (OP)- & OP Change-Histogram
TÜV Hessen Soft
DUC Aggressiv
DUC Soft
Normalized Speed
Norm
aliz
ed
Laod
Norm
aliz
ed
Laod
Normalized Speed
TÜV Hessen Aggr.
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 6
Module Real-world Statistics –Operating Point (OP)- & OP Change-Histogram
Quantified Operating Point Histogram:� Histogram for time and distance� Specific for powertrain concept
� In this case analysis of:� 92 PEMS tests (warm & cold)� 4 routes & 2 vehicles (B- & C-Class)� 3 drivers
Normalized Speed
Norm
aliz
ed
Laod
Normalized Speed
Norm
aliz
ed
Load
Speed change [rpm/s]
Load c
hange
[%/s
]
Time Share in %
Distance Share in %
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 7
Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office Stationary Standard ETB
Stationary ValidationGoal: Assurance of stationary emission conformity
Concept: Assessment of stationary emission behaviour considering concept-specific OP frequencies
Result: OP-specific RDE result and Homologation estimation
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 8
Goal: Assurance of stationary emission conformity
� Stationary map calibration and measurement of all necessary n/alpha-maps
� Real-world-Statistics Module provides for vehicle / engine-specific OP frequency for calculations
� OP-specific emission target EG
� RDE test drive / homologation estimation with stationary emission maps
Module Stationary Validation –What is the Engineering Target for stationary RDE Validation?
� Stationary behaviour as comparison basis for subsequent Module Dynamic Validation
„Erfüllungsgrad“ EG = Result / Limit
(Goal: EG<=1):Reaktionsgrößen:
1000 2000 3000 4000 5000
Drehzahl
Alp
ha [
%]
0
25
50
75
100
0.01
0.01 0.010.01
0.02
0.0
2
0.030.04
0.050.06
0.07
0.08
0.0
90.1 0.11
0.12
0.12
1000 2000 3000 4000 5000
Drehzahl [rpm]
0 0 0 0 0 0 0 00 0
0
350
350
350
700
700
1050
1050
1400
1400
1750
1750
1750
2100
2100
2450
2450
28002800
2800
3150
35003500 3500
Abgasmassenstrom
Stickoxide
Reaction Variables
+ =
No
mie
rte
La
st in
%
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Normierte Drehzahl in %
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
1.0000 1.0000 1.00001.1000 1.1000 1.1000
2.00002.0000 2.0000
3.00003.0000
3.0000
5.0000
5.0000
5.0000
5.0000
8.0000
8.0000
8.0000
8.00008.0000
12.0000
12.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.1000
1.1000
1.1000
1.1000
1.1000
2.0000
2.0000
2.0000
2.00002.0000
2.0000
2.0000
2.0000
2.0000
2.0000
2.0000
3.0000
3.0000
3.0000
3.00003.0000
3.0000
3.0000
5.0000
5.0000
5.0000
5.0000 5.0000
8.0000
8.0000 8.0000
12.0000
12.000012.0000
14.0000
14.000014.0000
17.0000
17.000017.0000
19.0000
19.000019.0000
30.0000
30.0000
30.0000
30.0000
30.0000
1
1.1
2
3
5
8
12
14
17
19
30
Real-world driving dominated by almoststationary behaviour:±100 rpm/s & ±10 %/s � 72% of test
Speed change [rpm/s]
Load c
hange
[%/s
]
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 9
OP-specific emission target EG:
No
mie
rte
La
st
in %
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Normierte Drehzahl in %
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
5.0000
8.00008.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.000017.0000
17.0000
17.000019.0000 19.0000
30.000030.0000
5.0000
8.00008.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.000017.0000
17.0000
17.000019.0000 19.0000
30.000030.0000
1
1.1
2
3
5
8
12
14
17
19
30
No
mie
rte
La
st
in %
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Normierte Drehzahl in %
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
5.0000
8.00008.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.000017.0000
17.0000
