SAE 2005-01-1125

2005-01-1125

Modeling the Effects of EGR on a Heavy Duty DI Diesel Engine Using a new Quasi-Dimensional Combustion Model

E. G. Pariotis, D.T. Hountalas and C.D. Rakopoulos School of Mechanical Engineering, National Technical University of Athens

Copyright © 2005 SAE International

ABSTRACT

The model has already been applied on an old technology, naturally aspirated HSDI Diesel engine and on a heavy-duty turbocharged DI one equipped with a high pressure PLN fuel injection system, and the results were satisfying as far as performance and pollutant emissions (Soot and NO) are concerned. Taking into account that the main scope of engine simulation models is to assist engineers and researchers to understand the complex mechanisms involved in diesel engine combustion and pollutants formation and that through the continues engine development, new techniques are implemented, it is obvious that engine simulation models must always be enhanced with new features in order to be kept up-to-date. In this study the model has been modified to take into account the effect of EGR, since the latter one is a measure that will be used more extensively in the future to control NO emissions from turbocharged HDDI Diesel engines. The model is validated using experimental data from a single cylinder test engine operating with various EGR percentages at two different engine loads (part and full load). Comparing calculated with experimental cylinder pressure traces a good agreement is observed and the trends of exhaust tailpipe emission values (Soot and NO) are quite well predicted, at all the operating conditions examined. Moreover taking into account what is already known about how EGR affects combustion and pollutant formation mechanisms, and considering the calculated in-cylinder spatial distribution of temperature and species concentrations, it is revealed that model’s predictions are in the correct way. This is encouraging, since by using this new quasi-dimensional model it is possible to obtain a more fundamental understanding of the various processes taking place inside the combustion chamber compared to existing multi-zone models, in a fraction of the time required by the more detailed CFD models.

INTRODUCTION

The diesel engine has been widely accepted as the most efficient powertrain for propulsion of trucks and vehicles [1,2]. However, considering the future strict emissions legislation, the automotive engineering community dealing with DI Diesel engines is trying to improve the

combustion mechanism in order to reduce the main pollutant emissions from this type of engine, i.e. NOx and Soot. Since the future emissions legislation is very strict, it is well established that a combination of various measures has to be applied to reduce both NOx and Soot emissions at acceptable levels [3-5]. However, the determination of the optimum strategy is a very demanding procedure, since any modifications or measures should not affect in an adverse way the engine’s performance and efficiency or result to an increase of cost or complexity [6-11]. To this scope, computer engine simulation models possess a significant role, in conjunction with properly designed experiments. Through computer simulation, the effect of engine design and operating parameters on combustion mechanism and furthermore on pollutant formation can be investigated on a fundamental basis, offering valuable guidelines to engine designers. This way, the experimental effort required for engine design and development can be significantly reduced [12].

Over the last decades, many computer simulation engine models have been developed. In general, there are two main categories of engine simulation models used nowadays, the phenomenological models and the multidimensional ones. The distinction of these two categories is made according to the methodology followed to simulate the processes taking place inside the combustion chamber. The methodology differs, since the purpose of modelling is different when using a phenomenological or a multidimensional approach. Both types of simulation models have features that make them attractive for specific applications; the phenomenological ones are more suitable for cycle calculations while the multi-dimensional ones are ideal candidates for more fundamental studies. For this reason it would be interesting to develop a hybrid simulation model, which would combine the main features of these two types of models. This new model should offer a more fundamental understanding of the various processes taking place inside the combustion chamber compared to existing phenomenological (multi-zone) models, in a fraction of the time required by the more detailed CFD models. To this scope, a new quasi-dimensional combustion model has been developed by the authors in the past [13,14], and has already been used successfully for the prediction of performance and

pollutants formation in two types of diesel engines: an old technology naturally aspirated, HSDI Diesel [13], and a new technology turbocharged HDDI Diesel engine [14]. Continuing our effort to evaluate and improve this newly developed model, and make it applicable to study the effect of various strategies for emission control in the present the use of EGR is examined. Specifically it is examined the effect of EGR on a HDDI Diesel Engine at various EGR rates and at two engine loads (part and full load).

EGR has been established as an effective method for reducing NOx emissions from diesel engines. Its importance becomes more apparent if we consider the new emissions legislation (EPA and EURO V) [15]. Unfortunately, due to the controversial mechanisms of NO and Soot formation, any measure affecting the combustion mechanism that results to the reduction of one of these two pollutants, leads to the increase of the other. An effective method for controlling NOx and Soot emissions is the use of high injection pressure, advanced injection timing and increased boost pressure to control soot emissions and EGR to control NO that rises to high values [6,9].

To evaluate the ability of the newly developed model to predict the effect of EGR on the combustion mechanism, this is applied on a heavy-duty, turbocharged, DI, single cylinder Diesel test engine operated with various EGR rates. The comparison of calculated with experimental cylinder pressure traces reveals a good agreement for all EGR rates considered. As far as NO and Soot emissions are concerned, the model manages to predict qualitatively well the effect of EGR rate. As for absolute values, higher differences between measured and calculated values are observed for Soot emissions, while calculated values for NO are close to the measured ones. Furthermore, the simulation provides information concerning the spatial distribution of temperatures and species concentrations inside the combustion chamber that assists to the correct interpretation of the actual effect of EGR upon the combustion mechanism. The simulation predicts correctly the main effect of EGR on pollutant formation mechanism, which are the reduction of peak in-cylinder temperatures and the reduction of local oxygen concentration, that results to lower NOx and higher Soot formation rates.

BRIEF DESCRIPTION OF THE SIMULATION MODEL

The simulation model used in this study is an improved version of a quasi-dimensional combustion model developed by the authors in the past [13,14]. The main feature of the model is that it uses phenomenological sub-models to describe the various processes taking place inside the combustion chamber, combined with methods used in CFD models to calculate the local values of the various properties examined. Specifically, phenomenological sub-models are used to describe: heat transfer through the cylinder walls, fuel injection rate, spray penetration, evaporation, combustion and

pollutants formation. On the other hand, the computational domain extends through the entire cylinder volume and the local value of each characteristic property of the field (specific enthalpy, species concentrations, pollutant emissions concentrations) is calculated at each computational cell, solving the general conservation equation. This is accomplished using the finite volume method, similarly to what is done in most CFD models.

This way the model developed describes in a more fundamental way the air-fuel mixing and combustion mechanism compared to existing multi-zone phenomenological models, while being less time consuming compared to the more accurate CFD models. Furthermore, it overcomes basic difficulties experienced in existing multi-zone models, as far as air-fuel mixing is concerned where only empirical relations are used. Only a brief description of the various sub-models used will be given in the following paragraphs for the sake of completeness, since these sub-models have been presented in detail in previous publications [13,14,16]. The new features added to the model used in the present work are the introduction of EGR and the improvement of the species distribution calculation.

