Hydrogen Engines

8/14/2019 Hydrogen Engines

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Paper Code: F02V102

HYDROGEN FUELED ENGINE PROPERTIES OF WORKING CYCLE ANDEMISSION POTENTIALS

Polek, Milo*

Macek, Jan

Takts, Michal

Josef Boek Research Center, Czech Technical University in Prague, Czech Republic

KEYWORDShydrogen combustion, NOx formation, simulation, computational fluid dynamics, experiments

ABSTRACTThe paper deals with the application of advanced numerical methods to modeling of hydrogen fueled engines. Asensitivity study of the influence of main engine parameters on NOx formation has been performed using the GT-Power

code. A general CFD algorithm based on the previously published Advanced Multizone Eulerian Model has been

adapted to detailed simulation of in-cylinder phenomena of the hydrogen engine. Semi-empirical combustion model

breaking connection between chemistry and turbulence has been proposed. Procedure of the model parameter

identification according to experimental data has been verified. Combination of the model with complex description of

chemical kinetics of both fast reactions and slow ones is shown. Possibilities of the chemical kinetics application to the

semi-empirical model parameter estimation are discussed.

INTRODUCTIONAs reserves of fossil fuels have decreased, alternative fuels as well as alternative power sources have become more and

more important. It is necessary to find such fuel or power source, which is able to meet all current and future

requirements concerning friendliness to the environment and reasonable overall net efficiency of energy transformation.

Recently, a lot of work has been done on development of fuel cells (FC). The fuel cells represent an alternative power

source using hydrogen as the primary source of energy. Unfortunately, the time when the fuel cells will be fully

prepared and competitive with current internal combustion (IC) engines seems to be rather far-off. Moreover, specific

energy referenced to weight (or volume) and costs are still inconvenient compared to those of IC engines. Therefore, it

is necessary to fill the gap until they are widely applicable and to accelerate infrastructure building in the meantime.

The fueling of classical IC engines with hydrogen represents the other possibility of hydrogen utilization as the

alternative renewable fuel. It is a very convenient fuel for reciprocating engines, which is able to fulfill all future

requirements concerning emission formation and engine efficiency. It has strong advantages since it can be used in the

classical IC engine without considerable change in the basic design concept. Nevertheless, it seems that the hydrogen

engine should be completely re-designed concerning fuel/air mixing, combustion, exhaust gas aftertreatment and

turbo/super charging if the potentials are to be fully utilized. The problems of fuel storage and availability, i.e.

necessary infrastructure, are not discussed in the paper. The change of fuel via ICE hydrogen ICE hydrogen FC

seems to be competitive to the currently used ICE reformer methanol/gasoline FC hydrogen FC. In the latter pattern many advantages of FC, namely high efficiency and no CO2 emission, are lost due to the reforming of

significant carbon content fuels such as methanol or hydrocarbons with unused chemical energy of carbon oxidation.

PROBLEM DESCRIPTIONThe main topic of the work is the general simulation of thermodynamic cycle of a hydrogen engine and detaileddescription of in-cylinder phenomena. Concerning the hydrogen engine simulation, uniqueness of the hydrogen fuel has

to be taken into consideration. Hydrogen has a broad limit of flammability. The high molecular diffusivity causes the

extremely lean hydrogen mixture to be flammable and hydrogen combustion to be fast enough to achieve reasonable

engine efficiency. The possibility of the extremely lean mixture use represents a strong advantage from the point of

view of NOx formation because of low in-cylinder temperature preventing from thermal NO x formation. The high

hydrogen molecule mobility means that molecular diffusion can not be neglected since it has comparable influence oncombustion and flame front propagation velocity as turbulent transport phenomena. It brings about high demands on the

formulation of simulation models.

The influence of the main engine parameters, i.e. air excess, spark timing, etc., on engine efficiency and NOx formation

has been investigated using a 0-D model. In the case of the hydrogen engine, combustion products are composed of ahigh amount of water vapor, oxygen if lean operation is assumed and nitrogen oxides. This is the reason why strongemphasis has been put on the simulation capability of engine emission characteristics in the model. In general, 0-D


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models are not capable of detailed modeling of in-cylinder phenomena such as the influence of interaction of velocityfield and concentration field on combustion. Nevertheless, those models provide the comprehensive and efficient tool

which is well suited in general engine simulations focused on full-engine simulations, extrapolation of results to other

cases of interest, etc.