17.000019.0000 19.0000
30.000030.0000
1.0000
1.0000
1.0000
1.1000
1.1000
1.10002.0000
2.0000
2.0000
2.0000
2.0000
3.0000
3.0000
3.0000
3.0000 3.0000
5.0000
5.0000
5.0000
8.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.0000
17.0000
17.0000
17.0000
19.0000
1
1.1
2
3
5
8
12
14
17
19
30
Nom
iert
e L
ast in
%
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Normierte Drehzahl in %
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
5.0000
8.00008.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.000017.0000
17.0000
17.000019.0000 19.0000
30.000030.0000
3.0000
3.0000
3.0000
3.0000
5.0000
5.0000
5.0000
8.00008.0000
8.0000
8.0000
8.000012.0000
12.0000
12.0000
12.000012.0000
14.0000
14.0000
14.0000
14.0000
14.0000
17.0000
17.0000
17.0000
19.0000
19.0000
19.0000
30.0000 30.0000
1.0000
1.00001.1000
1.1000
2.0000
2.0000
2.0000
2.0000
1
1.1
2
3
5
8
12
14
17
19
30
Nom
iert
e L
ast in
%
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Normierte Drehzahl in %
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
5.0000
8.00008.0000
8.0000
12.0000
12.0000
12.0000
12.0000
14.0000
14.0000
14.000017.0000
17.0000
17.000019.0000 19.0000
30.000030.0000
14.0000
17.0000
12.0000
8.0000
2.0000 2.0000
2.0000
2.0000
2.0000
3.0000
3.0000
3.00003.0000 3.0000 5.0000
5.0000
1.1000
1.1000
1.1000
1.1000
1.1000
1.0000
1.0000
1.00001.0000
1.0000
19.0000
1
1.1
2
3
5
8
12
14
17
19
30
Module Stationary Validation –Stationary Behaviour Compared to RDE Limits in g/km
Norm
alized L
oad [
%]
Norm
alized L
oad [
%]
Norm
alized L
oad [
%]
Norm
alized L
oad [
%]
Normalized Speed [%] Normalized Speed [%]
Normalized Speed [%]Normalized Speed [%]
NO
x
TH
CCO
CO
2
1
1.1
2
3
5
8
12
14
17
19
30
EG:
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 10
Module Stationary Validation –Stationary Behaviour Compared to RDE Limits in g/km
Stationary RDE-Prognosis:� Critical EG-operating points might be compensated with uncritical ones
� Prognosis needed � EG_stat_prog = RDE histogram based weighted mean value
� basically traditional “cycle” estimation
� Goal: EG_stat_prog <= 1
EG_stat_prog:CO=23,4
EG_stat_prog:THC=1,8
EG_stat_prog:NOx=1,1
EG_stat_prog:CO2=6,0
+ =
+ =
+ =
+ =
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 11
Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office Stationary Standard ETB Active Standard ETB
Stationary ValidationGoal: Assurance of stationary emission conformity
Concept: Assessment of stationary emission behaviour considering concept-specific OP frequencies
Result: OP-specific RDE result and Homologation estimation
Legislative Cycle Validation / EstimationGoal: Deduction of RDE Post-processing parameters & Transient RDE KPI
Concept: Comparison of stationary emission estimation vs. measured data
Result: RDE KPI for Transient Robustness & Post-processing parameters
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 12
Transient OPs used for calculation of stationary map signals:
� Emissions and State Signals
� Also used for CO2-Estimation
Module Legislative Cycle Validation / Estimation -Generation of Quasi-stationary Signals
1000 2000 3000 4000 5000Drehzahl
Alp
ha [
%]
0
25
50
75
100
250
250
500
500
750
1000
1250 12501500
15001500
1750 1750
17502000 20002000
2250 2250
25002750
300037504000
1000
2000
3000
4000
Alp
ha [
%]
0
25
50
75
100
-2.5
0
0
2.5
5
5
7.5
7.5
10
10
12.5
12.5
15
15
17.5
17.5
20
20
22.5
25 27.5
27.5
27.5
30
30 30
32.5
32.5 32.5
3537.50
10
20
30
Alp
ha [
%]
0
20
40
60
80
100
0.750.8
0.8
5
0.85
0.9
0.9
0.9
0.95
0.9
5
0.95
1
11
1
1 1
1
1
1.051.11.151.21.251.31.351.41.451.5 1.51.55 1.551.6 1.6 1.6 1.6 1.6 1.6 1.61.65
0.9
1.05
1.2
1.35
1.5
Lambda [-]
