Paper Number 87
Experimental and Numerical Investigations on HCCICombustion G. Barroso, A. Escher, K. Boulouchos Swiss Federal Institute of Technology ETH Zurich 2005 SAE_NA section
ABSTRACT Numerical and experimental investigations are presented with regard to homogeneous-chargecompression-ignition for two different fuels. N-heptane and n-butane are considered for covering an appropriate range of ignition behaviour typical for higher hydrocarbons. One fuel is closer to diesel (n-heptane), the other closer to gasoline ignition properties (nbutane). Butane in particular, being gaseous under atmospheric conditions, is used to also guarantee perfectly homogenous mixture composition in the combustion chamber. Starting from detailed chemical mechanisms for both fuels, reaction path analysis is used to derive reduced mechanisms, which are validated in homogeneous reactors. After reduction, reaction kinetics is coupled with multi zone modeling and 3D-CFD through the Conditional Moment Closure (CMC) approach in order to predict autoignition and heat release rates in an I.C. engine. Multi zone modeling is used to simulate port injection HCCI technology with nbutane. Comparison with experimental results for a passenger car engine – obtained at the University of Stuttgart – yield good agreement. 3D-CFD with Conditional Moment Closure is used to simulate direct injection HCCI technology with diesel. Comparison with experimental results for a common-rail-passenger car engine – again obtained at the University of Stuttgart – yield good agreement. On the experimental part a rapid compression machine (RCM) with wide optical access is used to provide autoignition and combustion data under well defined conditions, thus covering a wide range of engine operating parameters in terms of pressure, temperature and mixture composition around TDC. So far passive optical techniques, in particular chemiluminescence is used to provide – in addition to heat release rates obtained by pressure measurements – information on ignition locations, cyclic variability of combustion and distribution of reaction zones. The experimental test rig allows both external and internal fuel injection and therefore different degrees of mixture (in)homogeneities. Variable heating of the cylinder wall temperatures can be set in the RCM.
INTRODUCTION In conventional diesel diffusion combustion, as the speed of the chemical reaction is faster than the speed of the mixing of the fuel and air, the combustion reaction starts near stoichiometric air-fuel ratio and proceeds across a wide-ranging region from lean to rich. NOx and soot are accordingly generated and it is difficult to reduce these simultaneously. To solve this problem, it is desirable to complete the mixing process before combustion begins, and to burn the fuel in a lean homogeneous state. To comply with future emission standards, a combination of internal and external reduction of exhaust gases is necessary. The purpose of this study is to determine the characteristics of combustion of homogeneous charge compression ignition (HCCI). A rapid compression machine (RCM) is used to clarify the effects of air-fuel ratio, temperature, different fuels on both ignition delay and locations. To shorten development time and to understand combustion processes, the use of simulation is increasing. The limited calculation capacities and the shortened time from development to product need the modeling of the complex chemical and physical processes. In literature different complexity levels to model the HCCI combustion process can be found. A wide used approach is the treatment of the combustion chamber as a perfectly stirred reactor with variable volume and heat losses [1-5]. This approach is very useful if a valuation of suitability is performed and only the trends are essential [1-5]. Chen et al. [2] performed an investigation of internal EGR. He showed that using internal hot EGR leads to an earlier combustion. Fiveland et al. investigated in [4] the influence of initial temperature, initial pressure of mixture, natural gas composition, heat transfer model, equivalence ratio and compression ratio on ignition behavior of an HCCI engine. As expected, an increase of initial temperature leaded to an earlier ignition. Similar was the behavior while increasing the inlet pressure keeping the equivalence ratio and the inlet temperature constant. Adding to methane hydrocarbons of higher order - such as ethane and propane - in a range which is absolutely
