Fundamental Combustion Characteristics of Gasoline ... Presentations...13 Slide credit: Tamour Javed (Javed et al, PROCI 2016) Multi-component Surrogate Formulation Species mol% 2-methylbutane

Fundamental Combustion Characteristics of

Gasoline Compression Ignition (GCI) FuelsS. Mani Sarathy, Clean Combustion Research Center, KAUST

Acknowledgments

Farooq, Javed, Abbad, Chen, Selim, Ahmed, Naser, Singh, Bhavani Shankar, Mohamed, Atef, Manaa, Roberts, Chung

Dagaut

Hansen

Curran et al.

Pitz, Mehl, Westbrook

Sponsors

Oehlschlaeger et al.

Kukkadapu, Sung

3

What is KAUST?

• Founded in 2009 on the

shores of the Red Sea

• Graduate study only

research-based University

• International privately

operated instituion in

Saudi Arabia (~80

nationalities)

Aleppo

4

Engines and Fuels

SI

• Easy emission control

• Lower efficiency

• High-octane gasolines

(AKI* 90)

• Expensive emission control

• Higher efficiency

• Diesel fuel

• Bad control

• Can use almost any fuel

• High efficiency and

better emissions

• Low-octane gasolines

(AKI 70)

CI

HCCI

PPC/

GCI

∗ 𝐴𝐾𝐼 = 𝑅𝑂𝑁+𝑀𝑂𝑁

2

Slide credit: Tamour Javed/Bengt Johansson

n-alkanes

branched alkanes

cycloalkanes

aromatics tetralin

1-methylnaphthalene

1,2,4-trimethylbenzene

decalin

n-dodecylcyclohexane

n-hexadecane

n-dodecane

2-methylpentadecane

3-methyldodecane

2,9-dimethyldecane

1. Molecular Level Fuel Characterization

2. Surrogate Fuel Formulation•Reproduces target properties of real fuel•H/C ratio, functional groups, molecular weight, ignition

3. Chemical Kinetic Modeling

4. Experimental Testing

5. Predict CombustionCoupled kinetic/fluid models

6. Fuel/Engine Design

Fuels

Light Gases Diesels Solid fuels

Naphthas Lubricants Synthetic fuels

Gasolines Heavy fuel oils Oxygenates

5

Fuels for advanced gasoline engines

6

WT

T &

TT

W e

mis

sio

ns r

ed

uctio

ns

• Low carbon emissions [SAE 2013-01-2701]

• Low fuel consumption (BSFC) [SAE 2012-01-0677]

• Lower regulated emissions [SAE 2014-01-2678]

• Additional benefits – low aromatics: better H/C ratio, low engine-out soot

• Optimum fuel for GCI engines

are in 60 – 85 octane range

Slide credit: Tamour Javed

Fuels for Advanced Combustion Engines

FACE Gasolines

Collaborative research program led by KAUST with LLNL, UConn, RPI, UC Berkeley, CNRS...- Acquisition of 6 FACE fuels (A, C, F, G, I, J)- Compositional Analysis- Testing in ST, RCM, and JSR at different facilities- Formulation of suitable surrogates, modeling and validation- Kinetic analysis

Only sold in 55 gal barrels

7

RON 70 to 97

Sensitivity 0 to 11

Aromatics 0 to 35%

Ideal reactors

• GCI fuels are tested at wide range of combustion conditionsLaminar Flames

Fundamental Data for GCI Fuels

8

Ignition Devices

Engines

Surrogate formulation methodology

Optimization of palette species blend by matching target properties (Ahmed et al.)

• Target Properties• H/C ratio

• Density

• RON & MON

• DCN

• Carbon type mole fraction

(DHA, PIONA, NMR)

• Distillation curve

Ahmed et al., Fuel 143 (2015) 290-300.

9

iso-Alkanes

iso-pentane(2-methylbutane)

2-methylhexane

iso-octane(2,2,4-trimethylpentane)

n-Alkanes

n-butane

n-heptane

Aromatics

Toluene124-trimethylbenzene

1-hexene

Alkenes

cyclopentane

Cycloalkanes

1,2,4-trimethylbenzene

1-hexene

cyclopentane

Try it:cloudflame.kaust.edu.sa

Chemical Kinetic Models

The purpose of models is not to fit the data but to sharpen the questions.

-Samuel Karlin

Public Position

10

The purpose of models is to fit the data.