A general CFD code has been proposed to detailed simulation of in-cylinder phenomena of the hydrogen engine. The

CFD methods are capable of providing detailed information on concentration, temperature and velocity field in thecylinder but they are very demanding as regards physical sub-model formulation and numerical solution. It is necessary

to use quite a wide model considering not only flow phenomena but also turbulent transport phenomena. In the case of

the hydrogen fueled engine simulation, the multidimensional algorithm has to be able to properly capture fast

combustion including effect of turbulence.

Most numerical experiments have been performed on 1-cylinder experimental engine with the variable compressionratio. This engine has been redesigned for operating with hydrogen fuel. Hydrogen is injected directly into the cylinder.

Base engine parameters are shown in table 1. Integral parameters of the engine operating prevailingly with extremely

lean mixture and in-cylinder pressure have been measured [1]. All experiments have been done at the Technical

University of Liberec.

bore 82.5 mm

stroke 114.3 mm

compression ratio 10

engine speed 910 r.p.m.

aspiration natural

mixture formationdirect injection,

electromagnetic valve

Table 1: Main parameters of the investigated engine

AIMS OF THE WORKThe aims of the work presented can be summarized as follows:

modeling of the influence of the main engine parameters on NOx formation and engine efficiency finding compromise between engine efficiency, specific power and NOx formation formulation of simplified combustion model to be employed inside the CFD simulation formulation of a methodology of the model parameter identification using experimental data involvement of chemical kinetics and its application to hydrogen combustion verification of numerical procedures with respect to stiff chemistry involvement verification of possibility to use the chemistry to the simplified model parameter correctionTHEORETICAL BACKGROUNDTwo models of a different level have been used to simulation of phenomena connected to the hydrogen fuel use. The

GT-Power code [2] - has been employed as the very efficient tool for performing detailed analysis of the influence of

main engine parameters on working cycle. The CFD algorithm based on the AMEM [3] - has been used to detailed

modeling of in-cylinder phenomena including influence of flow, temperature and concentration field. The main stress

has been put on the capability of modeling of NOx formation.

The most crucial points of the hydrogen engine simulations are the modeling of combustion and correct treatment ofmixture properties. The combustion model parameters have been chosen according to the experimentally obtained rate-

of-heat-release [1]. Dealing with hydrogen combustion in general, it is necessary to take into account the high amount

of water vapor in combustion products, i.e., exhaust gases, which calls for the involvement of a real gas model into the

algorithms. Nevertheless, perfect gas state equation in combination with temperature dependent heat capacities has beenused in both numerical simulations and indicator diagram analysis. The same assumption used somewhat compensates

the error caused by the real gas properties neglecting. However, the CFD algorithm is fully prepared for the

involvement of the real gas state equation.

Modeling of influence of main engine parametersThe GT-Power code has been used to modeling of the 1-cylinder hydrogen fueled engine in order to simulate the

experimental setup so that the model parameters can be corrected according to experimental data. It is important from

the point of view of model use to the extrapolation to other cases of interests and, mainly, the model application to full-

cylinder engines. The GT-Power code represents typical 0-D code, which is commonly used to engine simulation, but itcombines the 0-D approach to in-cylinder phenomena modeling with 1-D model of pipes. It enables us to formulate the

engine layout in a very comprehensive manner.


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The combustion has been modeled using a standard way applying Wiebes law to a description of rate-of-heat-release.

As has been already stated, parameters of the combustion model have been chosen according to the experimentally

obtained rate-of-heat-release patterns. The attention has been paid mainly on correct modeling of the combustion

duration because only simple Wiebes law has been used to model rate-of-heat-release as no significant after-burning is

observed. The NOx formation has been modeled using the extended Zeldovich reaction mechanism. The experimental

engine is equipped with the direct fuel injection but only operation regimes with lean homogenous mixture have beenconsidered up to now. Considering the stratified charge combustion, it is possible to perform only rough check of NO xformation using adjustment of the combustion model parameters.