possible in natural occurrence, the ignition delay could be shortened up to half a millisecond. In [5] the computational investigation of [4] was extended and was compared with experiments. Both, experiments and simulation, showed again that adding higher order alkanes leaded to an earlier ignition. For 100% methane simulation and experiments agreed reasonable. But using gas mixture the difference between simulation and experiments was increased. Because in reality the combustion chamber is not homogeneous, models have been improved using various zones, which can have stochastic [6,7] initial conditions or the use of models which divide the combustion chamber into an adiabatic core, a boundary layer and a crevice volume [8,9]. Depending on the model assumption the zones experience no interaction [6], volumetric work between the boundaries or mass and energy exchange due to stochastic collision [7]. In [8, 9] there is mass exchange between the crevice zone, the boundary layer and the adiabatic core zone, respectively. Schiessl et al. [6] extrapolates from formaldehyde H2CO measurements at start of combustion a standard deviation of the temperature at IVC of 5K. They tell that their simulations show reasonable agreement with experiments under lean conditions (λ > 2). Fiveland et al. [9] could predict additional to pressure and temperature curves the emissions of UHC with reasonable agreement. The deviation in CO prediction was a little higher. In [10-13] the initial conditions for detailed chemical kinetics calculation are taken from 3D-CFD calculations. Babajimopoulos et al. [10] simulates with KIVA-3V the gas exchange process and investigates strategies with variable valve actuation, among other things negative valve overlap. They experienced that for cases with high average temperature and with combustion before TDC not much difference could be observed using a multi zone model with temperature and phi distribution, a multi zone model with only temperature distribution or a single zone model. However for cases with marginal combustion, which often are cases with high EGR, the difference was high. Babajimopoulos et al. validated the model proposed in [10] with experiments of a test engine in [11]. The proposed approach could provide an accurate 10%, 50% and 90% mass fraction burned within 1-2 CA. However, the model predicted near 100% combustion efficiency because it can not capture the cool regions in the cylinder. Aceves et al. [12] used a similar approach calculating the compression with KIVA until 20° ATDC without combustion and then using a 10 zones approach to calculate the detailed chemistry. The calculations were smoother compared to the one with a single zone model. Similar to Babajimopoulos et al. [10, 11] and Aceves et al. [12] Amano calculated the intake and the compression with 3D-CFD and then switched to multi zone modeling to calculate combustion. A disadvantage of this methodology is, that first a complete 3D-CFD calculation has to be done. After that, a realistic temperature, air-fuel ratio and EGR distribution has to be extracted from the CFD data. Then
a calculation with the multi zone model can be performed. Bikas [13] developed a reduced kinetic mechanism and investigated the HCCI combustion process under different conditions with a single zone model. He used a representative interactive flamelet (RIF) model to capture for spatial inhomogenities and compared the results with the obtained by the 0D-model for one operating condition. The authors propose two promising ways to simulate HCCI combustion processes. The first model is a classical multi zone model with stochastic initialization of the lambda and the temperature distribution and is physically only recommendable to simulate HCCI combustion process with port injection. The second model, allows for spatial and temporal inhomogeneities by calculating the complete high pressure cycle with 3DCFD. To solve the chemistry source term only the mixture fraction and its variance is transported and detailed chemistry is solved in the mixture fraction space. The models accounts for combustion turbulence interaction by conditional moment closure. This model has been used in more fundamental research such as spray combustion by Mastorakos et al. [15], Wright et al. [16] and Weisser et al. [17].
SIMULATION In this section a short overview of the used methodology for the stochastic multi zone model is presented. In the next section an overview over the more extensive CMCModel is given. METHODOLOGY OF THE MULTIZONE MODEL As in a single zone model the sum of the volumes of all zones is calculated by the crank kinematics given by equation 1.
V (ϕ ) = S (ϕ ) ⋅ π ⋅
B2 + Vc 4
(1)
Where S(ϕ) is the distance from to piston to the position at TDC.
L 1 S (ϕ ) = H ⋅ (1 − cos(ϕ ) + s (1 − cos 2 (ϕ ))) 2 4
(2)
And Vc is the cylinder volume at TDC.
Vc =
VD ε −1
(3)
Equation 4 is the energy equation of a single homogenous reactor.
