Institute for Internal Combustion Engines and …...Institute for Internal Combustion Engines and...

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


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


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?


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


� 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.


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 %






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


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

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2

0.030.04

0.050.06

0.07

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0.0

90.1 0.11

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0.12

1000 2000 3000 4000 5000

Drehzahl [rpm]

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28002800

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35003500 3500

Abgasmassenstrom

Stickoxide

Reaction Variables

+ =

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mie

rte

La

st in

%

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2.00002.0000 2.0000

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30

Real-world driving dominated by almoststationary behaviour:±100 rpm/s & ±10 %/s � 72% of test

Speed change [rpm/s]

Load c

hange

[%/s

]


OP-specific emission target EG:

No

mie

rte

La

st

in %

0.0

10.0

20.0

30.0

40.0

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70.0

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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

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14.0000

14.000017.0000

17.0000

17.000019.0000 19.0000

30.000030.0000

1

1.1

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30

No

mie

rte

La

st

in %

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30.0

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60.0

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100.0


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5.0000

8.00008.0000

8.0000

12.0000

12.0000

12.0000

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14.0000

14.0000

14.000017.0000

17.0000

17.000019.0000 19.0000

30.000030.0000

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1.0000

1.0000

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1.1000

1.10002.0000

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3.0000

3.0000 3.0000

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5.0000

5.0000

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30

Nom

iert

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ast in

%

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5.0000

8.00008.0000

8.0000

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12.0000

12.0000

12.0000

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14.0000

14.000017.0000

17.0000

17.000019.0000 19.0000

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3.0000

3.0000

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ast in

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1.00001.0000

1.0000

19.0000

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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:


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

+ =

+ =

+ =

+ =






Office Stationary Standard ETB Active Standard ETB




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 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

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75

100

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15001500

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300037504000

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ha [

%]

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25 27.5

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Alp

ha [

%]

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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


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







Active Standard ETB







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


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


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


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


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







Active Standard ETBEngine-in-the-Loop ETB







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





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


� 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)


0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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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

� 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


0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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� 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



0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500Vhcl.Distance [m]

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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


� Interaction-Plot summarizes all tests

vmean

Vehic

lespeed

[m/s

]a

pos[m

/s2]







Active Standard ETBEngine-in-the-Loop ETBActive Standard ETB







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





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


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


� 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


Thank you for

your Attention!

Contact:Hauke Maschmeyer, M.Sc.

Website:www.verbrennungskraftmaschinen.de

Tel.: +49 6151 16-21263Fax: +49 6151 [email protected]

Institute for Internal Combustion Engines and …...Institute for Internal Combustion Engines and...

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Transcript of Institute for Internal Combustion Engines and …...Institute for Internal Combustion Engines and...