Detailed modeling of in-cylinder phenomena

The Advanced Multizone Eulerian Model (AMEM) has been used as the basis for detailed modeling of in-cylinder

phenomena. The AMEM represents the general method of computational fluid dynamics. The model has beenformulated with respect to simulation of specific phenomena in a cylinder of a combustion engine. It is based on the

integral form of the general budgeting equation taking into account moving boundaries of a computed domain. The

equation yields:

( ) ( ) D-P+dAnj+An).w-w(s-=dVs

dt

dj,j,s

A

GF

VAV jjjj

ffdrrr

r

rrr

=

(1)

=jV

dVsF r (2)

The equation (1) is written for arbitrary bulk quantity F. The moving boundaries are respected inside (1) by term

defining convective flux in which relative velocity on a domain interface appears. In this term, wF denotes fluid

(material) velocity and wG denotes grid velocity, i.e. velocity of the moving boundary. The equation (1) creates the

basis for a formulation of laws of conservation because bulk quantity F denotes mass of specie, energy, etc. The eq. (1)

involves diffusion fluxesjs and both dissipation and production termsP, D.

The model uses an approach of finite volumes. It means that computational domain is divided into sub-volumes and all

quantities are solved locally. The specific budgeting equations are deduced from (1) since the integral form of (1)

matches the finite volume approach. The system of laws of conservation is not sufficient for solution and the algorithmis amended for closure formulae and for additional sub-models for simulation of combustion, heat transfer via cooled

walls, etc. The model is not described here in detail. For a more detailed description see [3], [4]. Only the description of

combustion sub-model and way of chemical kinetics involvement are done below.

Two-parameter model of turbulent hydrogen flame

A semi-empirical model similar to the PDF one has been used as the basis for simulation of the turbulent premixed

flame. The combustion model assumes local amount of unburned fuel in every finite volume as the main reaction

variable. The model breaks connection between stiff chemistry and turbulence. It seems to be very important feature

considering strong uncertainties due to the choice of the turbulence model parameters which significantly affect

combustion. In spite of the fact that the model does not need local turbulence parameters, it is able to treat turbulent

flame correctly. The reason for this is that the parameters of the semi-empirical model are chosen according toexperimental measurements done on real-world engines so that it involves correctly the influence of turbulence on

combustion.

The first parameter of the model characterizes

flame front velocity propagation. In fact, the

knowledge of the flame front velocity propagation

is not the correct parameter for combustion

modeling because the instantaneous flame front

position including a flame front wrinkling is

needed. Nevertheless, it seems difficult to

formulate such a comprehensive model and,

therefore, the flame front is assumed to be

hemispherical. The second parameter of the

combustion model defines local burning time. The

local burning time has influence on the width ofthe reaction zone see fig. 1.

Dyfl

burned

unburnedreaction zone

wfl

ad

dQ

flw

a

a

Fig. 1: Turbulent flame scheme.


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The flame front propagation velocity is chosen according to the experimentally obtained rate-of-heat-release patterns.

Assuming constant net heating value of the fuel, it is easy to determine amount of burnt mixture as a function of time,

i.e., crank angle. If homogeneous state in the cylinder during combustion is further assumed, i.e., only one zone model

is employed, the volume of the burned mixture is defined by simple formula:

cylburned

cyl

mixture

burned VxVxmV == ,

0,

r(3)

In this formula, mass of burned mixture is defined using Wiebes law and initial mass of mixture in the cylinder. Hence,

the mass of unburned mixture is defined by product ofxand mmixture,0. Vcyland rcylmean instantaneous cylinder volumeand cylinder charge density. In presented computations, the shape of the flame front is assumed to be hemispherical so

that the burned mixture volume is Vburned=f(r3), where rdenotes radius of the flame front. The velocity of flame front

can be written in simple form:

( )aaaa d

dxV

d

dVx

d

dV

d

dV

rn

dt

drcyl

cylburnedburned+== ,

3

16

2(4)

where formula da=6.n.dtis employed in (4). The equation (4) is valid only at the first stage of combustion until flamereaches the piston, at later stages more complicated geometry has to be taken into account. The presented proceduredescribes the simplest way of the flame front propagation velocity identification. It is applicable provided that either the

rate of oxidized reactants, i.e., fuel, is known or the fuel heating value is assumed to be constant. Practically, the rate-of-

heat-release patterns are known only and it is necessary to correct heat released during combustion to instantaneous in-

cylinder temperature. It calls for the employment of a 0-D code being able to simulate the high-pressure part of the

engine cycle. In fact, the procedure is somewhat inverse to the indicator diagram analysis.

The described procedure enables us to estimate one of the combustion model parameters only. The second one remains

unclear because it requires more detailed experimental data and a more sophisticated model of turbulent flame. As has

already been stated, the second parameter defines local combustion time. In fact, the parameter defines the width of the

reaction zone Dyfl see scheme in fig. 1. The time dependency of the reaction zone width has to be taken into accountfor solution of the rate-of-heat-release.

