TAILPIPE EMISSION SIMULATION OF HEV’S...Surya Kiran Yadla, Dr. Andreas Balazs, Dr. Marius Böhmer Frankfurt am Main, 8th October, 2018 TAILPIPE EMISSION SIMULATION OF HEV’S USING

© by FEV – all rights reserved. Confidential – no passing on to third parties

Prepared for

European GT Conference, 2018

Surya Kiran Yadla, Dr. Andreas Balazs, Dr. Marius Böhmer

Frankfurt am Main, 8th October, 2018

TAILPIPE EMISSION SIMULATION OF HEV’S

USING GT-SUITE

Tailpipe Emission Simulation of HEV's using GT-SUITE

© by FEV – all rights reserved. Confidential – no passing on to third parties |

Agenda

Introduction

Modeling Approach

Simulation results

Summary

Surya Yadla, European GT-Conference, 2018 2


© by FEV – all rights reserved. Confidential – no passing on to third parties | 3Surya Yadla, European GT-Conference, 2018


Sales moving from Diesel to Gasoline Hybrids

Europe

Vehicle Sales / %Vehicle sales 2030 / million units

FEV POWERTRAIN FORECAST

Source: FEV

*: normalized to NEDC; **: including fossil

and alternative fuels

e-gas: gas produced by electricity from

renewable energy

Source: FEV

<95 g/km*CO2 fleet

emission: <81 g/km* <66.5 g/km*

Short-term shift

towards Gasoline

Hybrids


European Emission Roadmap for Gasoline and Hybrid Powertrains

Real Driving Emissions (RDE) and EU7

4Source: Reg. EU 427/2016; Reg. EU 646/2016; EC, Reg. 2017/1154, Reg. 2017/1151.

* may be changed according to measurement technique ** Can be avoided by an application for CF = 2.1 until 2020

1TA: Type Approval – New Types2FR: First Registration – New Vehicles

Dates valid for M1 (PKW) and N1 (NFZ < 3,5 t) Class I vehicles 1 year later has to be considered for N1 Class II and III and N2 vehicles

Euro 6d(01/20 for type approval)

Euro 6d-TEMP (09/17 for type approval)

Euro 7Euro 6b(09/14 for type approval)

2015 2016 2017 2018 2019 2020 2021 2022 Discussions ongoing, Proposals required

by parliament until 2025 latest

RD

E P

ack 4

(publis

hed 1

2/1

8)

Fu

ture

Published

Expected

PN size < 23 nm,

CFHC, CFCO2

Future RDE Update:

CFCO, λ = 1 entire map

3000 km run-in before RDE test, Power binning method

eliminated, Hybrid vehicles (PHEV) without need for

ICE operation in urban part, MAW Postprocessing

replaced by single correction factor, AES pre-approval

max. 12 months before type approval, valid for 18

months, extension only by proof that no new

technology is accessible, annual update of non-

acceptable AES; risk: competitors with Lambda = 1

Cycle

Tmod: +3 to +30 °C

Text: -2 to +35 °C

CFPN = 1.5*

Final: CFNOx = 1 + margin*

Tmod: 0 to +30 °C

Text: -7 to +35 °C

Cold start, Periodic regeneration of cyclic aftertreatment systems, Hybrid

vehicles (PHEV) 12 km with ICE in urban part, Extended documentation of

auxiliary emission strategies

RD

E P

ack 1

-3(p

ublis

hed 0

4/1

6 –

07/1

7)

Final: CFPN = 1 + margin*Monitoring

NOx, PN, CO

CFNOx = 1.43**

CO Monitoring

Future RDE requiring

gasoline hybrids with

λ = 1 in entire map

CFNOx = 2.1

Requires GPF

for gasoline &

gasoline hybrid

powertrains

Lim

its

6 x 1012 /km PN 6 x 1011 /km PN

FRFR

50 mg/km HC

500 mg/km CO

35 mg/km NOx

AES promoting

λ = 1 entire map

Euro 7 promoting

better catalysts with

faster light-off

Euro 6c

NEDC WLTP + RDE

FREuro 6c

?