iga_igc [°KW]
THC vKat [ppm]
n, alpha
� Hypothesis: Usually in transient operation the engine is not “cleaner” than during stationary behaviour
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 13
Goal: Deduction of RDE Post-processing Parameters & Transient RDE KPIs
� Measurement of RDE-Reference Test (e.g. Most-Relevant-Test of prior project) & WLTC for concept comparison
� Idea: high emission OPs might be neglectable due to few occurences
� Additional map based deduction of their quasi-stationary time dependent signals
� Difference between stationary emission estimation vs. measured data describestransient engine robustness
Module Legislative Cycle Validation / Estimation –Quasi-stationary Simulation for KPI Determination
Outcome: RDE KPIs for Comparisons
� EGstat = EMstat / Limit
� important RDE KPI
� Summary of stationary engine behaviour
� EGdyn=EMdyn/ EMstat� RDE KPI for transient robustness
� Summary of transient engine behavior
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 14
Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office Stationary Standard ETB Active Standard ETB
Active Standard ETB
Stationary ValidationGoal: Assurance of stationary emission conformity
Concept: Assessment of stationary emission behaviour considering concept-specific OP frequencies
Result: OP-specific RDE result and Homologation estimation
Legislative Cycle Validation / EstimationGoal: Deduction of RDE Post-processing parameters & Transient RDE KPI
Concept: Comparison of stationary emission estimation vs. measured data
Result: RDE KPI for Transient Robustness & Post-processing parameters
Transient ValidationGoal: Influence Assessment of transients and states on engine emission behaviour
Concept: DoE-based analysis of OP-ramps for different engine states
Result: Identified critical ramps for engine concept and corresponding technical cause
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 15
Module Transient Validation –Transient Map Analysis in early Development Phase
Advantages:� Systematic / holistic� Concept-specific / Individual� Applicable on standard engine testbeds� Automatable & Reproducible
Disadvantages:� No direct link to RDE Legislation� Risk of Over-Engineering
Goal: Detailed influence assessment of transients and states on engine emission behaviour
� Robust RDE engine concept independent of vehicle basis
Concept:� DoE-based analysis of OP-ramps for different
engine states
� If ICE is “clean” in transient behavior:
� no RDE Problems independent of vehicle type,
road, driver behaviour …
Load in %
Speed in r
pm
Time in s
DoE-based variation of:� Starting point & gradient of speed� Starting point & gradient of load� Coolant & oil temperature
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 16
Module Transient Validation -Difference to Quasi-stationary Signals as Transient Identification
� DoE-based measurement of average difference of transient to quasi-stationary emission behaviour [g/s]
� Ramp time-signal converted to ramp KPI in Concerto post-processing script
� DoE-based modeling of differences dependent on ramp parameters
measurement of average difference between transientand quasi-stationarybehaviour
Conditioning systems needed
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 17
Choice of RDE critical Transients –Assessment of Concept-Specifc RDE Relevance
Statistic Relevance:
Identification of remarkable ramps
� Difference in mg/s transient vs. stationary > 0
Concept-specificassessment of statistic relevance
� Histogram-classification� Calculation of ramp weight
G using individual ramp and OP frequencies
Ramp prioritization (for furtherdevelopment)