( )==

D==

)()( tfV

flflu

tfV

flucomb

flfl

yAdHdt

ddVH

dt

d

dt

dQrr (5)

The local burning time can be solved employing (5) but information concerning the reaction zone width achieved, e.g.,

by means of measurements on transparent engine is needed. It is possible to improve the whole procedure using the

flame front velocity measured by the means of ionization probe, etc. In presented simulations, the local burning time,

respectively local burning angle, has been chosen so that smooth enough solution is obtained on a relatively coarse

mesh because of lack of pertinent experimental data. Computations show good qualitative agreement of obtained flame

front velocity, i.e., observed velocity, with published data [5]. The observed velocity is going down towards the end of

combustion. The burning velocity should be slightly increasing but it is kept constant since the lack of experimental

data. Nevertheless, the general rules concerning the second model parameter determination are being prepared on the

basis of the chemistry modeling and published results for hydrocarbon fuels. Unfortunately, the unique features

connected with the hydrogen fuel utilize do not permit direct use of the models based on hydrocarbon combustion

simulations. The possibility of the use of the detailed chemistry solution to the model parameter identification is

discussed further.

The simplified combustion model uses two-parameters but it is obvious that one more definition still remains open. To

close the model, it is necessary to define local rate-of-progress-variable for solution of the local rate-of-heat-release in a

finite volume which is affected by flame. The local burning rate has to respect time history of combustion and mixture

transport through the finite volume interface. In the presented work, the local burning rate has been solved using a

function similar to the Wiebes one. However, corrections according to amount of combustion products in a finite

volume, e.g., carbon dioxide, water vapor, may be taken into account if the time history is treated properly. It means

that combustion products can be used as the marker to what extent combustion has been completed in any particular

time and as the rough scale of radicals concentration. The model does not require any other transported quantity, such as


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quantity characterizing local cumulative ignition delay time, since the instantaneous flame front position is fully definedand flame development is not directly modeled.

Formulation of the model based on detailed chemistry description

The chemical kinetics is involved into the algorithm in order to simulate NOx formation. However, full reaction

mechanism describing the hydrogen combustion has been employed to test the algorithm for future possibility of using

the chemical kinetics model as the predictive one being able to solve the flame front propagation. The chemistry issolved in a standard manner using Arrhenius law. Assuming arbitrary i-th elementary reaction of a reaction mechanism

( )I1,...,i1

''

,

1

'

, ===

K

k

kik

K

k

kik cucu (6)

where nk,iis stoichiometric coefficients and ck is the chemical symbol of the k-th specie. The production rate of the k-thspecie can be solved as a summation of rate-progress-variables for all reactions involving k-th specie.

( ) ' ,''

,,

1

, ,K1,...,k, ikikik

I

i

iikk

k qdt

dCuuuuw -====

=

& (7)

The rate of progress variable qiis given by the forward and reverse rate of the reaction:

K

kkeTAkCkCkq

if

irRT

E

iif

K

k

kir

K

k

kifi

i

iikik,

,,

1

,

1

, ,,'',

',

==-=

-

==

buu

(8)

Ckdenotes molar concentration ofk-th specie, kr,iand kf,iare the reverse and forward constants ofi-th reaction,Kis theequilibrium constant. As for numerical procedure used to solution of the chemical production rates, the chemistry is

involved into the AMEM in an automated way using the CHEMKIN-III solver [6]. Reactions considered are shown

table 1. The reaction mechanism has been chosen according to [7]. The suitability of the mechanism for the internalcombustion engine simulation has to be further proven.

OH+H2=H+H2O O+OH=O2+H O+H2=OH+HH+O2(+M)=HO2(+M) H+O2(+N2)=HO2(+N2) H+O2(+H2)=HO2(+H2)

H+O2(+H2O)=HO2(+H2O) OH+HO2=H2O+O2 H+HO2=OH+OH

H+HO2=H2+O2 H+HO2=O+H2O O+HO2=O2+OH

OH+OH=O+H2O H+H+M=H2+M H+H+H2=H2+H2

H+H+H2O=H2+H2O H+OH+M=H2O+M H+O+M=OH+M

O+O+M=O2+M HO2+HO2=H2O2+O2 OH+OH(+M)=H2O2(+M)

H2O2+H=HO2+H2 H2O2+H=OH+H2O H2O2+O=OH+HO2

H2O2+OH=H2O+HO2 O+N2=NO+N N+O2=NO+O

OH+N=NO+H

Table 2: List of reactions considered in the hydrogen combustion simulations.