Agenda

Introduction

Modeling Approach

Simulation results

Summary




Powertrain & hybrid concept definition with Real Driving Emission (RDE)

Simulation

PT-Technology Definition

Identify RDE Worst Case Cycle

Emission Modeling

Parametric Driver and Road Profile

x, y, z, …

HC

…

PN

CO2

NOX

Lo

ad

Speed

s

Ve

hic

le S

pe

ed

a, b, c, …

s

Ve

hic

le S

pe

ed

PN

x, y, z, … a, b, c, …

agressive

defensive

RDE

DoE

Vehicle simulation

Emission Sub-Models

λ TWCTCOOL …

Base Maps 90 °C, λ = 1, …

6

Hybrid

Calibration

Aftertreatment

1 2 3

Surya Yadla, European GT-Conference, 2018



Map based Modeling approach ideal for concept evaluation and Realtime

applications during early development phase

7

MODELING APPROACHES


Kinetic

TWC modelComments

Map based

modelComments

1. Measurements effort (time and

costs)LGB tests are necessary to characterize the

TWC

Measurements can be performed on

an available engine dyno

2. Calibration effort (time)Each considered reaction has to be

calibratedThree emission groups are calibrated

3. Complexity for the integration

into a vehicle model

In vehicle testing, the mixture is not

controlled like in the LGB, therefore it is

necessary to use assumptions for all the not

measured emissions (like water, H2…)

4. Simulation solver stabilityTransient cycle operations can easily lead to

solver crashVery stable methodology

5. Simulation speedNormally slower than realtime (Depends

strongly on the individual reactions)Realtime capable

6. Fidelity in predicting light-off

behaviorVery good prediction capabilities

It is not possible to investigate the

light-off of C3H6 and C3H8 separately

7. Ability to predict volume

variationsVolume variation possible only by

increasing / decreasing the length

8. Ability to predict PGM loading

variationsEach reaction rates is calibrated accordingly

to the PGM loading

Not Possible : Model requires re-

calibration with the corresponding

PGM Loading measurement data

9. Ability to predict aging

Measurements at different aging status are

necessary to investigate the correlation

between the reaction rates and the aging

status

Not Possible



Benchmarking activities at FEV for various Exhaust After-Treatment

systems helps in building up of TWC simulation models

8

SYSTEM LAYOUT OVERVIEW

- Variables to be controlled

Θ1, Θ2, Θ3 Throttle angular positions / °

, Cooling water mass flows / (kg/h)

λ & α Air fuel ratio and spark timing

𝑚1 𝑚2

- Target variables

TCat. Catalyst temperature as per the testplan

p3, p4 Pressure upstream turbine and catalyst (acc. to engine mapping)

Parallel installation of 2

intercoolers

Each throttle can

be operated

independently

Compensator embedded in

the by-pass pipe to absorb

thermal expansions /

contractions

The position of the

system can be

adapted for the

specific engine




Map based conversion Modeling for each emission group depending on

rel. air/fuel ratio, space velocity and temperature

9

CATALYST CHARACTERIZATION METHODOLOGY

Stationary measurements LGB measurements Final conversion efficiency map

The conversion efficiency of the catalyst

is measured with respect to temperature

and space velocity at the engine test

bench

LGB investigations on a similar catalyst

are used to interpolate the conversion

efficiency data measured at the test

bench

The final conversion efficiency map is

obtained combining measured and

interpolated data points

Source: FEV

# PROJECT EXAMPLE

Tem

pera

ture

in T

WC

/ °

C

Space velocity / (1/h)

TWC stationary measurements Extrapolated points

Tem

pera

ture

in T

WC

/ °

C


TWC stationary measurements

Tem

pera

ture

in T

WC

/ °

C


TCat = 200 °C; TCat = 250 °C TCat = 277 °C; TCat = 300 °C TCat = 370 °C




Realistic light-off behavior of Three Way Catalyst in GT-Suite


Source: FEV

2 seconds after 1st engine start 10 seconds after 1st engine start 150 seconds after 1st engine start

Axial discretization of catalyst brick

Temperature distribution along the catalyst

during warmup phase is used to determine

the conversion efficiency

The light – off temperature for each

individual emission group can vary and this

temperature is determined through

measurement data

For example, 10% of the catalyst has

reached its light-off temperature 10 s after

1st engine start

The SV in this case for the 10% segment is

10 times higher than the SV of the overall

catalyst

The resulting temperature and SV is used

to look-up the conversion efficiency at the

respective operating point

In the first 150 s, the complete catalyst has

reached the light-off temperature, therefore

the SV to be considered is the one of the

overall catalyst

The temperature to be considered for the

conversion efficiency determination is the

average temperature in the overall catalyst

Cat

alys

t tem

pera

ture

/ °C

TLight-off

Exhaust

gas flow

2 s

Rel. Catalyst length / -


TLight-off

Exhaust

gas flow

2 s



TLight-off

Exhaust

gas flow

2 s



10 s 10 s

150 s

Cat

alys

t tem

pera

ture

/ °C

Cat

alys

t tem

pera

ture

/ °C

0.1 1



Agenda

Introduction

Modeling Approach

Simulation results

Summary




A virtual plug-in parallel hybrid vehicle is investigated to analyze the

influence of hybridization on tailpipe emissions


INPUT DATA FOR SIMULATION

Source: FEV

Vehicle data E-Segment

PHEV

Vehicle mass used for simulation / kg 2075

Transmission 8 AT

Powertrain Architecture Parallel (P2)