dT dV dQw ⎞ 1 ⎛ dQB = −p − ⎜ ⎟ dt m ⋅ cv ⎝ dt dt dt ⎠
(4)
dQB/dt is the heat release rate by chemical reactions which is calculated with detailed chemistry. Ns dQB = V ⋅ ∑ w i ⋅ M i ⋅ ui dt i =1
(5)
w i is the source or sink, respectively, of species i
[mol/(cm3·s)], Mi is the molar weight [kg/mol], ui is the internal energy [J/kg] and V [cm3] is the Volume of the reactor. For the calculation of species production or destruction rate the molar weight and the internal energy, Chemkin II subroutines are used. The stiff differential equation system is integrated with the subroutine DVODE. For the calculation of the heat losses the model proposed by Woschni is taken,
dQW = α w ⋅ AZ ⋅ (T − TW ) dt
(6)
cylinder pressure. Change of the mass in the fire land volume is compensated by all the zones depending on their mass fraction. The multi zone model consists of various reactors as described above. The reactors are coupled by pressure compensation an volume work between the zones. The individual Zones are calculated as a homogeneous reactor during one time step. Afterwards the cylinder pressure is calculated considering energy conservation (Eq. 9), the ideal gas law (Eq. 8) and having the total cylinder volume given by the crank kinematics (Eq. 1).
cv ⋅ mcyl ⋅ Tcyl = ∑ j =z1 cv , j ⋅ m j ⋅ T j N
The sum of all individual zone volumes must be equal to the cylinder volume. The pressure of all zones is set after each time step to the cylinder pressure. To conserve the zone mass, volume work between the zones is done. The zone temperature and air fuel ratio at intake valve close is calculated stochastic. A normal distribution is taken with user prescribed standard deviation and mean value (Eq. 10, 11). NZ
σT = ∑
where the heat transfer coefficient is calculated with equation 7.
i =1
mi ⋅ (Ti − T ) 2 mtot NZ
αW = α scaling ⋅130 ⋅ B (C1 ⋅ cm + C2 ⋅
−0.2
⋅ p ⋅T 0.8
−0.53
VH ⋅ T1 ⋅ ( p − pZs ))0.8 V1 ⋅ p1
⋅
p ⋅V = m ⋅ R ⋅ T
T =∑
(7)
The value for αscaling can be varied for conventional direct injected diesel engines in a range of +- 30%. In this work the parameter αscaling has been varied in a range from 0.01 to 1. The constant C1 is set to 2.28 + 0.308 · cu/cm. The swirl factor cu/cm is for the investigated engine 1.23. For the constant C2 the standard value for direct injected engines is taken. It is conscious to the authors that the model developed by Woschni is unsuitable for the HCCI combustion process. Zoran et al. [18] adapted the constants of the model for use with HCCI engines. The adapted version has also been used during this work. No noticeable improvement was detected looking on various operating points. The presented model assumes that al zones have the equal probability to have heat losses to the wall. Therefore the calculated heat losses are proportional to the mass fraction. The gas is modeled as ideal (Eq. 8). (8)
A simplified model for the fire land is taken. A new zone is introduced which represents the volume of the fire land. In this volume no chemistry is calculated. The fire land has a constant volume and the temperature is equal to the wall temperature. This assumption is suposed to be valid, because this small volume has a big common surface. The pressure is equal to the
(9)
i =1
mi ⋅ Ti mtot
(10)
(11)
METHODOLOGY OF THE 3D-CFD MODEL WITH CONDITIONAL MOMENT CLOSURE (CMC) The CMC modeling and the coupling with the commercial CFD code StarCD used in this work, has been presented by previous works Mastorakos et al. [15] and Wright et al. [16]. Here a short summary of the governing equations and the methodology is given. Using detailed chemistry in combination with 3D-CFD the conservation equation of mass (12) for each species has to be solved.