THE COMPUTATIONAL DOMAIN

The engine treated in this study has a bowl in piston combustion chamber and an eight-hole injector centered in the cylinder bore. Due to symmetry, the computational domain is restricted to the one eighth of the cylinder volume to save computational time, as depicted in Figs. 1a,b. The area inside the cylinder is divided into cylindrical computational cells as shown in Fig. 2, using a structured grid that contracts and expands to account for the variation of the clearance volume. Moreover, depending on the distance between piston crown and cylinder head, the number of computational cells varies in a predefined way.

In the present study the grid used for all cases examined has ten cells in the radial direction inside the piston

r direction

z direction

Fig. 1a Computational domain at a vertical plane (r-z)

θ direction

r direction

Piston cavity

Cylinder walls

θ-r plane view

Injection Direction

Fig. 1b Computational domain at a horizontal plane (θ-r)

r

z

θ N

B

T

W

ES

Fig. 2 Computational cell and coordinates

bowl, five cells in the outer volume, six cells inside the piston bowl in the axial direction and twelve to five cells in the region between the piston and the cylinder head (depending on piston position). Finally, in the circumferential direction six cells are used.

GENERAL CONSERVATION EQUATION

As already mentioned, the main characteristic of the newly developed quasi-dimensional model is that the value of each property (specific enthalpy, species concentrations and pollutants emission concentrations) is calculated at each computational cell, solving the general conservation equation for each of these properties, using the finite volume method. Assuming that Φ is the general property, the conservation equation that is solved at each computational time step, over the whole computational domain, is:

( ) ( ) ( ) ( )

Φ

piston

piston

Sz

zΦ

Γ

θθΦ

rΓ

r1

rrΦ

rΓ

r1

zΦ wρ

θΦ ρv

r1

rΦr u ρ

r1

tΦ z ρ

z1

+∂

∂∂

ϕ∂+

∂

∂∂

ϕ∂+

∂

∂∂

ϕ∂=

∂∂

+∂

∂+

∂∂

+∂

∂

(1)

Using the source term ΦS and depending on the

physical meaning of the general property Φ, the following processes can be considered: the compression and expansion of the computational cells (due to piston movement), the heat exchange rate with the cylinder walls, the addition of fuel vapor mass (due to fuel spray evaporation), or the addition of combustion products due to combustion and dissociation. For the calculation of the transport terms of the conservation equation EQ(1) the three dimensional velocity vector (u,v,w) at each computational cell is required. For this reason use is made of a phenomenological gas motion model developed in the past by the authors [16] is used, avoiding the direct solution of the momentum equation (which is the common practice in most pure CFD models). As a result, a rough estimation of the velocity field at each time step is obtained, following a simpler procedure and requiring much less computational time compared to the more detailed CFD models. Even though the estimated flow field using this methodology is not detailed it is qualitatively correct providing a good estimation for the velocity distribution and its evolution with engine crank angle. A detailed description of the gas motion model used and the procedure followed for the calculation of the spatial distribution of temperature and species concentrations, at each time step, is given in previous publications [13,14,16].

At each computational cell, in general, fourteen species are considered. These are: Fuel Vapor, NO and Soot concentrations and the combustion products which, in this study, are defined considering dissociation, using the chemical equilibrium scheme proposed by Vickland et al [17]. According to this chemical equilibrium scheme, the following eleven species are considered to be present in chemical equilibrium:

O2, N2, CO2, H2O, H, H2, N, NO, O, OH, CO

When the dependent variable in the general conservation equation EQ(1) is the mixture specific enthalpy (Φ=h), the overall heat transfer between cylinder walls and gas computational cells is taken into account through the volumetric source rate SΦ, using the following expression:

( ) ( )

−×+

−××= 4

cell4wall

cell

cellwallheat TTc

VTT

hAS (2)

The convection heat transfer coefficient is obtained from the following correlation:

char

c3c21 l

kPrRech ×××= (3)

where: µ

lwρRe char

char ××= (4)

kc

µ Pr p= (5)

and c1, c2, c3, c are constants. In this study c1=0.30, c2=0.80, c3=0.33 and c=5.668E-8.

SPRAY MODEL

SPRAY TRAJECTORY AND DISPERSION

In pure CFD models, spray trajectory is defined solving the momentum equation and taking into account the interaction between the two phases (liquid and gas). This procedure is computationally demanding and various assumptions need to be made, since even today many aspects of the processes taking place, especially in the region near the injector’s holes, have not been fully understood [18-21]. To overcome these difficulties and due to the different nature of the proposed model, fuel spray trajectory and dispersion is defined based on semi-empirical equations. This is in accordance to the procedure followed in most multi-zone phenomeno-logical models.

As the fuel spray penetrates inside the combustion chamber, it is divided into packages (called zones) as follows [22]: in the injection direction the number of zones formed is determined from the computational time step, while in the radial direction the fuel jet is divided into three zones (M-direction) and into eight in the circumferential direction (N-direction) , as shown in Fig. 3. Each group of new zones entering the combustion chamber, at each time step, is called a ‘parcel’. The mass of fuel in each parcel can be either specified as input, or calculated using a fuel injection sub-model. The fuel mass of a parcel is distributed evenly to each zone.

Frame 001 31 Aug 2002 | |Frame 001 31 Aug 2002 | |

Fig. 3 Spray division into zones (N=8, M=3) at a certain instance.

Each parcel entering the cylinder initially travels a distance, at a constant speed, equal to the fuel injection speed, called the break-up length. Fuel vaporization initiates after the break-up length. After break-up the injected fuel is distributed within a spray angle, which is unique for each spray parcel and is calculated using

empirical correlations. In the present study the correlations of Hiroyasu and Arai [23] are used to estimate jet penetration as modified by Assanis et al. [24] to account for nozzles with discharge coefficient in the range of 0.6-0.8. A detailed description of the equations used for the calculation of spray trajectory and dispersion is given in [13]

INJECTION RATE

To estimate the injection rate of fuel and the initial conditions at the nozzle exit, it is assumed that the flow through the nozzle hole is quasi-steady, one- dimensional and incompressible. Thus, the fuel mass flow rate is calculated by the following equation [12]:

∆P2ρAcm lnD= (6)

where An is the nozzle hole area and ∆P the local pressure difference. In the present study the injection pressure was measured during experiments and serves as input to the fuel injection sub-model, in order to calculate the pressure drop “∆P” across the nozzle.

FUEL VAPORIZATION

After break-up a group of drops is generated in each zone. In the present study it is assumed that all droplets have a diameter equal to the Sauter Mean Diameter, given by the following empirical correlation [22]:

( ) ( ) ( )0.131f

0.121α

0.13532 Vρ∆P23.9D −= (7)

where Vf is the volume of fuel injected per pump stroke. The number of droplets within each zone is calculated using the following equation:

l,zonezone 3

32 l

mN 6

πD ρ= (8)

where ml,zone is the zone fuel mass. For the evaporation process the model of Borman and Johnson [25] is followed.