The chemistry has been used to modeling of NOx formation up to now but the code is fully prepared for solution of the

rate-of-heat-release and flame front velocity propagation using chemical kinetics only. It means that the reaction

mechanism consists of both slow reactions and fast ones. The rate-of-heat-release can be solved using production rates

wkand internal energy including the heat-of-formation of species hk:

=

-=

K

k

Kk

mixture

chem hmdt

dQ

1

1w& (9)

The combustion model based on the chemical kinetics brings about high demands not only on the chemistry formulation

but it calls for the involvement of proper modeling of turbulent transport phenomena. It seems to be an even more

problematic issue in the case of the internal combustion engine simulation. In presented simulations, the turbulence

phenomena has been modeled using simple assumption of equal transport of all by turbulence transported quantities. It

means that the Prandtl number and the Schmidt one are assumed to be equal to unity. The dynamic viscosity used insidethe AMEM denotes the effective one and it is chosen being at 2-3 orders of magnitude higher than the molecularviscosity of air. The way of turbulence model involvement does not restrict physical interpretation of the combustion


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model since the semi-empirical combustion model involves influence of turbulence on the flame front propagation but itmay lead to misinterpretation regarding transport phenomena solution.

NOxformation simulation

The NOx formation is solved in a standard manner using extended Zeldovich chain mechanism. The mechanism is

employed in order to simulate formation of the thermal NOx.

O + N2 = NO + N

N + O2 = NO + O

OH + N = NO + H

Proper simulation of the thermal NOx formation is important in the case of the hydrogen-fueled engine since a

formation of prompt NOx can be neglected because of the lack of HC radicals [10].

The main problem connected to the NOx formation modeling arises from the characteristic time of the slow NO xformation reactions. The slow kinetics requires solving of the stiff and computationally demanding chemistry much

longer time than it is necessary to solve the combustion to be able to predict the NOx concentration in the exhaust.

Code construction

The chemical kinetics involvement brings about problems withnumerical solution due to significant stiffness of the obtained

equation set. This is reason why chemical kinetics equations are

integrated independently of the base algorithm using specialized

stiff solver. In this case, LSODE and DVODE procedures areimplemented [8]. The code is divided into two threads which

are driven by common time driver, i.e., engine crank. The strong

advantage of the chemical kinetics involvement is also

possibility to correct the rate-of-heat-release to dissociation

reactions and products of incomplete combustion.

Concerning the numerical integration of the flow phenomena and

the transport phenomena, convective terms are discretized using

up-wind or central differences. Therefore, the order of accuracyin space is of 1

stone for the up-wind scheme and 2

ndone for the

central difference scheme. The diffusion terms are of 2nd

order in

space. The order of accuracy in time is given by the numericalprocedure employed. The multi-stage Runge-Kutta method of 2

nd

and 4th

order in time has been used up to now.

It is necessary to stress that the numerical procedure has quite a

significant impact on the physical interpretation of results,

mainly that of the transport phenomenon solution. It is caused

because of the necessity to add an artificial viscosity into the

numerical algorithm to get stable and non-oscillatory solution.

The effect is important especially in the case of lower order

schemes. The numerical diffusion may strongly affect the flamefront propagation and the reaction zone width mainly in the case

of detailed chemistry solution because the artificial transport is

often comparable to the turbulent one. The influence of the numerical scheme construction is higher if a coarse mesh is

used.

DISCUSSION OF RESULTSAll simulations have been performed on 1-cylinder engine. The engine parameters have been chosen to simulate the

experiments. The naturally aspirated engine has been considered up to now. As stated above, the experimental engine is

equipped with the direct fuel injection system enabling the stratified charge combustion but the premixed charge

combustion has been assumed in all simulations. This restriction is done due to capabilities of the used combustion

models. However, hydrogen is injected directly into cylinder in both the stratified mixture combustion and premixed

mixture combustion and the only difference is in the injection timing. In the case of the premixed mixture operation, the

fuel is injected during the intake stroke and compression one to assure sufficient mixing time for the nearlyhomogeneous mixture formation. This regime is designated as early injection further.

initial conditions+

boundary conditions

conservation of species

3 species solved

conservation of

momentum

conservation of energy

combustion model conservation of species

13 species solved

convection and

diffusion considered

only

chemical kinetics

numerical integration


kinetics only

time driver


combustionmodelcorrection

dissociation,

incomplete

combustion

Fig 3: Scheme of the code construction.