Electric driving range 50 km

Specifications

Displacement / l 2.0

Rated engine power / kW 160 kW @ 5500 1/min

Rated system power / kW 240 kW

Rated torque / Nm 350 Nm @ 1500 – 4500 1/min

Rated system torque / Nm 700 Nm

# CASE STUDYTailpipe Emission Simulation of HEV's using GT-SUITE


PN

/ (#

/km

)

0·100

1·1012

2·1012

3·1012

Ve

hic

lesp

ee

d / (

km

/h)

0

50

100

150

NO

x/ (m

g/k

m)

0

25

50

75

CO

/ (g

/km

)

0.0

1.0

2.0

3.0

Time / s0 1000 2000 3000 4000 5000 6000 7000

P2 PHEV Conventional

Hybrid emission challenges in worst-case Real Driving:

2.0 L TC GDI engine in conventional vs. P2 PHEV powertrain


HYBRID EMISSIONS NEED DEDICATED CALIBRATION STRATEGIES


0PHEVDelta

mass

Conv. E-

Boost

Stop

Start

E-

Driving

1 g/km; CF = 1

60 mg/km; CF = 1

6e11 #/km; CF = 1

PHEV with up

to 10 x more

engine starts

compared to

conventional

powertrain

All results shown in charge

sustaining mode. Effect of charge

depleting mode quantified extra

Euro 6d =

Euro 7 Expectation

Euro 6d

Euro 6d

(not limited in RDE yet)

Euro 7

Expectation

Euro 7

Expectation

Vehicle: E-Segment

Transmission: 8AT

Engine: 2.0 TC GDI

Close Coupled EATS

Aged TWC & Coated GPF

Charge sustaining mode


Simulation based powertrain optimization for fast and effective

development process


FEV‘S DRIVETRAIN OPTIMIZATION TOOL: POSSIBLE APPLICATIONS

FC: Hybrid strategy optimization

Base

Optimized

Hybrid strategy

NVH: Noise limit assessment

Vehicle

Engine

Noise level

Emissions: Impact of catalyst / GPF size

Drivetrain

Optimization

Tool

ICE

Tech.

Battery

systems

Trans-

mission

Hardware

variabilities

After-

Treatment

System

E-

Machine

Hybrid

topology

Shift

strategy

Hybrid

operation

strategy

Calibration

strategyDriver

influence

ICE

Control

Strategy

Emission

limits

Env.

factorsNVH

behaviour

Boundary

conditions /

targetsFuel /

energy

cons.

targets

Drive-

ability



Model point Validation point Repetition point

Par

amet

er 2

Parameter 1 Parameter 1

FEV’s Drivetrain Optimization Tool (DOT) helps in analyzing and optimizing

the powertrain - Approach for DoE, Simulation & Optimization


TARGET: OPTIMIZATION OF HYBRID POWERTRAINS FOR CUSTOMER RELEVANT DRIVING CYCLES

Source: FEV

Parametric description of combustion engine,

powertrain and operation strategy

Variation parameter:

Engine configuration

Powertrain configuration with all

components

Mathematical Modeling and

numerical optimization

Impact of all var.

parameters on CO2 –

emissions

Consideration of

constraints, e. g.

performance

Drive cycle simulation in GT-SUITE

Different powertrain models

Simulation of customer relevant driving

cycles

Creation of DoE test plan

Variation of all parameters within defined constraints

Optimized hybrid

drivetrain for

customer relevant

operation

Time

Ve

hic

le

Sp

ee

d

CO2

DoE Model

Parameter 1

…

Parameter 2

DoE

15



Different vehicle configurations can

be simulated in various driving

cycles (conventional, HEV P0, P1,

P2, P3, P4, Plug-In)