COMBUSTION MODEL

IGNITION

After fuel injection has been initiated, various physical and chemical processes take place before combustion initiation. To determine the ignition delay period, in this study an empirical equation is used [26]. In each computational cell ignition occurs when the following criterion is satisfied:

( ) 1ePc

1ign

g

τ

0 T46501.19ign

=∫ − (9)

where P is the mean cylinder pressure and cign is a constant. After ignition, evaporated fuel (which in this study is assumed to be normal dodecane) and air react at a rate given by the following Arrhenius type equation [12]:

)TEexp(YYAρR

g

nox

mfv

2mixfv −−= (10)

where ρmix is the local mixture density, A is the frequency factor, E is the reduced activation energy, m and n are constants, and Yfv, Yox are the local fuel vapor and oxygen mass concentrations, respectively. In this study constants m and n are taken equal to unity.

INLET CHARGE COMPOSITION

To extend the applicability of the simulation model when EGR is used, required modifications have been made to the source code. The EGR percentage is defined by:

EGR

air EGR

mEGR (%)= ×100m +m

(11)

where airm is the mass of fresh air and EGRm is the amount of recycled exhaust gas [27]. The recycled exhaust gas consists of O2, N2, CO2 and H2O [28-32]. To determine the inlet gas composition at each EGR rate examined, fresh air and recycled exhaust gases are mixed to form the inlet gas mixture, which has a uniform composition. The composition of the exhaust gas is determined through an iterative procedure, using the composition of cylinder mass at exhaust valve opening event [27].

POLLUTANTS EMISSION FORMATION

NITRIC OXIDE FORMATION

In the present study the chemical equilibrium scheme proposed by Vickland et al. [17] is used, to calculate the concentration of each of the following eleven species, in each computational cell:

O2, N2, CO2, H2O, H, H2, N, NO, O, OH, CO

The formation of nitric oxide is controlled by chemical kinetics [12]. In the present work, the extended Zeldovich mechanism is used to calculate the NO concentration at each computational cell.

SOOT FORMATION AND OXIDATION

As far as soot formation is concerned, many empirical models have been proposed. However the detailed mechanism of soot formation in internal combustion engines is not fully understood until today. In this study the semi-empirical two-rate equation model proposed by Hiroyasu et al. [22] is used. This model has been widely

used in various phenomenological models [24,33,34] to predict soot emissions. The model manages to estimate, in a qualitatively correct way, the effect of engine operating parameters on soot emissions.

RESULTS AND DISCUSSION

DESCRIPTION OF THE TEST ENGINE

The present investigation has been conducted on a single cylinder, direct injection, turbocharged diesel test engine, at DaimlerChrysler laboratories. The compressor has been replaced by a blower while the turbine is simulated by the throttle at the engine exhaust to maintain the back pressure at levels corresponding to the ones of the production engine on which the current engine design is based. To take into consideration EGR, the exhaust pressure before the turbine has been maintained at approximately 0.2 bar above the inlet pressure.

The engine has a bore of 130 mm, a stroke of 150 mm and a compression ratio of 17.6. The engine is capable of withstanding peak pressures up to approximately 200 bar. It is equipped with a PLN injection system having a maximum injection pressure up to approximately 1900 bar. Injection timing is controlled using an electrically actuated solenoid valve.

In the present study, the use of cooled EGR is considered using a constant recirculated exhaust gas temperature equal to 140 oC, at all EGR rates examined.

TEST CASES EXAMINED

In the past a preliminary study was conducted to determine the model’s ability to predict engine performance and emissions for two different engine configurations (one old technology naturally aspirated HSDI Diesel engine [13] and one new technology turbocharged HDDI Diesel engine [14]), at various operating conditions covering the full range of engine speed and load. The results were encouraging, indicating that the model describes correctly the air-fuel mixing mechanism and the processes taking place inside the combustion chamber. Furthermore, in both cases the simulation captured correctly the effect of operating conditions on pollutant emissions (NO and Soot).

In the present study, since the main objective is to examine the model’s ability to predict the effect of EGR on engine performance and emissions, two engine loads (part and full) were examined, and at each engine load, three EGR rates were considered, as shown in Table 1.

Table 1. Experimental test cases examined Engine

Speed (rpm) Engine

Load (%) EGR rates (%)

1130 50 0 10 20 1130 100 0 10 20

At each engine load, the zero EGR case was used as reference for the effect of EGR rate.

MODEL CALIBRATION

Since empirical and semi-empirical correlations have been used in the proposed simulation model, it is necessary to calibrate its constants at a specific operating point, before of its use for engine simulation. This is an inherent weakness of computer engine simulation models (regardless to whether they are phenomenological or CFD ones), which reveals their great dependence on experimental data. The calibration procedure is applied only once for a new engine design, since the constants, after having been determined, remain the same regardless of engine operating conditions. During calibration, the right set of model’s constants is determined to match the calculated with the experimental mean cylinder pressure diagram and the corresponding values of soot tailpipe exhaust emissions. For NO emissions no calibration is made. In the present study, model calibration has been made for the zero EGR case, at full engine load (1130 rpm, 100% load).

MODEL VALIDATION

PERFORMANCE

In Figs. 4a-c, the predicted cylinder pressure traces are compared with the experimental ones at 1130 rpm engine speed and full engine load, for the EGR rates considered (0%, 10% and 20%, respectively). In all test cases examined, a good agreement between calculated

20 40 60 80 100 120 140 160 180 200 220 240 260 280 300Engine Crank Angle (deg)

0102030405060708090

100110120130140150160170180

Cyl

inde

r Pre

ssur

e (b

ar)

Cylinder Pressure1130 rpm, 100% Load

10% EGRCalculatedMeasured

Fig. 4b Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 100% load and 10% EGR rate.

and experimental values is observed during the entire closed part of the engine cycle. The same comparison is also made for the part engine load, as shown in Figs. 5a-c. At all EGR rates examined, there is a good agreement between calculated and experimental cylinder pressure values, during the entire closed part of the engine cycle, with a slight difference at peak combustion


0102030405060708090

100110120130140150160170180

Cyl

inde

r Pre

ssur

e (b

ar)




0102030405060708090

100110120130140150160170180

Cyl

inde

r Pre

ssur

e (b

ar)



Fig. 4a Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 100% load and 0% EGR rate.

Fig. 4c Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 100% load and 20% EGR rate.


0

10

20

30

40

50

60

70

80

90

100

110

120

130

Cyl

inde

r Pre

ssur

e (b

ar)




0

10

20

30

40

50

60

70

80

90

100

110

120

130

Cyl

inde

r Pre

ssur

e (b

ar)



Fig. 5a Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 50% load and 0% EGR rate.

Fig. 5c Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 50% load and 20% EGR rate.


0

10

20

30

40

50

60

70

80

90

100

110

120

130

Cyl

inde

r Pre

ssur

e (b

ar)



Fig. 5b Comparison of predicted and measured cylinder pressure traces at 1130 rpm engine speed, 50% load and 10% EGR rate.

pressure for the cases of 10% and 20% EGR rates, were the calculated values are lower than the experimental ones. Comparing the cylinder pressure traces for the three EGR rates examined and for both engine loads (part and full), it is obvious that as EGR rate increases, in-cylinder peak pressure decreases

affecting slightly the indicated work. Thus, the model predicts the effect of EGR rate on engine performance, at both engine loads examined.