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The CFD simulations have considered very simple geometry of the modeled cylinder. The flat piston and cylinder head

have been assumed. The simple geometry has been used in order to eliminate influence of complicated numerics. It

enables easier interpretation and better understanding of results. Nevertheless, the model is not limited to the simple

geometry at all. Despite the simple geometrical setup, the simulations are quite comprehensive because combustion,

heat transfer via cooled walls, heat conduction, diffusion and chemistry have been considered.

Basic results of 0-D simulations are presented in the paper only. These results show the influence of the start of

combustion and air excess on engine parameters. More detailed description of results can be find in [9]. The main

attention is paid to the multidimensional computations in this section. Both models of completely different levels have

been combined and the 0-D simulations have been used to determine initial and boundary conditions of the CFD

algorithm.

Results of the GT-Power simulations

The influence of spark timing, respectively start-of-combustion, is shown in figs. 4, 5 and 6. All simulations have been

performed at constant air excess of 2. Start-of-combustion angle has a very strong impact on NOx formation due to the

decreasing in-cylinder temperatures if retarding spark advance timing see fig. 4. Figs. 5 and 6 show typical

dependencies of indicated mean effective pressure and indicated specific fuel consumption on the start-of-combustion

angle. These dependencies clearly demonstrate that optimal spark timing is very close to TDC because of fast

combustion, i.e. short combustion duration.

Fig 4: Influence of start of combustion on NOx production.

Air excess of 2, compression ratio of 10, 910 r.p.m.,

homogeneous charge combustion. Comparison of

computed and measured data.

Fig 5: Influence of start of combustion on i.m.e.p. Air

excess of 2, compression ratio of 10, 910 r.p.m.,



Fig 6: Influence of start of combustion on i.s.f.c. Air

excess of 2, compression ratio of 10, 910 r.p.m.,



Fig 7: Influence of air excess on NOx production. Spark

advance of 5 degCA BTDC, compression ratio of 10, 910

r.p.m., homogeneous charge combustion (early injectiontiming). Experimental results of stratified mixturecombustion are also plotted (late injection timing).

Comparison of computed and measured data.

The influence of air excess at constant spark timing of 5 deg CA BTDC is shown in figs. 7, 8 and 9. In fig. 7 the

comparison of computed and measured NOx concentration in exhaust gases is presented. Two cases have beenexamined experimentally premixed mixture combustion and stratified mixture one. Only the premixed mixture

combustion has been considered in simulations but, in principle, it is also possible to model the latter one using


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corrected rate-of-heat-release patterns inside the GT-Power model. Results show very strong dependence of NO xformation on air excess. Higher concentrations of NOx for stratified combustion have been observed due to faster

combustion accompanied by higher in-cylinder temperatures. The predicted NOx emissions on a specific scale are

shown in table 2. The specific NOx emissions are referenced to the indicated engine power.

air excess [1] 1.4 1.6 1.8 2

NOx [g.kW-1

.h-1

] 46.7 11.25 2.02 0.28Table 3: Specific NOx emissions referenced to indicated engine power

Comparison of computed and measured indicated mean effective pressure is shown in fig. 8. The naturally aspiratedengine has been considered in all simulations. Thus, low indicated mean effective pressure has been achieved

considering lean mixture operation. In fig. 9, the influence of air excess on indicated specific fuel consumption is

presented. A difference between computed and measured data has appeared. The predicted indicated specific fuel

consumption has been optimistic compared to the measured one. It can be corrected by further tuning of model

parameters (heat transfer coefficients, etc.).

Fig 8: Influence of air excess on i.m.e.p. Spark advance of

5 degCA BTDC, compression ratio of 10, 910 r.p.m,



Fig 9: Influence of air excess on i.s.f.c. Spark advance of 5

degCA BTDC, compression ratio of 10, 910 r.p.m.,



Results of the detailed in-cylinder phenomena modeling

The results of the multidimensional simulations document mainly the state-of-the-art of the model development. In

addition, they clearly demonstrate unique properties of hydrogen which have to be treated not only inside a numericalmodel but also in the case of real-word hydrogen fueled engines.

The combustion model parameters has been identified using experimentally obtained combustion duration but the rate-

of-heat-release has been interpolated using the Wiebes function. It is not necessary but it keeps the whole procedure

simple and it does not impact the result quality and the stage of the model development.

Fig 10: Rate-of-heat-release pattern. The AMEM

simulation.