Private Position

11

• Ignition of GCI Fuels and Surrogates

– Shock tube and rapid compression machine ignition delay and species

measurements

• Low-octane Fuels (Light naphtha AKI 64 and FACE I AKI 70)

• Mid-octane Fuels (FACE A and C AKI 84)

• High-octane Fuels (TPRF surrogates and wide range of high octane

gasolines AKI 91)

• Understanding surrogate complexity requirements using targeted

experiments and chemical kinetics analysis

– PRF, TPRF and multi-component surrogates

Summary of GCI Fuel Ignition Studies

12

Light Naphtha Fuel Characterization

• Detailed hydrocarbon analysis (DHA) and octane testing (RON & MON) were done

at Saudi Aramco R&DC

• Low octane (RON = 64.5, MON = 63.5), highly paraffinic (> 90% paraffinic content)

fuel

Light

naphtha

RON 64.5

MON 63.5

Sensitivity 1

H/C ratio 2.34

Avg. mol. wt. 78.4

n-alkanes 55.4

iso-alkanes 35.9

Cycloalkanes 6.7

Aromatics 1.32

13Slide credit: Tamour Javed (Javed et al, PROCI 2016)

Multi-component Surrogate Formulation

Species mol%

2-methylbutane 0.25

2-methylhexane 0.1

n-pentane 0.43

n-heptane 0.12

Cyclopentane 0.1

LN-KAUST surrogate composition

14Slide credit: Tamour Javed (Javed et al, PROCI 2016)

Comparison of Experimental Data with Surrogate Simulations

• LN-KAUST and PRF 64.5 simulations are in good agreement with each other

and with data at high temperature and NTC region

• At low temperatures, PRF 64.5 simulations are more reactive by a factor of

two specially at f = 1 and 215

f = 0.5 f = 1 f = 2

Slide credit: Tamour Javed (Javed et al, PROCI 2016)

Low Temperature Rich Conditions: Experiments and Simulations

f = 2

16

• Further targeted experiments reveal same

trends at low temperatures

• LN-KAUST simulations and experiments

are in good agreement with light naphtha

data

• PRF 64.5 simulations and data are around

a factor of two faster

• Multi-component surrogate (LN-KAUST)

works better over a broad range of test

conditions

Slide credit: Tamour Javed (Javed et al, PROCI 2016)

FACE I Measurements

• FACE I exhibits full NTC behavior in 750 –

850 K range

• PRF 70 captures the reactivity of FACE I

• PRF 70 marginally faster ( 25 %) at low

temperatures17

Fuel / air, f = 1,

P = 20 bar

Slide credit: Tamour Javed (unpublished)

FACE IFG-I

surrogate

PRF 70

surrogate

RON 70.3 70.7 70

MON 69.6 68.4 70

Sensitivity 0.7 2.3 0

Avg. mol. wt. 95.5 98.9 109.7

n-alkanes 14 12 33

iso-alkanes 70 72 67

Cycloalkanes 4 6 0

Aromatics 5 4 0

Olefins 7 6 0

18

Low Temperature Octane Dependence

Fuels with S < 7 exhibit weak octane

dependence on ignition delay times

Fuels with S > 7 exhibit octane

dependence on ignition delay times

Sensitivity (S) = RON – MON

Low Octane GCI Study

Fuel Light naphtha PRF 65 FACE I gasoline PRF70

RON 64.18 65 70.3 70

S (=RON-MON) 0.61 0 0.7 0

Density (kg/m3) 642 689 688 690

H/C 2.34 2.26 2.25 2.26

Slide credit: Nimal Naser (unpublished)

Description Specification

Injector type Common rail piezo-injector

Injector model Bosch (0445116030)

Fuel inj. pressure 300 bar

Injector holes 7

Nozzle hole diameter 0.18 mm

Spray included angle 142°

Fuel injector

Piston

Combustion

chamber

Mass of fuel for constant CA50

Mass of PRF 65 to achieve constant CA50 of 4°CA aTDC CA50 of different fuels using same mass as PRF 65 at

corresponding SOISlide credit: Nimal Naser (unpublished)

Equivalence ratio distribution for PRF 65 and LN

Equivalence ratio distribution on the piston bowl surface at 1°CA aTDC (above) side view

of piston bowl (middle), T-f map colored with OH mass fraction with SOI at 19 °CA bTDC

PRF 65 LN

Slide credit: Nimal Naser (unpublished)

CFD on the fuel stratification with injection time

Slide credit: Bengt Johansson

DCN of 71 pure compounds and 54 blends was collected/ measured using IQT.

