department of engineering science university of oxfordactivity coefficients: unifac or nrtl method...

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Department of Engineering Science University of Oxford Joe Camm, Safwan Hanis Bin Mohd Murad, Richard Stone, Martin Davy, (Oxford University) Dave Richardson (JLR Powertrain Research) [email protected] Imaging and Modelling of Gasoline Fuel Sprays 13 June 2017 This work was completed through support of the University of Oxford Clarendon Fund Scholarship

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Page 1: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Department of Engineering ScienceUniversity of OxfordJoe Camm, Safwan Hanis Bin Mohd Murad,

Richard Stone, Martin Davy, (Oxford University)

Dave Richardson (JLR Powertrain Research)

[email protected]

Imaging and Modelling of Gasoline Fuel Sprays

13 June 2017

This work was completed through support of the University of Oxford

Clarendon Fund Scholarship

Page 2: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Overview

Motivation for study of gasoline fuel sprays

Fuel spray chamber

Design

Sample images

Comparison with engine results

Droplet evaporation modelling

Non-ideal fuel mixture behaviour – increasing ethanol content in

gasoline

Summary

13 June 2017

Slide 2

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 3: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Gasoline fuel sprays

13 June 2017

Slide 3

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Improved thermal efficiency…

Charge cooling, controlled fuel delivery,

stratified charge operation…

…but PM emissions greater than from PFI

Locally rich mixture sources:

Unevaporated droplets

Surface fuel films

Inhomogeneity

Focus on

Spray evaporation

Spray structure

Spray penetration

Page 4: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Atmosperic Spray Rig

• Inject and purge continuously for consistent

injector behaviour (>5 Hz)

• Optical access for imaging, laser diagnostics,

droplet sizing, etc

• Heating to 150oC tip temperature

• 400 bar GDI, 2200 bar diesel

• LabVIEW vi for injector temperature control,

timing synchronization and data acquisition

• Overdriven LED illumination (up to 1 kW)

13 June 2017

Slide 4

Oxford Spray Chamber

and Instrumentation

Set up for:

• GDI injector, with variable orientation

• Spray impingement / heat flux studies

• Single-hole Spray A diesel injector

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 5: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Characterizing flash boiling

Fuel saturation pressure ratio

𝑅p > 1 means superheated

𝑝amb is usually 1 atm in Rig

Images taken with 4 µs exposure. Injector energizing time was 2 ms

13 June 2017

Slide 5

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 6: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Spray movies

13 June 2017

Slide 6

135degC

(or 90degC at 0.5 bar)90degC

Bespoke thresholding algorithm

20degC

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 7: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Effect of superheat level on spray structure

13 June 2017

Slide 7

With this injector, increasing superheat causes greater and greater spray collapse

into a single jet structure, with eventually a greater penetration. Observed in

literature for other GDI injectors

S Murad et al., SAE Technical Paper 2016-01-0991

M Xu et al., SAE Technical Paper 2013-01-1614

Bespoke Spray Image Analysis code developed

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 8: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Fuel superheat influence on PM emissions – Sample Results

13 June 2017

Slide 8

• JLR optical engine in homogeneous mode

• Part load (MAP 0.5 bar), 1000 rpm, BMEP ~ 2 bar, air intake at 40℃• Cylinder head (coolant) temperature varied to change fuel superheat

• Injection timing varied

• Lambda = 0.9 or 1.01

• Metal components where possible for PM tests but spray structure

verified during motoring tests, with full optical liner

• Heated sample line – limited nucleation mode PM

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 9: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Fuel superheat influence on PM emissions – Sample Results

13 June 2017

Slide 9

Tests and analysis

performed by

Safwan

• Peak at 200 nm

relatively unaffected

by lambda, timing or

spray structure

• Smaller peak greatly

increased with

superheat at medium

timing – severe

impingement

• Early injection timing

resulted in very low

particulate levels –

lower cylinder

pressure and faster

charge motion??