Fig 11: In-cylinder pressure pattern and temperature

pattern. The AMEM simulation.


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crank angle of 178 deg. CAcrank angle of 190 deg. CA

crank angle of 180 deg. CA (TDC)crank angle of 192 deg. CA

crank angle of 182 deg. CA







crank angle of 200 deg. CAFig 12: Mass fraction of fuel in cylinder during combustion. Start of combustion at 5 degCA BTDC. Local combustion

angle of 3 degCA.

The obtained rate-of-heat-release pattern is shown in fig. 10. It has been determined for premixed mixture combustionat air excess of 2. It is necessary to stress that the pattern described in fig. 10 has been obtained as the results of the


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particular multidimensional simulation and the combustion model slightly interacts with the computational mesh. In allsimulations presented, the 3-D model assuming axis-symmetry has been used. The simple geometry used enables the

use of the orthogonal mesh. Half of the cylinder has been solved and the number of finite elements in radial direction

was 50, that in axial direction was 30. The mesh seems to be quite coarse, but the main part of the simulation has been

done close to TDC which leads to the extremely compressed mesh. Therefore, characteristic mesh size is acceptable.

The mesh size has been also chosen as the compromise between the method resolution and computational time.

Unfortunately, the performed simulations have concluded in the necessity of further mesh refinement.

The in-cylinder pressure and temperature patterns are presented in fig. 11. Comparing them with experimentally

obtained ones, both in-cylinder pressure and temperature are overpredicted. Slightly optimistic combustion duration,

heat loss underestimation and procedure solving released heat during combustion are possible reasons for this. The heat

release is determined under assumption of constant fuel heating value. It causes the error in the released heat solution

especially in the case of the hydrogen combustion if thermal effect of reactions is not corrected to instantaneoustemperature. This is not necessary to take into account if the heat release is solved using (9). The effect has impact not

only on the mean in-cylinder temperature but it also affects local temperatures. The correct local temperature estimation

is important to simulate correctly NOx formation, which is strongly temperature dependent. As a consequence, the NOxpredictions are not expected to be quantitatively correct.

crank angle of 180 deg. CA (TDC) crank angle of 200 deg. CA

crank angle of 190 deg. CA crank angle of 210 deg. CAFig. 13: Temperature field in cylinder during combustion. Start of combustion at 5 degCA BTDC. Local combustion

angle of 3 degCA.


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Fig. 12 shows mass fraction in the cylinder during combustion. In fact, it describes instantaneous flame front positionand the width of reaction zone as the fuel mass fraction defines the main reaction coordinate. The reaction zone width is

determined by the local burning angle, i.e., local burning time, which represents predefined combustion model

parameter. The local burning angle has been chosen of 3 degCA and it has been kept constant during the simulation.

Temperature fields during combustion and after combustion end are shown in fig 13. The end of combustion can be

clearly identified from the rate-of-heat-release pattern in fig. 10. The influence of flame front position and cooling loses

is clearly visible in temperature isolines. The mass fraction contour lines prove that the assumed local burning timecauses quite a wide reaction zone to appear. The influence of the artificial diffusion probably affects the phenomena as

well.

crank angle of 178 deg. CA crank angle of 188 deg. CA






crank angle of 196 deg. CAFig 14: Mass fraction of hydrogen. Prediction achieved using chemical kinetics solution. The chemistry solved on the

background of the base model considering start of combustion at 5deg BTDC, local burning angle of 3deg CA.

The chemistry has been employed in the simulation to add the capability of solving NO x formation and to check the

used local burning time. Examples of hydrogen mass fraction contours are shown in fig. 14. Those contours can bedirectly compared with fig. 12 as they describe the instantaneous flame front position and reaction zone width solved by


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the detailed description of chemistry. The chemistry is solved on the background of the base model. The disproportion between the base model simulation and the chemical kinetics has appeared. The main reason for it is that strong

temperature dependence of the used chemistry can be observed. It causes that hydrogen mixture burns extremely fast

when it is exposed to temperature above 1000K. Therefore, the local in-cylinder temperature assures the fast burning

and the flame front remains very thin. The flame front is not completely smooth in fig. 14 because the chemistry

solution interacts with the computational mesh and the mesh size is near to limit of the flame front structure capture.