Consideration of engine and vehicle

calibration functions in simulation

model along with the hybrid

operation strategy

Sub-models for simulating transient

thermal behavior of Engine,

transmission, E-Machines and

batteries

Dynamic driver model for either drive

cycles or Real Driving scenarios

Longitudinal dynamic simulation model for gasoline engines at FEV with a

modular architecture


TOP LEVEL OVERVIEW OF THE GT-DRIVE MODEL FOR CONVENTIONAL VEHICLE AND HEV

Source: FEV


16


Different vehicle configurations can

be simulated in various driving

cycles (conventional, HEV P0, P1,

P2, P3, P4, Plug-In)

Consideration of engine and vehicle

calibration functions in simulation

model along with the hybrid

operation strategy

Sub-models for simulating transient

thermal behavior of Engine,

transmission, E-Machines and

batteries

Dynamic driver model for either drive

cycles or Real Driving scenarios

Longitudinal dynamic simulation model for gasoline engines at FEV with a

modular architecture


TOP LEVEL OVERVIEW OF THE GT-DRIVE MODEL FOR CONVENTIONAL VEHICLE AND HEV

Source: FEV


17


Advanced thermal Modeling of the catalyst enables light-off and light-out

simulation in hybrid powertrains


THERMAL MODEL OF THE CATALYST

Source: FEV

eCat

Thermal model of the catalyst

consisting of:

Ambient air

Heat shield

Canning

Catalyst substrate

Air gap between substrate and

heater

Possibility to implement an

Electrically Heated Catalyst (EHC)

TWC sub-model layout suitable for

map based Modeling approach

Simulation of Warm up and cool

down behavior

1 19 20

Main Catalyst with

discretized elements


18


Segment of the simulated RDE

worst case cycle

Hybridization increases the degrees

of freedom for powertrain

optimization

EM boost / assist functionality can

be utilized for reduction of

emissions during critical driving

scenarios

In this case, EM boost is used not

only at higher load requests for

improving performance, but also at

cold start conditions to avoid large

emission peaks before the catalyst

reaches light off temperature

Hybrid operation strategy in combination with catalyst temperature for

optimizing cold start emissions

19

Source: FEV



WORST CASE RDE CYCLE

PN

aG

PF

/

(#/s

)

0·100

2·1011

4·1011

6·1011

Time / s50 53 56 59 62 65

Ve

hic

le s

pe

ed

/

(km

/h)

0

20

40

60

80

CO

aT

WC

/

(g/s

)

0.00

0.20

0.40

0.60

0.80

EM

po

we

r/

kW

-5

0

5

10

15

Base calibration Optimized calibration ICE On


PN

/ (#

/km

)

0·100

1·1012

2·1012

Vehic

le

speed /

(km

/h)

0

50

100

150

NO

x

/ (m

g/k

m)

0

25

50

75

100

CO

/ (g

/km

)

0

1

2

3

Time / s0 1000 2000 3000 4000 5000 6000 7000

PHEV Base PHEV Euro 6d PHEV Euro 7

Hybrid Real Driving Emissions (RDE) solutions for Euro 6d and Euro 7


HYBRID EMISSIONS NEED DEDICATED CALIBRATION STRATEGIES


Lambda

1

Larger

Coated

GPF

PHEV

Base

Load

Cap

Opt.

Injection

Strategy

Soot

Control

PHEV

Euro 6d

PHEV

Euro 7

1 g/km (CF = 1)

1.43 ∙ 60 mg/km (CF = 1.43)

1.5 ∙ 6e11 #/km (CF = 1.5)

Vehicle: E-Segment

Transmission: 8AT

Engine: 2.0 TC GDI

Close Coupled EATS

Aged TWC & Coated GPF

Charge sustaining mode

Euro 7

Expectation

Euro 6d

Euro 7

Expectation

Euro 6d

Euro 7

Expectation

Euro 6d WLTP limit


Agenda

Introduction

Modeling Approach

Simulation results

Summary




Simulation based optimization of future Powertrains shows potential for

faster and effective development of low emission concepts


KEY TAKEAWAYS

New Emission Legislation

to improve air quality

Exhaust Aftertreatment

benchmarking activities at

FEV

Simulation based RDE

development for reducing

effort and testing costs

Tailor-made solutions for

Euro 6d TEMP, Euro 7 and

beyond


Documents

TAILPIPE EMISSION SIMULATION OF HEV’S...Surya Kiran Yadla, Dr. Andreas Balazs, Dr. Marius Böhmer Frankfurt am Main, 8th October, 2018 TAILPIPE EMISSION SIMULATION OF HEV’S USING