POLLUTANT EMISSIONS

The ability of the model to predict the effect of EGR rate on pollutant emissions (NO and Soot) is also investigated, comparing the measured tailpipe exhaust value of each pollutant with the corresponding predicted one, at all test cases examined. In Fig. 6a, it is observed that the model manages to predict quite well NO tailpipe exhaust values at full engine load, with a minor exception at 0% EGR rate, where NO is under-predicted, while at part engine load, the differences between calculated and experimental values are higher, but the trend is captured correctly.

Since NO emissions are very sensitive to the ‘history’ of local temperature distribution inside the combustion chamber, the correct prediction of NO tailpipe exhaust values is an indication that the model describes in a correct way the combustion mechanism and how this is affected by EGR. Moreover, at full engine load, it is observed that NO is reduced almost linearly with the increase of EGR rate. The reduction of NO with EGR is mainly due to the reduction of in-cylinder gas temperature and the reduction of available oxygen in each computational cell, as shown later on.

As far as soot tailpipe emissions are concerned, in Fig. 6b a comparison between the predicted and the measured values is shown, for all EGR rates considered, at part and full engine load. Comparing

0 10 20Exhaust Gas Recirculation [%]

0

4

8

12

16

Nitr

ic O

xide

[gr/k

Wh]

1130 rpm, 100% LoadCalculatedMeasured


0

4

8

12

16

Nitr

ic O

xide

[gr/k

Wh] 1130 rpm, 50% Load

CalculatedMeasured


0.0

0.4

0.8

1.2

1.6

2.0

Soo

t [gr

/kW

h]



0.0

0.4

0.8

1.2

1.6

2.0

Soo

t [gr

/kW

h]


Fig. 6a Comparison between calculated and measured exhaust tailpipe values for NO emissions at 1130 rpm engine speed, 50% and 100% engine load, for the case of 0, 10 and 20% EGR rate respectively.

Fig. 6b Comparison between calculated and measured exhaust tailpipe values for Soot emissions at 1130 rpm engine speed, 50% and 100% engine load, for the case of 0, 10 and 20% EGR rate respectively.

calculated with experimental soot values, it is concluded that the model predicts the overall effect of EGR rate on soot emissions. Even though in absolute values a difference exists at 20% EGR for both engine loads examined, trends are predicted adequately. Taking into account that the sub-model used for Soot formation is an empirical one and that the main purpose of engine modeling is the prediction of trends, the performance of the simulation model for this first application is judged as satisfactory. However, it is required to improve the model’s predictive ability for soot emissions by incorporating a more detailed Soot formation mechanism [35].

In Figs. 7a,b the corresponding in-cylinder histories for NOx and Soot emissions are given, at full engine load for all EGR rates examined. The information provided in these figures enables us to obtain a better understanding of the pollutant formation mechanism and especially for the effect of EGR upon it. Examining the ‘history’ of NO emission for the three test cases considered (Fig. 7a), it is obvious that the use of EGR has a strong positive effect (reduction) on NO formation rate. Increasing EGR rate results to late freezing of NO values, revealing that combustion is shifted towards the expansion stroke.

In Fig. 7b, the ‘history’ of Soot concentration inside the combustion chamber during the close part of the cycle is shown, at full engine load for the three EGR rates considered. Examining the predicted ‘history’ of Soot formation it is observed that from the beginning of soot formation the concentration of Soot rises rapidly as

180 200 220 240 260 280 300 320Engine Crank Angle (deg)

0

1

2

3

4

5

6

7

8

9

10

11

12

Nitr

ic O

xide

(gr/k

Wh)

1130 rpm, 100% Engine loadCalculated Values

0% EGR10% EGR20% EGR

Fig. 7a NO formation ‘history’ at 1130 rpm engine speed and 100% engine load for the case of 0, 10 and 20% EGR rate respectively.

EGR rate increases. The in-cylinder peak soot values increase considerably with EGR rate and are shifted to the right towards the expansion stroke. Moreover, a significant difference is observed in the soot oxidation mechanism when increasing EGR rate. The observed retardation of the soot oxidation mechanism, when using

160 180 200 220 240 260 280 300 320Engine Crank Angle (deg)

0

50

100

150

200

250

300

350

400

Soot

(mg/

m3 )

1130 rpm, 100% Engine loadCalculated Values


Fig. 7b Soot formation ‘history’ at 1130 rpm engine speed and 100% engine load for the case of 0, 10 and 20% EGR rate respectively.

EGR is attributed mainly to the less available oxygen and the lower in-cylinder gas temperatures [28,29]. The history of NO and Soot concentration during the close part of the cycle for all EGR rates considered at part load, is not shown in the present work due to space limitations. However the effect of EGR rate at part load is similar to the one described for the case of full engine load.

EFFECT OF EGR ON TEMPERATURE, EQUIVALE-NCE RATIO, NO AND SOOT DISTRIBUTION

One of the main advantages of the proposed model, compared to existing multi-zone phenomenological ones, is that it does not divide the in-cylinder gas mixture into regions with specific properties (i.e. no mixing between the zones, discrete fuel spray region, burned and unburned zones), but it computes the enthalpy, temperature and species concentrations at each computational cell, taking into consideration the heat and mass exchange between them. Obviously this provides a more realistic representation of the fuel-air mixing mechanism leading to a more fundamental understanding of the combustion and pollutant formation mechanism.

In the following paragraphs the spatial distributions of temperature, fuel equivalence ratio and emission concentrations (NO and Soot) are presented at certain time instants. This provides information concerning the evolution of the combustion mechanism and formation of pollutant emissions inside the combustion chamber. Furthermore this information is used to validate models ability to describe the effect of EGR on these parameters. Since no experimental data are available for

the spatial distribution of these quantities, the validation is qualitative, based on existing knowledge concerning the effect of EGR on combustion and pollutant formation mechanisms [6,9,12,15,28-32]. Moreover since the main scope of the present work is to present the ability of the proposed model to describe the effect of EGR on engine performance and emissions, and since the way that EGR affects combustion and pollutant formation is similar at part and full engine load (although the intensity of this effect differs), in the following paragraphs results are given for the spatial distribution only at full engine load.

Spatial Distribution of Temperature

In Fig. 8a the calculated in-cylinder temperature field at full engine load, for 0% EGR case, at 11 degrees CA ATDC, in a vertical plane through the center of the fuel spray is presented, together with the iso-curves for three values of the fuel equivalence ratio, namely Φ=0.5, 1.0 and 1.5. As observed, combustion has initiated in the region where the highest local temperatures exist (inside piston bowl, close to its boundaries), which coincides with the region where the gas mixture is slightly rich (close to stoichiometry). Moreover, it is shown that the temperatures near the cylinder boundaries are lower compared to the ones towards the center of the cylinder due to the heat exchange through the cylinder walls, and that near the nozzle exit a region exists with lower temperatures due to fuel evaporation.

40060080010001200140016001800200022002400260028003000

0.01 0.02 0.03 0.04 0.05 0.06

Radial Direction (m)

-0.01

Axi

al D

irect

ion

(m)

F=0,5F=1,0F=1,5

Temperature Fill Contours (Kelvin)Fuel Equivalence RatioLine Contours

Nozzle Exit

Piston BowlWall

Fig. 8a Spatial Temperature distribution in a vertical plane through the center of the fuel spray at 11 degrees CA ATDC, 1130 rpm engine speed, 100% load, 0% EGR rate.