The correctness of the results has to be verified and influence of other model parameters such as Prantdl and Schmidtnumber value, turbulence parameters and mixture molecular diffusivity have to be carefully examined.

crank angle of 180 degCA crank angle of 196 degCA

Fig 15: Mass fractions of NO. Prediction achieved using chemical kinetics solution. The chemistry solved on the

background of the base model considering start of combustion at 5deg BTDC, local burning angle of 3deg CA.

The results of the NOx formation model are presented in fig. 15. The conclusion that the model predicts formation of

nitrogen oxide in post-flame region can be done comparing the NOx isolines with the fuel mass fraction one. It is

necessary to stress the circumstances, concerning the temperature solution, under the NOx formation has been solved. Itcauses significant NO concentration overestimation and that is the reason why no integral parameter is not presented.

The computation assuming shorter angle characterizing local burning time has been done in order to verify the model

behavior. Results of the simulation are summarized in fig. 16. The local burning value has been assumed to have a value

of 1 degCA. The mass fraction isolines show significant influence of the local burning angle on the reaction zone width.

However, the computation mesh needs to be refined if the flame distribution is captured correctly. It calls for use of the

fine grid during whole simulation or for employment of computation mesh refinement algorithms in parts with high

local gradients.

The multidimensional algorithm is extremely computational demanding especially in the case of the chemical kinetics

involvement. This is another reason why the simple geometry and rather coarse grid have been used up to now. The

computational time on IBM RS/6000 server is in scale of days. In general, CFD models require very detailed physical

submodels such as turbulence model, diffusion transport properties determination, etc. All these models have a lot of

uncertainties as for used parameters. This demonstrates reason of proposing the simplified approach to combustion

modeling inside the CFD methods. The simplified model can not fully substitute the detail combustion models based on

the detailed description of chemistry but it helps in providing the simulation tool which combines multidimensional

methods with experiments.


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crank angle of 178 deg.CA crank angle of 186 deg.CA

crank angle of 180 deg.CA crank angle of 188 deg.CA

crank angle of 182 deg.CAcrank angle of 190 deg.CA

crank angle of 184 deg.CA crank angle of 192 deg.CAFig 16: Mass fraction of hydrogen during combustion. Example of testing simulations assuming local burning angle of1 deg. CA. Simplified combustion model used only.

CONCLUSIONSConclusions of the work can be summarized as follows:

The 0-D model provides practically useable data and it is ready to use for full-scale hydrogen engine simulation. Itis possible to generalize experimental data by the means of the 0-D model, e.g., the GT-Power code, and to use the

simulation to extrapolation of experimental data to other cases of interests.

It is possible to use broad flammability limits of hydrogen and sufficiently fast combustion on extremely leanmixture conditions to NOx production reduction. The measures reducing pollutant formation can be employed

without unacceptable restriction of the engine efficiency.

CFD model provides high potentials concerning detailed in-cylinder phenomena modeling. The main advantage iscapability of solving interaction of concentration, temperature and velocity field on NOx formation. On thecontrary, such models are extremely computationally demanding.

The simplified combustion model based on experimental data splits connection between stiff chemistry andturbulence model. However, it respects parameters of the turbulent flame correctly because it is based on

experimental data involving all possible effects.

The combination of the simplified combustion model with chemical kinetics provides strong advantages in thepossibility of the chemistry solution use to the combustion model parameter correction. It also extends capabilities

of the model to NOx formation modeling in the general manner which is of concern in the hydrogen engine

simulations.

The hydrogen combustion chemistry solution shows the reaction zone should be very thin. It is caused because ofthe very fast chemistry. Influence of mixture molecular transport properties and turbulence parameters on hydrogenflame has to be proved. It seems to be necessary to use experiments being able to resolve flame distribution to the

feature verification. In the presented simulations, suitability of the used reaction mechanism has to be examined. The CFD model predicts that NOx are formed in post-flame region only.


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ANCKNOWLEDGEMENTS

All measurements used during the work elaboration have been done in laboratories at the Technical University of

Liberec, Halkova 6, CZ 461 17 Liberec, Czech Republic. The authors would like to thank to colleagues from the

university for their efficient cooperation.

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[7] Marinov, N., Westbrook, C.K. and Pitz, W.J.,"Detailed and Global Chemical Kinetics Model for Hydrogen" in

ransport Phenomena in Combustion, Volume 1 (S. H. Chan, edited), Talyor and Francis, Washington, DC, 1996

[8] Netlib Public Library. www.netlib.org.[9] Polek, M. Macek, J. Takts, M. Vtek, O.: Application of Advanced Simulation Methods and their

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