� Pollutant specific ramp weight
� Global worst case transient
Most-Relevant-Ramp:
� high EM difference & � high statistic relevance
CO Ramp Weight GCO
Most-Relevant-Ramp time signal used for following optimization and technical cause identification
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 18
Choice of RDE critical Transients –Identification of Technical Causes in Time Domain
Ramp 138: CO_dynamic=160 g/km, CO_stationary=35 g/km
Visual comparison of quasi-stationary andtransient state signalsallow analysis on cause of differences
16
11
7,5
4
0,86
0,79
85
53
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 19
Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office Stationary Standard ETB Active Standard ETB
Active Standard ETBEngine-in-the-Loop ETB
Stationary ValidationGoal: Assurance of stationary emission conformity
Concept: Assessment of stationary emission behaviour considering concept-specific OP frequencies
Result: OP-specific RDE result and Homologation estimation
Legislative Cycle Validation / EstimationGoal: Deduction of RDE Post-processing parameters & Transient RDE KPI
Concept: Comparison of stationary emission estimation vs. measured data
Result: RDE KPI for Transient Robustness & Post-processing parameters
RDE Sensitivity AnalysisGoal: Detection of vehicle individual challenges
Concept: Efficient assessment of all possible RDE influences on powertrain; Use of virt. RDE test drives on EiL-ETB
Result: RDE Robustness KPI; all concept-specific critical maneuvers
Transient ValidationGoal: Influence Assessment of transients and states on engine emission behaviour
Concept: DoE-based analysis of OP-ramps for different engine states
Result: Identified critical ramps for engine concept and corresponding technical cause
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 20
Set Engine Load
Testbed Interface
Module RDE Sensitivity Analysis –X-in-the-Loop RDE Tests on Engine-Testbeds with RDE-Module
Testbed Automation System
Meas. Torque
Realtime System:
Real Driving Simulation Module
Set ICE Throttle
Set ICE Speed
ICE Dyno
Driver Model
3d Environment Model
Vehicle Model
Signals
Desired Cruising Speed
Road & Environment
Sp
eed
lim
itati
on
s
Shifting,
Pedalry &
SteeringVehicle Speed
Forces Resistances & Information
Traffic Signs & Objects
Automatable, reproducible & emission measurement Virtual real-world tests, flexible, holistic
� Goal: Identification of vehicle-specific challenges & engineering targets
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 21
� Powertrain (real, virtual) remains unchanged
� Driving scenario parameters varied for model-based validation of powertrain:� Driver
� Vehicle
� Environment
� Tested parameter intervals are concept-specific based on Module Real-world Statistics
� DoE-Design for efficient testing and optimized modeling
� Measurement of pollutant emissions for each segment and whole test
Module RDE Sensitivity Analysis –Definition of RDE relevant Variation Parameters
Exemplary RDE relevant variation parameters:� Max. longitudinal acceleration� Max. lateral acceleration� Desired driver speed� Road inclination & decline� Curve radius and angle� Stop time � cw-value� Additional vehicle load
(Source: MTZ 10/2016)
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 22
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
Module RDE Sensitivity Analysis –From Time Domain to Interaction-Plot
� Each Point in Plot represents whole test in time domain
� Time based signals (e.g. emissions) is summed upby mean value
VEHICLE Comparison:
CO
2
Add. Load =350 kg
Add. Load =0 kg
Torq
ue
[Nm
]
carload
vmean
alat_mean
apos_mean
?