In Fig. 8b, the corresponding temperature distribution is shown 21 degrees CA ATDC for the case of 0% EGR rate, at full engine load. At this time instant, higher local temperatures are observed due to the evolution of combustion, while the area where combustion takes place has expanded into the region above the piston crown. To investigate the effect of EGR rate on spatial temperature distribution, a comparison is made between the 0% EGR rate case (Fig. 8b) and the corresponding one for 20% EGR rate (Fig. 8c) at full engine load. As observed, although the temperature distribution is quite similar with and without EGR, a substantial reduction of peak combustion temperatures is noticed when 20%

EGR is used. Specifically, when 0% EGR rate is used the peak in-cylinder temperature is near 3000 Kelvin while at 20% EGR rate case, the corresponding value is

0.01 0.02 0.03 0.04 0.05 0.06


-0.02

-0.01

Axia

l Dire

ctio

n (m

)

40060080010001200140016001800200022002400260028003000

Temperature Fill Contours (Kelvin)

Nozzle Exit

Piston BowlWall

T=2700 Kelvin

T=2100 KelvinT=2400 Kelvin

T=3000 Kelvin

Fig. 8b Spatial Temperature distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load, 0% EGR rate.

0.01 0.02 0.03 0.04 0.05 0.06


-0.02

-0.01

Axia

l Dire

ctio

n (m

)

40060080010001200140016001800200022002400260028003000

Piston BowlWall

Temperature Fill Contours (Kelvin)

Nozzle Exit T=2100 Kelvin

T=1500 KelvinT=1800 Kelvin

T=2400 Kelvin

Fig. 8c Spatial Temperature distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load, 20% EGR rate.

near 2400 Kelvin. The main reason for the reduction of peak temperature with EGR is the replacement of fresh air with recirculated exhaust gas. This results to a reduction of local oxygen concentration (dilution effect), which consequently affects the combustion mechanism. Furthermore, the dissociation of combustion products (i.e. CO2 and H2O) introduced with EGR results to a further reduction of temperature.

A better understanding of the effect of EGR rate on the local temperatures inside the cylinder can be obtained by examining Figs. 9a-c. In these figures is given the comparison of the percent of the total mass, having a temperature within a specified range at each crank angle for 0%, 10% and 20% EGR, at full engine load. Figure 9a shows that as the EGR rate increases, the percentage of gas mixture having temperatures within the upper interval (2733 K-3000 K) decreases considerably. It is observed that for a 20% EGR, no portion of the gas mixture has a temperature within this

range. The latter one affects the mass percent of mixture having temperatures inside the next temperature ranges, i.e. (2466 K-2733 K) and (2200 K-2466 K) as shown in Figs 9b,c. As noted, the increase of EGR rate results to an increase of the percentage of gas having a temperature within the next temperature regions. This explains the fact that, although the peak local temperatures decrease as EGR rate increases, at the same time the mean cylinder temperature may increase.

170 180 190 200 210 220 230 240 250 260 270Crank Angle Degrees

0

1

2

3

4

5

6

7

8

9

10

Mas

s Pe

rcen

tage

(%)

Temperature Range2733-3000 Kelvin


Fig. 9a Predicted mass percentage of the gas mixture, having a temperature between 2733K and 3000K, for 0%, 10% and 20% EGR rates, at each crank angle.


0123456789

1011121314151617

Mas

s P

erce

ntag

e (%

)



Fig. 9b Predicted mass percentage of the gas mixture, having a temperature between 2466K and 2733K, for 0%, 10% and 20% EGR rates, at each crank angle.

Spatial distribution of Fuel Equivalence ratio

The reduction of oxygen concentration when using EGR obviously affects the local fuel equivalence ratio. For this reason, it is given in Figs. 10a,b the spatial distribution of fuel equivalence ratio inside the combustion chamber, for 0% and 20% EGR rates


0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

32

Mas

s P

erce

ntag

e (%

)



Fig. 9c Predicted mass percentage of the gas mixture, having a temperature between 2200K and 2466K, for 0%, 10% and 20% EGR rates, at each crank angle.

0.01 0.02 0.03 0.04 0.05 0.06


-0.02

-0.01

Axi

al D

irect

ion

(m)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

2.20

Piston BowlWall

Fuel Equivalence RatioFill Contours

Fig. 10a Fuel equivalence ratio distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 0% EGR rate.

0.01 0.02 0.03 0.04 0.05 0.06


-0.02

-0.01

Axi

al D

irect

ion

(m)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

2.20

Piston BowlWall

Fuel Equivalence RatioFill Contours

Fig. 10b Fuel equivalence ratio distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 20% EGR rate.

respectively, in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed and full engine load. Comparing Fig. 10a to Fig. 10b, it is observed that when EGR rate increases, the local values of fuel equivalence ratio increase inside the combustion chamber. The spatial distribution of fuel equivalence ratio seems to be similar for the two cases examined (0% and 20% EGR rate), but higher absolute values are observed for the 20% EGR rate case. This is expected to have a positive effect on NO formation (reduction) and a negative one on soot (increase), as shown in the next paragraphs.

Spatial distribution of NO concentration

In Figs. 11a,b the spatial distribution of NO concentration inside the combustion chamber is shown at 21 degrees CA ATDC for 0% and 20% EGR rate respectively, in a vertical plane through the center of the fuel spray, together with iso-contours of some characteristic temperatures, at full engine load. Comparing the absolute values of NO concentration, it is obvious that for the 20% EGR rate case the in-cylinder NO concentration is much lower than the corresponding one for 0% EGR. On the other hand, the shape of the region where NO is formed is almost similar for the two EGR rates. Moreover, taking into account the temperature iso-curves shown in the same

0.01 0.02 0.03 0.04 0.05 0.06


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Axi

al D

irect

ion

(m)

0.0E+000

1.0E-003

2.0E-003

3.0E-003

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5.0E-003

6.0E-003

7.0E-003

8.0E-003

9.0E-003

1.0E-002

1.1E-002

1800K2200K2800K

NO mass concentrationFill Contour Levels

Nozzle Exit T=2200 KelvinT=1800 Kelvin

T=2800 Kelvin

Temperature Line Contours

Piston BowlWall

Fig. 11a NO in-cylinder distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 0% EGR rate.

0.01 0.02 0.03 0.04 0.05 0.06


-0.02

-0.01

Axia

l Dire

ctio

n (m

)

0.0E+000

1.0E-004

2.0E-004

3.0E-004

4.0E-004

5.0E-004

6.0E-004

7.0E-004

8.0E-004

9.0E-004

NO mass concentrationFill Contour Levels

Nozzle Exit T=2200 KelvinT=1800 Kelvin

T=2800 Kelvin

Temperature Line Contours

1800K2200K2800K

Piston BowlWall

Fig. 11b NO in-cylinder distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 20% EGR rate.

figures, it is confirmed that the maximum NO concentration occurs in the region where the mixture gas temperature peaks. Thus, it is concluded that the increase of EGR rate affects the absolute values of NO concentration (through the reduction of gas temperature and available oxygen) and to a lesser extend the spatial distribution of NO.

