presentation title f2018-pte-122 pte8 : powertrain

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Author, Co-author Name, Organization (Arial 23pt)

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INDIA

Theme: Disruptive Technology for Affordable and Sustainable Mobility

2-5 October, 2018

Chennai Trade Centre, India

F2018-PTE-122

PTE8 : Powertrain Technology – P2

Estimation of Turbulence Level in Spark

Ignition Engine using Experimental Data

of In-Cylinder Pressure

Sjerić Momir , Kozarac Darko, Jakoubek Mateo

University of Zagreb, Faculty of Mechanical Engineering

and Naval Architecture, Croatia

INDIA FISITA 2018

Estimation of Turbulence Level in Spark Ignition Engine

using Experimental Data of In-Cylinder Pressure

Presentation Layout

• Introduction

• Experimental Setup

• Background of Quasi-D Combustion Model

- Flame Tracking Model

- Evaluation of Flame Front Surface Area

- Turbulence Modelling

• Comparisons of Estimated/Measured Data with Cycle-Simulations

Results- Cycle - Averaged Results

- Cycle - Resolved Results: Cycle-to-Cycle Variations

• Conclusions

• Acknowledgment

F2018-PTE-122

INDIA FISITA 2018



Introduction

F2018-PTE-122

Why the in-cylinder turbulence level of IC engines is of high interest?

➢ affects the heat transfer

➢ defines the fuel/air mixing process and combustion process in CI engines

➢ influences the flame wrinkling and combustion process in SI engines

Measurement

Hot wire anemometers• only motored conditions

Laser – based methods (LDA)• extensive engine modifications• expensive equipment

Simulations Estimations

Computational Fluid Dynamics• DNS - Direct numerical simulation• LES - Large eddy simulation• RANS – Reynolds ave. Navier-Stokes

Cycle - simulations (1-D/0-D)• 0-D: no spatial discretization of

cylinder domain

accuracypredictability

computationaltime

low

high

low

high

Calculated ROHR from measured pressure profiles

+Equation of Quasi-D combustion

model

Turbulence intensity u’Particle Image Velocimetry (PIV)

INDIA FISITA 2018


using Experimental Data of In-Cylinder Pressure F2018-PTE-122

Introduction

Within the cylinder of IC engines the turbulence intensity changes:

➢ Over the cylinder volume,

➢ Over the time, during combustion period

➢ From cycle-to-cycle.

Cyclic combustion variability

averaged cycle

individual cycles

X

✓

✓Assumption that turbulence variation from cycle-to-cycle is

the most dominant effect for combustion variability

Other causes of CCV:

➢ Mixture stratification➢ Location of spark discharge➢ Variation in the shifting

amplitude and shifting direction of flame kernel

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Experimental Setup

F2018-PTE-122

Manufacturer/Engine Name Hatz 1D81

Bore 100 mm

Stroke 85 mm

Connecting Rod Length 127 mm

Compression Ratio 11.95

Intake Valve Opens / Closes 36°CA BTDC / 60°CA ABDC

Exhaust Valve Opens / Closes 54°CA BBDC / 21°CA ATDC

Engine Speed 1000, 1500, 2000, 2500, 3000 rpm

Air excess ratio 1.00

Load WOT – wide open throttle

Fuel Type Commercial gasoline (RON95)

Pressure sensor at intake pipe: AVL LP11DAIn-cylinder pressure sensor: AVL GH14DKCrank angle encoder: AVL 365c

Laboratory of IC Engines and Vehicles, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb

AVL IndiCom+

AVL IndiSmartgigabit 612

INDIA FISITA 2018



Background of Quasi-D Combustion Model

F2018-PTE-122

Flame Tracking Model

= =

==

tria

1

3

1

i,

*

jN,

,

sf

sf

1N

j i

t

actj

UZ uAn

Hdt

dmHQ

+−=

4/1

iN

2/1

N

iNit,

'13.137.4,0.1max

Lu

u

uuu

NuMetghalchi and Keck correlation

Look-up tables used in 3D-CFD

eth triangl−j

1 2

3

1t,u 2t,u

3t,u

*

jN,A

Flameorigin

Part of smooth (laminar) flame front entrains the

fresh mixture by the (local) turbulent flame speed

.

*

jN,A

it,u

Turbulent flame speed (Frolov at al. 2015):

Frontal combustion:

External evaluation

Input: CAD model

surface mesh

Icosahedron subdivision of unit sphere

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F2018-PTE-122

Evaluation of Flame Front Surface Area

INDIA FISITA 2018




F2018-PTE-122

Turbulence Modelling

k - ԑ model:

HHcL L =Iku

3

2'=

Integral length scale

Example of 3-D simulation:Example of 0-D:

( )

−−+

+=

dt

dk

dt

dkU

m

qU

dt

dk

3

2

3

2SS 2

ivcs

c

in

mivcs1000

( )kdt

d

dt

d

m

qp

dt

d 2

2ε

c

in

mc1000 C

12

5

3

4C

3

4CC

−+

+

+=

Turb

ule

nt kin

etic

energ

y

intake compression expansion exhaust

combustion

totUZ

CRANKANGLE

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Comparisons of Estimated and Experimental

Data with Cycle-Simulation Results

Cycle – Averaged Results



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Cycle – Resolved Results: Cycle-to-Cycle Variations



Averaged value: 10%-90% of burned mass fraction n = 1500 rpm

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Cycle – Resolved Results: Cycle-to-Cycle Variations



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averaged cycleslow burning cycle fast burning cycle

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Conclusions



• The presented estimation model for in-cylinder turbulence is applicable for operating points of

SI engine whose ROHR is defined by the propagation of flame over the premixed mixture in the

cylinder.

• The estimation model for in-cylinder turbulence level uses measured pressure profiles and it is

based on the newly developed quasi-dimensional combustion model – Flame Tracking Model.

• The model was applied on averaged cycle at full load condition and over the engine speeds

1000 rpm - 3000 rpm. The estimated values of turbulence intensity are close to MPS and it can

be used for the calibration of turbulence sub-model (k-ԑ) of cycle-simulation model. Average

difference between the estimated and simulated turbulence intensities are below 15%.

• For the selected OP (1500 rpm) the estimation of turbulence level was made on the individual

cycles (over 300 cycles) which helps the definition of turbulence perturbation constants for the

simulation of cyclic combustion variability.

• The presented estimation model for in-cylinder turbulence level in SI engines represents

efficient method for the faster calibration of cycle-simulation model, especially when CCV are

studied.

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Acknowledgment



This work was done within HrZZ IP-2014-09-1089 project ‘Experimental Research, Optimization and Characteriz

ation of Piston Engine Operation with Dual-Fuel Combustion – DUFCOROC ’ funded by the Croatian Science

Foundation. This help is gratefully appreciated.

Faculty of Mechanical Engineeringand Naval ArchitectureUniversity of Zagreb

Croatian ScienceFoundation

INDIA FISITA 2018

Thank you for your attention!

Contact Information:

Momir Sjerić, Ph.D., Assistant Professor

Faculty of Mechanical Engineering and Naval Architecture,

University of Zagreb

Ivana Lučića 5, 10 002, Zagreb, Croatia

Phone: +385 1 6168 144

Web: http://www.fsb.unizg.hr/miv/

Email: [email protected]



http://www.fsb.unizg.hr/miv/

mailto:[email protected]

presentation title f2018-pte-122 pte8 : powertrain

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