� Most critical tests identified
Large vehicleSmall vehicle
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 23
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
Module RDE Sensitivity Analysis –From Time Domain to Interaction-Plot
� Each Point in Plot represents whole test in time domain
� Time based signals (e.g. emissions) is summed upby mean value
VEHICLE Comparison:
CO
2
Add. Load =350 kg
Add. Load =0 kg
Torq
ue
[Nm
]
carload
vmean
alat_mean
apos_mean
If driver doesn‘t accelerate, additional load is not so critical
� Most critical tests identified
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 24
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
-400
-350
-300
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
350
400
450
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]
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Module RDE Sensitivity Analysis –From Time Domain to Interaction-Plot
CO
2
carload
alat_mean
apos_mean
DRIVER Comparison:
apos_max =7apos_mean=0,64
apos_max =1apos_mean=0,04
vdesired =130vmean =52,5
vdesired =30vmean =27
� Powertrain is evaluated for all vehicles, drivers and roads
� Most critical tests identified
� Interaction-Plot summarizes all tests
vmean
Vehic
lespeed
[m/s
]a
pos[m
/s2]
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Overview Tasks / Use-Cases for RDE –6 Methodology Approaches for RDE Development on ETBs
Real-world StatisticsGoal: Avoidance of Over-Engineering
Concept: Concept-specific statistcs of realworlddata (virt. & real)
Result: RDE representative operating points &transients
Office Stationary Standard ETB Active Standard ETB
Active Standard ETBEngine-in-the-Loop ETBActive Standard ETB
Stationary ValidationGoal: Assurance of stationary emission conformity
Concept: Assessment of stationary emission behaviour considering concept-specific OP frequencies
Result: OP-specific RDE result and Homologation estimation
Legislative Cycle Validation / EstimationGoal: Deduction of RDE Post-processing parameters & Transient RDE KPI
Concept: Comparison of stationary emission estimation vs. measured data
Result: RDE KPI for Transient Robustness & Post-processing parameters
Most-Relevant-TestGoal: Condensation of gained concept-specific challenges to one RDE representative test
Concept: Merging critical test
segments or maneuvers to RDE valid test & elimination of uncritical parts
Result: (Short) RDE representative test as new comparison basis for existing engine testbeds
RDE Sensitivity AnalysisGoal: Detection of vehicle individual challenges
Concept: Efficient assessment of all possible RDE influences on powertrain; Use of virt. RDE test drives on EiL-ETB
Result: RDE Robustness KPI; all concept-specific critical maneuvers
Transient ValidationGoal: Influence Assessment of transients and states on engine emission behaviour
Concept: DoE-based analysis of OP-ramps for different engine states
Result: Identified critical ramps for engine concept and corresponding technical cause
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 26
Module Most-Relevant-Test -Generation of New RDE-Evaluation Basis / RDE Reference Test
Concept:� Development basis should be a worst-case test� � If passed, most likely every other certification test will be passed
� Test must be individual due to concept-specific challenges� Test must be fully relevant for RDE Procedure � Most-Relevant Test Scenario� Test is merged of critical test segments or maneuvers from prior modules � elimination
of uncritical parts
What street do you want to drive on and how?
� How can be assured that RDE certification is passed?
� What is the comparison basis for concepts, functions and components?
Goal: Condensation of gained concept-specific challenges to one RDE representative test
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 27
Statistics Module
Module Most-Relevant-Test -Process Structure for Generation of RDE Reference Test
Maneuver Database
Measurement Scenario Generation
Simulative Pre-testing & Legislative Relevance
Engine Characterisation on ETB
CO2
Prognosis
Simulation Environment
Most-Rele-vant Test Scenario
Raw data
Trigger-Mechanisms
Crit. Virtual Maneuvers
Data Evaluation
Generation of Most-Relevant-Test
Test Definition ready for utilization?�CO2 representative� Initial states reenacted?
Crit. Maneuvers & States fromSensitivityAnalysis
Consistent Data ManagementLiterature
Set-Point Signal Deduction
Most-Rele-vant Test Cycle
Emission critical maneuvers
Maneuvers identified as crititcal
Test Scenario Definition
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 28
� RDE is completely different from NEDC legislation
� RDE means many more influences & randomness
� � more work and uncertainty for the development
� These challenges are ideally addressed primarily on existing engine testbeds
� Therefore, 6 RDE-Methodology Modules are defined to enable as early and as much RDE development as possible
� DoE-approaches allow holistic analysis, yet are efficient
� Concept-specific statistics avoid over-engineering
Summary
18. Mai 2017 | Institute for Internal Combustion Engines and Powertrain Systems | H. Maschmeyer | 29
Thank you for
your Attention!
Contact:Hauke Maschmeyer, M.Sc.
Website:www.verbrennungskraftmaschinen.de
Tel.: +49 6151 16-21263Fax: +49 6151 [email protected]