Spatial distribution of Soot concentration

In Figs. 12a,b the corresponding spatial distribution of Soot concentration inside the combustion chamber is shown at 21 degrees CA ATDC for 0% and 20% EGR rates respectively, in a vertical plane through the center of the fuel spray, together with iso-contours of some characteristic fuel equivalence ratios. Considering Fig. 7b, it is revealed that the mean in-cylinder Soot concentration (at the same time instant) is near its peak value. Comparing Fig. 12a to Fig. 12b, it is observed that the shape of the region where Soot is formed is similar for the zero and 20% EGR cases, although the absolute values of Soot concentration are much higher for the latter case.

Moreover, comparing Figs. 11a,b with Figs. 12a,b it is observed that soot formation occurs in different areas

0.01 0.02 0.03 0.04 0.05 0.06


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Axi

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irect

ion

(m)

0.0E+000

1.0E-004

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3.0E-004

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5.0E-004

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8.0E-004

9.0E-004

F=0,5F=1,0F=1,5F=1,9

F=0,5F=1,0F=1,5

Fuel Equivalence RatioLine Contours

Nozzle Exit

Soot mass concentrationFill Contour Levels

F=1,5

Piston BowlWall

Fig. 12a Soot in-cylinder distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 0% EGR rate.

0.01 0.02 0.03 0.04 0.05 0.06

Radial Direction

-0.02

-0.01

Axi

al D

irect

ion

0.0E+000

2.0E-004

4.0E-004

6.0E-004

8.0E-004

1.0E-003

1.2E-003

1.4E-003

1.6E-003

F=0,5F=1,0F=1,5

Fuel Equivalence RatioLine Contours

Nozzle Exit

Soot mass concentrationFill Contour Levels

F=2,0

1800K2200K2800K

Piston BowlWall

Fig. 12b Soot in-cylinder distribution in a vertical plane through the center of the fuel spray at 21 degrees CA ATDC, 1130 rpm engine speed, 100% load and 20% EGR rate.

compared to NO (as it is expected [12]). The highest values of NO concentration occur inside the piston bowl (where the highest local temperatures are observed), while the peak values of Soot concentration are shifted towards the cylinder head (close to the region with the highest values of fuel equivalence ratio). This reveals the controversial mechanism of NO and Soot formation, which is obviously not affected by the use of EGR.

Temporal evolution of spatial in-cylinder distribution of NO and Soot concentration

One of the main advantages of the proposed model compared to existing multi-zone phenomenological ones is that it provides an estimation of the local distribution of pollutant emissions inside the combustion chamber, and how this distribution changes during the entire closed part of engine cycle. Thus a more fundamental understanding of the parameters affecting combustion and pollutant formation mechanism can be obtained, which is a prerequisite when investigating new techniques for engine development and pollutant emission reduction.

In Figs. 11a,b, 12a,b the in-cylinder spatial distribution of NO and Soot emissions are shown at a certain time instant after injection (21 CA ATDC) for the case of 0% and 20% EGR rate, at full engine load. However, to obtain a more detailed understanding of NO and Soot formation and how this is affected from the use of EGR, the temporal evolution of the spatial in-cylinder distribution of NO and Soot concentration is needed. To this scope, in Figs. 13a,b a comparison is made between the calculated spatial distributions of NO concentration inside the cylinder for the case of 0% and 20% EGR rate respectively, at 1130 rpm engine speed and full engine load. Spatial distributions are provided for several time instants from 11 degrees CA ATDC up to 47 degrees CA ATDC. This time interval covers a significant part of the NO formation history. Due to the considerably lower values of NO when using EGR we have used a different scale for the initial formation period up to 21 deg ATDC. Comparing Figs. 13a and 13b, it is observed that EGR does not affect the region where NO formation takes place, however it affects significantly the rate of NO formation. This is in accordance to what is expected, since NO formation is highly affected by the magnitude of the local temperature and oxygen concentration, which are both reduced by EGR as shown in the previous paragraphs. From the time instant corresponding to 27 degrees CA ATDC and then, the scale used for the contour levels of the figures 13a,b is common, and thus a more clear comparison between the spatial distribution of NO concentration for 0% and 20% EGR is possible. As observed in Figs. 13a,b, when using EGR, the region where NO is actually formed is significantly restricted compared to the non-EGR case. As combustion progresses, when no EGR is used (Fig. 13a), the region where NO is formed coincides with the region where combustion takes place and the local oxygen

Contour Level (for the following figures)

0.0E

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2.0E

-003

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-003

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0.01 0.02 0.03 0.04 0.05 0.06

11 CA ATDC

-0.01 Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

11 CA ATDC


0.01 0.02 0.03 0.04 0.05 0.06

17 CA ATDC

-0.01

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

17 CA ATDC

-0.01

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

21 CA ATDC

-0.02

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

21 CA ATDC

-0.02

-0.01

Piston BowlWall


0.0E

+000

2.0E

-003

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-003

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-003

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-002

1.2E

-002

1.4E

-002


0.0E

+000

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-003

4.0E

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-003

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-002

1.2E

-002

1.4E

-002

0.01 0.02 0.03 0.04 0.05 0.06

27 CA ATDC

-0.03

-0.02

-0.02

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-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

27 CA ATDC

-0.03

-0.02

-0.02

-0.01

-0.01

Piston BowlWall

Fig. 13a NO in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 0% EGR rate, at various time instants. (continued over)

Fig. 13b NO in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 20% EGR rate, at various time instants. (continued over)


0.0E

+000

2.0E

-003

4.0E

-003

6.0E

-003

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-002

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-002

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-002


0.0E

+000

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-003

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-002

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-002

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-002

0.01 0.02 0.03 0.04 0.05 0.06

31 CA ATDC

-0.02

-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

31 CA ATDC

-0.02

-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

37 CA ATDC

-0.03

-0.02

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

37 CA ATDC

-0.03

-0.02

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

41 CA ATDC

-0.03

-0.02

-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

41 CA ATDC

-0.03

-0.02

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

47 CA ATDC

-0.04

-0.03

-0.02

-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

47 CA ATDC

-0.04

-0.03

-0.02

-0.01

Piston BowlWall

Fig. 13a NO in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 0% EGR rate, at various time instants.

Fig. 13b NO in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 20% EGR rate, at various time instants.

concentration is high. On the other hand, when 20% EGR rate is used (Fig. 13b), although the region where combustion takes place is not significantly affected (e.g. Fig.11b), NO formation is reduced due to the lower local peak temperatures and oxygen availability. Moreover examining Fig.13a, it is noticed that after 27 degrees CA ATDC the local NO concentration starts to decline. This

is attributed to NO diffusion and to the chemical kinetic mechanism, in accordance to what is shown in Fig. 7a. On the other hand, at the same CA degree when 20% EGR rate is used, NO concentration is still increasing, because EGR shifts combustion towards the expansion stroke.