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 10: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Multi-component droplet evaporation

13 June 2017

Slide 10

Comprehensive suite of models in MATLAB for single droplet

evaporation

Re-implemented in OpenFOAM for GDI spray simulation

Low pressure modified Raoult’s law: 𝛾𝑖𝑋𝑖𝑃𝑣𝑖 = 𝑦𝑖𝑃 Activity coefficients: UNIFAC or NRTL method

Modifiable at high pressure for gas phase non-ideality, supercritical states and gas

solubility (diesel injection conditions)

Droplet internal composition

Well-mixed (batch distillation)

Unmixed (constant, averaged properties)

Liquid diffusion-controlled ( 𝑋𝑖 = 𝐷L𝑖𝛻2𝑋𝑖) - Effective Diffusivity Model

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

𝑚 = 𝜋𝑑𝜌𝐷FASh′ ln(1 + 𝐵Y), 𝐵Y =Σ𝑌𝑖s

1−Σ𝑌𝑖s

Page 11: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Multiplicative non-ideal thermodynamic correction factor based on activity coefficient

𝐷L = 𝛤𝐷L,ideal,

𝛤 = 1 + 𝜕 ln 𝛾𝑖 𝜕 ln𝑋𝑖

Bi-component: Well-mixed vs Liquid Diffusion controlled

13 June 2017

Slide 11

Well-mixed approximation used typically – check validity by solving the diffusion equation 𝑋𝑖 = 𝐷𝐿𝑖𝛻

2𝑋𝑖

Liquid diffusion coefficient Temperature and composition dependent

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 12: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

13 June 2017

Slide 12

Internal droplet composition

Bi-component: Well-mixed vs Liquid Diffusion controlled

e40 blend, initial liquid temperature 100ºC,

ambient at 100ºC, 3 bar

The non-ideal liquid diffusivity is much smaller, causing the diffusion boundary layer to regress inwards without the surface concentration changing greatly. Closer to the unmixed model??

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 13: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Multi-component extension

13 June 2017

Slide 13

Had not seen this in literature so extended to N species

Liquid diffusion-controlled model requires N – 1 coupled diffusion equations

Matrix equation: 𝜕 𝑋

𝜕𝑡= 𝐷 𝛻2𝑋

Hydrocarbon species have much higher diffusivity within themselves (better mixing)

Treat as a pseudo-binary mixture: ethanol + hydrocarbons

Only solve one equation, as with ethanol + iso-octane

Units 10-10 m2/s

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

J Camm et al., SAE Technical Paper 2015-01-0924

Page 14: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Findings from droplet and spray simulations

13 June 2017

Slide 14

Iso-octane/ethanol

Most basic gasoline model

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Well-mixed model in error, for most

conditions, due to trade-off between

ethanol volatility and ethanol latent heat

7 component model fuel +

ethanol

Well-mixed model over-predicts lifetime.

The continued ethanol presence boosts

droplet volatility

J Camm et al., SAE Technical Paper 2015-01-0924

Page 15: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

Summary

13 June 2017

Slide 15

Fuel spray imaging and image analysis, subcooled and superheated

Spray structure, penetration and evaporation rate

Effects on particulate matter emissions

Detailed modelling of multi-component single-droplet evaporation

Quickly identify trends due to fuel or operating conditions

Identify required modelling complexity for accurate simulations

For gasoline-like fuels (containing ethanol), assess impact of ethanol

on ability of mutually repellent species to mix within the droplet, and

subsequently on evaporation rate

This work was completed

through support of the

University of Oxford

Clarendon Fund

Scholarship

Page 16: Department of Engineering Science University of OxfordActivity coefficients: UNIFAC or NRTL method Modifiable at high pressure for gas phase non-ideality, supercritical states and

New Shock Tube at Oxford

High temperature, high pressure Fuel Spray and Kinetics research

Designed around ECN Spray A condition

Extendable to trans- and supercritical regimes (150 bar, 1500 K)

Test times on order of 3-10 ms

13 June 2017

Slide 16