Dataset was used to study the relationship between CN/DCN and 8 structural parameters

1) Paraffinic CH3 groups

2) Paraffinic CH2 groups

3) Paraffinic CH groups

4) Olefinic CH-CH2 groups

5) Naphthenic CH-CH2 groups

6) Aromatic C-CH groups

7) Molecular weight

8) A new parameter called as Branching Index (BI)

Predicting ignition quality from NMR spectra

Slide credit: Abdul Jameel (Energy Fuels 2016)

NMR Based Model

DCN= −21.71 + 0.2730 ∗ paraffinic CH3 wt %

+0.5645 ∗ paraffinic CH2 wt %

+0.2393 ∗ paraffinic CH wt %

−0.0031 ∗ olefinic CH − CH2 wt %

+0.3238 ∗ naphthenic CH − CH2 wt %

+0.2481 ∗ aromatic C − CH wt %

+0.2484 ∗ Molecular weight

−20.27 ∗ BI

1H NMR spectra

Slide credit: Abdul Jameel (Energy Fuels 2016)

Try it:cloudflame.kaust.edu.sa

Predictive capability

The model was validated with 22 real fuel mixtures (gasoline / diesel) and 59

blends of known composition.

Slide credit: Abdul Jameel (Energy Fuels 2016)

• Both physical and chemical kinetic properties of GCI fuels

control combustion performance

• Surrogates used for CFD simulations need to capture both

physical and chemical kinetic features (depending on engine

operating mode).

• Fuel design based on first principles of combustion

chemistry is possible.

26

Summary

27

MAKE COMBUSTION

GREAT AGAIN

شكرا

[email protected] http://cpc.kaust.edu.sa

谢谢 Thank you

Merci Grazie

GraciasDank u

ありがとう

Kiitos

Děkuju

धन्यवाद

감사합니다

terima kasih

takk

متشکرم

شکريا

Cảm ơn bạn

Dziękuję

Спасибо

köszönöm Tack

ขอบคุณ

Obrigado

hvala

நன்றி

teşekkür ederim

Danke

ευχαριστώ Efharistó

29

Fuel design from chemical kinetics

• Higher sensitivity fuel displays less NTC behavior; less reactive at RON-like and more reactive at MON-like.

• At RON-like conditions, fuel components that control OH radical pool are rate controlling

• At MON-like conditions, fuel components that drive OH and HO2 radical coupling are important

1.E-03

1.E-02

1.E-01

1 1.1 1.2 1.3 1.4 1.5

Ign

itio

n D

ela

y T

ime (

s)

1000/T (1/K)

const. vol. simulations 20 atm, stoichiometric fuel/air mixtures

RON=94, S=5.6

RON=97, S=11

700KRON-like825K

MON-like

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

500

1000

1500

2000

2500

3000

3500

0 0.005 0.01 0.015 0.02 0.025

Mo

le F

racti

on

Te

mp

era

ture

(K

)

Time (s)

20 atm, 700 K, phi=1

FGG-Temp FGF-Temp FGG-OH FGF-OH FGG-HO2/1000

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

500

1000

1500

2000

2500

3000

3500

0 0.005 0.01 0.015 0.02 0.025

Mo

le F

rac

tio

n

Tem

pe

ratu

re (

K)

Time (s)

20 atm, 825 K, phi=1

FGG-Temp FGF-Temp FGG-OH FGF-OH FGG-HO2/1000 FGF-HO2/1000

• Modeling rationalizes non-linear blending effects (source/sink interactions)

• Aromatic/alcohol and aromatic/naphthenic couplings

Sarathy et al, Combust Flame 2016

RON, MON, and S correlations

CPC group

4

MC90.5(2.5) TRF89.1(3.5) MC90.9(8.2) TRF89.3(11.1)

0

5

10

15

20

25

30

10 20 30 40 50

Ign

itio

n d

ela

y t

ime

(m

s)

Pressure (bar)

MC90.9(-0.2)

MC90.5(2.5)

TRF89.1(3.5)

MC90.9(8.2)

TRF89.3(11.1)

TRF92.3(11.6)

TRF,93.7,(3.4)

TRF97.7(11.5)

TRF95.2(4.7)

TRF86.6(2.4)

TRF85.7(1.1)

TRF98(10.6)

TRF65.9(8.2)

TRF76.2(5.3)

TRF75.6(8.7)

TRF85.2(10.4)

TRF89.3(11.1)

TRF93.4(11.9)

TRF96.9(11.7)

TRF99.8(11.1)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 1 2 3 4 5 6 7 8 9 10 11 12

Pre

ssu

re E

xp

on

en

t (N

)

Fuel Sensitivity (S)

850 K, 50 bar in Air Phi 1.0 IDT = a * P ^ -N

Singh, Badra, Mehl, Sarathy, Energy Fuels 2016

• Engineering correlations can be made using simulated ignition delay times (79 fuels in training set)

• Reaction path analysis shows the effects of fuel composition (PIONA) on radical source/sink

• Pressure dependence of a ignition delay is correlated to sensitivity such that quantitative predictions can be made

RON (S)