0.0E

+000

2.0E

-004

4.0E

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6.0E

-004

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0.01 0.02 0.03 0.04 0.05 0.06

11 CA ATDC


0.01 0.02 0.03 0.04 0.05 0.06

11 CA ATDC


0.01 0.02 0.03 0.04 0.05 0.06

17 CA ATDC

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Piston BowlWall

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Piston BowlWall

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Piston BowlWall

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21 CA ATDC

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

27 CA ATDC

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0.01 0.02 0.03 0.04 0.05 0.06

27 CA ATDC

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Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

31 CA ATDC

-0.02

-0.01

Piston BowlWall

0.01 0.02 0.03 0.04 0.05 0.06

31 CA ATDC

-0.02

-0.01

Piston BowlWall

Fig. 14a Soot in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 0% EGR rate, at various time instants.

Fig. 14b Soot in-cylinder mass concentration distribution in a vertical plane through the center of the fuel spray at 1130 rpm engine speed, 100% load and 20% EGR rate, at various time instants.

The corresponding evolution of soot spatial concentration is provided in Figs 14a,b for 1130 rpm and 100% load using 0% and 20% EGR rate respectively.

Comparing Figs. 14a,b it is observed that EGR does not affect the region where soot is formed, but has a significant effect on the magnitude of soot concentration. As combustion progresses until 21 degrees CA ATDC, it is observed that local peak soot concentration increases while the region where soot is formed expands for both EGR rates (0% and 20%). The local values of peak soot concentration are higher for the case of 20% EGR. These higher values can be attributed to the higher fuel equivalence ratio observed when using EGR as is shown in Fig. 10b. This time instant (i.e. 21 degrees CA ATDC) corresponds to the time when the maximum mean in-cylinder soot concentration is observed for the case of 0% EGR rate (as shown in Fig. 7b). After this point due to the high in-cylinder temperatures, and oxygen availability when 0% EGR rate is used, soot oxidation takes a predominant role leading to a decrease of local soot concentration. On the other hand, we have an opposite behavior when using 20% EGR. In this case (Fig. 14b) due to the lower local temperatures and the dilution effect of EGR, soot cannot be oxidized adequately, which results to higher soot concentration compared to the non-EGR case. (Fig. 14b, 27 and 31 degrees CA ATDC).

CONCLUSIONS

In this work a newly developed quasi-dimensional combustion model has been further improved, extending its applicability to cases where exhaust gas recirculation (EGR) is used to control NO emissions. To validate the model’s ability to predict the effect of EGR rate on engine performance and emissions, the application of “cool” EGR on a single cylinder HDDI turbocharged diesel engine has been considered. The model has been validated in the past on two different engine designs (an old technology naturally aspirated HSDI Diesel engine and a new technology turbocharged Heavy Duty DI one) managing to predict with reasonable accuracy engine performance and pollutant emissions at various engine operating conditions. In the present study to validate the model, three EGR rates are considered (0%, 10% and 20%), at two engine loads (part and full), at 1130 rpm engine speed. The experimental investigation was conducted at Daimler-Chrysler laboratories under EU funded project HEDE.

The comparison of calculated and experimental cylinder pressure traces has revealed a good agreement for all test cases examined. This indicates that the simulation manages to capture well the effect of EGR on the

combustion mechanism. Moreover, as far as NO and Soot emissions are concerned, comparing calculated with experimental tailpipe exhaust values, it can be concluded that for all test cases examined, the model predicts well the absolute values for NO emissions (although at part load relatively higher differences are observed), while the predicted Soot values reveal higher differences compared to the corresponding experimental ones. Nonetheless, the simulation manages to predict the overall effect of EGR, i.e. trends, on both NO and Soot emissions. This is encouraging even though a need for improving the soot formation model is recognized.

Moreover, the simulation provides detailed information concerning the spatial distribution of temperature, fuel equivalence ratio, NO and Soot concentrations inside the combustion chamber. This contributes to a better understanding of how EGR rate affects the combustion and pollutants formation mechanism. As revealed, the increase of EGR rate results to a decrease of local peak temperatures and local oxygen concentration (dilution effect) inside the combustion chamber. This has a positive effect on NO formation (reduction) and a negative one on soot (increase).

From this preliminary investigation it appears that the proposed model can be useful to examine the effect of EGR on engine performance and emissions, without any further tuning of its constants. This is encouraging, since it gives an alternative option to engine simulation, apart from the already used phenomenological and CFD models. The attractive feature of the proposed model compared to existing multi-zone ones is that it provides a realistic description of the air fuel mixing mechanism avoiding the use of correlations only. The latter ones usually suffer from the fact of not considering the mixing between the zones, a situation that is not close to reality. Owing to its structure, the proposed simulation is also suitable to examine multiple injection strategies, pilot and/or post injection. On the other hand, compared to detailed CFD models, the proposed one offers a rough only estimation of the flow field inside the combustion chamber, but its main advantage is the serious reduction of computational time that makes it suitable for cycle calculations. Therefore the proposed model appears to be a reasonable compromise between phenomenological and detailed CFD models.

Considering the present results, the need for further improvement and validation of the model is revealed. The authors are currently examining its application for predicting the effect of multiple injections on DI diesel engine performance and emissions.

NOMENCLATURE

A :Area An :Nozzle hole area cD :Nozzle discharge coefficient cp :Specific heat of the gas

D32 :Sauter Mean Diameter E :Activation energy h :Specific enthalpy of the gas or, Convection heat

transfer coefficient

k :Conduction heat transfer coefficient lchar :Characteristic length m :Fuel mass flow rate m :Mass Nzone :Number of droplets within each fuel spray zone P :Pressure r :Radial direction SΦ :Volumetric source rate t :Time Tcell :Gas temperature of a computational cell Twall :Temperature of the cylinder boundaries u :Radial component of gas velocity or, Fuel

injection velocity at the nozzle tip v :Circumferential component of gas velocity Vcell :Volume of a computational cell Vf :Volume of fuel injected per fuel injection w :Axial component of gas velocity wchar :Characteristic velocity Y :Mass concentration z :Axial direction zpiston :Distance between the gas face of the cylinder

head and the piston top

GREEK SYMBOLS

Γϕ :Diffusion coefficient ∆P :Pressure drop across the nozzle hole θ :Circumferential direction µ :Dynamic viscocity ρ :Density Φ :Fuel equivalence ratio Φ :General property in the conservation equation SUBSCRIPTS

air :Air EGR :Exhaust Gas Recirculation fv :Fuel vapor ign :Ignition mix :Mixture ox :Oxygen DIMENSIONLESS GROUPS

Re :Reynolds number Pr :Prandtl number

ABBREVIATIONS

ATDC :After Top Dead Centre CA :Crank Angle DI :Direct Injection EGR :Exhaust Gas Recirculation HSDI :High Speed Direct Injection HDDI :Heavy Duty Direct Injection NO :Nitric Oxide rpm :Revolutions per minute

REFERENCES

1. Weissbeck, H., “Technologies That Will Improve Diesels”, presentation at SAE Congress 2002 Executive Panel :” The Diesel Engine of Tomorrow”, Detroit, MI, 2002

2. Foster, D.E., “Competition To The Diesel Engine?”, presentation at SAE Congress 2002 Executive Panel: ” The Diesel Engine of Tomorrow”, Detroit, MI, 2002

3. Moser, F.X., Sams, T. and Cartellieri, W., "Impact of Future Exhaust Gas Emission Legislation on the Heavy Duty Truck Engine", SAE Paper No 2001-01-0186

4. Timothy V. Johnson, "Diesel Emission Control Technology –2003 in Review", SAE paper No 2004-01-0070

5. Assessment and Standards Division Office of Transportation and Air Quality U.S. Environmental Protection Agency, "Highway Diesel Progress Review Report 2", EPA420-R-04-004, March 2004

6. Hountalas, D.T., Benajes, J., Pariotis E.G. and Gonzalez, C. A., "Combination of High Injection Pressure and EGR to Control Nitric Oxide and Soot in DI Diesel Engines", THIESEL 2004 Conference on Thermo and Fluid Dynamic Processes in Diesel Engines

7. Tow, T.C., Pierpont, D.A. and Reitz, R.D., “Reducing Particulate and NOx Emissions by Using Multiple Injections in a Heavy Duty D.I. Diesel Engine”, SAE Transactions paper No 940897

8. Hountalas D.T., “Available Strategies for Improving the Efficiency of DI Diesel Engines-A Theoretical Investigation”, SAE paper No 2000-01-1176

9. Kouremenos D.A., Hountalas, D.T. and Binder K.B., “The Effect of EGR on the Performance and Pollutant Emissions of Heavy-Duty Diesel Engines Using Constant and Variable AFR”, SAE Transactions paper No 2001-01-0198

10. Tomohiro Kanda, Shinichi Kobayashi, Ryuta Matsui and Hiroshi Sono, "Study on Euro IV Combustion Technologies for Direct Injection Diesel Engine", SAE paper No 2004- 01-0113

11. Jeffrey A. Leet, Stefan Simescu, Kent Froelund,Lee G. Dodge and Charles E. Roberts, "Emissions Solutions for 2007 and 2010 Heavy-Duty Diesel Engines", SAE paper No 2004-01-0124

12. Heywood, J.B., Internal Combustion EngineFundamentals, McGraw-Hill, New York, 1988

13. Pariotis, E.G. and Hountalas, D.T., “A New Quasi-Three Dimensional Combustion Model for Prediction of DI Diesel Engines’ Performance and Pollutant Emissions”, SAE Transactions, paper No 2003-01-1060

14. Pariotis, E.G. and Hountalas, D.T., "Validation of a Newly Developed Quasi-Dimensional Combustion Model – Application on a Heavy Duty DI Diesel Engine", SAE Transactions, paper No 2004-01-0923

15. Ladommatos, N., Abdelhalim, S. and Zhao, H., "The effects of exhaust gas recirculation on diesel combustion and emissions", International Journal of Engine Research, Vol. 1, no. 1, (2000)

16. Hountalas, D.T, Pariotis, E.G, “A Simplified Model for the Spatial Distribution of Temperature in a Motored DI Diesel Engine”, SAE Transactions, paper No 2001-01-1235

17. Vickland, C.W., Strange, F.M., Bell, R.A. and Starkman, E.S., “A consideration of the high temperature thermodynamics of internal combustion engines”, SAE Transactions, 70, 785-793

18. Bo, T., Clerides, D, Gosman, A. and Theodossopoulos, P., “Prediction of the Flow and Spray Process in an Automobile DI Diesel Engine”, SAE paper No 970882

19. Crowe, C., Sharama, M. and Stock, D., “The Particle-Source-in-Cell (PSI-Cell) Model for Gas-Droplet Flows”, ASME 75-WA/HT-25

20. Griffin, M.D., et al., “Computational Fluid Dynamics Applied to Flows in an Internal Combustion Engine”, AIAA, paper 78-57

21. Ahmadi-Befrui, B., Gosman, A.D., Issa, R.I. and Watkins, A.P., “EPISO – Implicit non-iterative solution procedure for the calculation of flows in reciprocating engine chambers”, Computer Methods in Applied Mechanics and Engineering, Vol. 79, pp.249-279, 1990

22. Nishida, K., and Hiroyasu, H., “Simplified Three-Dimensional Modeling of Mixture Formation and Combustion in a D.I. Diesel Engine,” SAE Transactions, paper No 890269, 1989

23. Hiroyasu, H. and Arai, M., “Fuel Spray Penetration and Spray Angle of Diesel Engines”, Transactions of JSAE, Vol. 21, pp.5-11, 1980

24. Jung, D. and Assanis, D., “Multi-Zone DI Diesel Spray Combustion Model for Cycle Simulation Studies of Engines Performance and Emissions”, SAE paper 2001-01-1246

25. Borman, G.L. and Johnson, J.K., “Unsteady Vaporization Histories and Trajectories of Fuel Drops injected into Swirling Air”, SAE paper

598C,1962

26. Wolfer, H.H., “Ignition Lag in Diesel Engines”, VDI-Forschungsheft 392, 1938; Translated by Royal Aircraft Establishment, Farnborough Library No. 358, UDC 621-436.047, August 1959

27. Zhu, Y., Zhao, H., Melas, D.A. and Ladommatos, N., "Computational study of the effects of the geometry of the piston bowl pip for a high-speed direct injection diesel engine", Proc Instn Mech Engrs, Vol 218, Part D, (2004)

28. Ming Zheng, Graham T. Reader and J. Gary Hawley, "Diesel engine exhaust gas recirculation -a review on advanced and novel concepts", Energy Conversion and Management, Vol 45, pp. 883-900, (2004)

29. Abd-Alla, G. H., "Using exhaust gas recirculation in internal combustion engines: a review", Energy Conversion and Management, Vol 43, pp. 1027-1042, (2002)

30. Timothy Jacobs, Dennis Assanis and Zoran Filipi, "The Impact of Exhaust Gas Recirculation on Performance and Emissions of a Heavy-Duty Diesel Engine", SAE paper No 2003-01-1068

31. Lapuerta, M., Hernandez, J.J. and Gimenez, F., "Evaluation of exhaust gas recirculation as a technique for reducing diesel engine Nox emissions", Proc Instn Mech Engrs, Vol 214, Part D, (2000)

32. Z. Gao and W. Schreiber, "The effects of EGR and split fuel injection on diesel engine emission", International Journal of Automotive Technology, Vol. 2, No. 4, pp. 123-133 (2001)

33. Kouremenos, D.A., Rakopoulos, C.D., and Hountalas, D.T., “Multi-Zone Combustion Modeling for the Prediction of Pollutants Emissions and Performance of DI Diesel Engines”, SAE Transactions, paper No 970635, 1997

34. Rakopoulos, C.D., and Hountalas, D.T., “Development and validation of a 3-D multi-zone combustion model for the prediction of DI diesel engines performance and pollutants emissions”, SAE Transactions, paper No 981021, 1998

35. Feng Tao, Sukhin Srinivas, Rolf D. Reitz, and David E. Foster, "Current status of soot modeling applied to diesel combustion simulations", International Symposium COMODIA 2004

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