ρ
∂Yi +ρ u ⋅∇Yi − ∇ ⋅ ( ρ Di ∇Yi ) = w i ∂t
(12 )
The first term on the LHS is the temporal change of species Yi, the second term on the LHS is the convection and the third term on the LHS is the diffusivity assuming Fick’s law of diffusion with diffusivity Di. The RHS is the species production rate by chemical reaction. ∇ and ∇ ⋅ are the gradient and the divergence operators, respectively. Because turbulence is modeled in our computation, velocity (u) and its fluctuation (u’) are ensemble averaged values. Conditional moments are averages, variances, etc., taken for only those members of the whole ensemble, which comply with a specified condition. Now we consider the conditional average (an average, because our computation (RANS) only give a
ensemble averaged solution) and variance of species mass fraction Yi not only being dependent on the location (x) and time (t) but also on the mixture fraction ξ. Although a new independent variable has been introduced, the dimensionality of the problem can often be reduced, assuming that not the location but the mixture fraction at that location is important. According to [15, 16, 19] the conditional expectation or average of the mass fraction Yi of species i and the conditional expectation or average QT of temperature T are defined as
Qi (η , x, t ) ≡ Yi ( x, t ) | ξ ( x, t ) = η ≡ Yi | η
(13 )
QT (η , x, t ) ≡ QT ( x, t ) | ξ ( x, t ) = η ≡ QT | η
(14 )
and
where η is the sample variable for the conserved scalar (in this case the mixture fraction) and
Yi ( x, t ) | ξ ( x, t ) = η
denotes that the expectation or
average of mass fraction of Yi at location x to the time t having the mixture fraction ξ in physical space, corresponds to the expectation at η in the mixture fraction space. In other words, ξ(x,t) must fulfill the condition ξ(x,t) = η and therefore the average mass fraction of Qi at the physical location x at the time t depends only on the mixture fraction. The value of the mass fraction Yi of species i at the location x to the time t is
Yi (η , x, t ) = Qi (ξ ( x, t ), x, t ) + yi ( x, t )
(15 )
where Q(ξ(x,t),x,t) is the mean value and y(x,t) is the deviation which has according to equation (15) an expectation of 0. (16 )
yi ( x, t ) | ξ ( x, t ) = η = 0
Bilger [19] inserts in equation (12) instead of Yi and its derivations equation 13 and its derivation, respectively. Following [15, 16, 19, 20], the conservation equations for the conditional species mass fractions (Eq. 17) (CMC equation) can then be written as (17 ∂Q 1 ρ i +ρ u | η ∇Qi + ∇ ⋅ ⎡⎣ u ' y | η ρ P (η ) ) ∂t P(η ) ∂Qi = wi | η + ρ Di ∇ξ ⋅∇ξ | η ∂η 2 where P (η ) is the probability density function (pdf). Full closure of equation (17) requires modeling of the conditional mean reaction rate,
ω |η
, velocity
u |η
χ | η = cχ ⋅ D ∇ξ ⋅∇ξ | η
scalar dissipation rate
as
well as the turbulent flux. In this work the scalar dissipation rate is modeled according to [15, 16]
ε χ = cχ ξ ''2 k
(18 )
where cχ is set to 2, following standard practice. ε is the
turbulence energy dissipation rate, k the turbulence kinetic energy and ξ the variance of the mixture fraction. Closure of the chemical source terms is performed at first-order. This means, that the mean chemical source for a given η is only a function of the conditional species concentration Qi(η), the conditional temperature QT(η) and the pressure P (Eq. 19) ''2
(19 )
w i | η = ω i (Qi , QT , p )
The conditional turbulent fluxes are modeled with gradient fluxes, while the conditional velocities are modeled based on a linear relationship [16]. USED REACTION MECHANISM FOR N-HEPTANE AND N-BUTANE On the one hand, using multi zone modeling the computational cost increases linearly with the amount of used zones, on the other hand, using the CMC approach, detailed chemistry has to be solved for each node in the mixture fraction space. Additional the pdf has to be integrated for each species and each computational cell to get the unconditional species value. The use of skeletal mechanism reduces dramatically the computational effort, without a large drop in accuracy. A starting mechanism for n-heptane with 65 species and 285 reactions [21] was succesfully reduced to a skeletal mechanism with 24 species and 63 reactions using reaction path analysis. The starting mechanism for n-butane is a submechanism of the detailed iso-octane mechanism of the Lawrence Livermore National Laboratory [22]. It consists of 385 species and 1895 reactions. This mechanism was successfully reduced using heat release rate analysis of the individual reactions to a skeletal mechanism with 140 species and 453 reactions. In Table 1 are the operating points listed, where the skeletal mechanism for n-heptane and the one for nbutane, respectively, are compared to the starting mechanisms. The engine data are listed in Table 2. OP λ [-] rpm [1/min] p @ IVC [bar] mF[mg] mAir [mg] T @ IVC [°K]
2xx 2 1200 1.2 18 543 352
25xx 2.5 1200 1.33 16 603 352
3xx 3 1200 1.39 14 633 352
35xx 3.5 1200 1.61 14 739 352
4xx 4 1200 1.84 14 845 352
45xx 4.5 1200 2.07 14 950 352
Table 1: λ−ε window where the mechanisms where compared. Compression ratio 15, 16, 17 and 18 were used. [xx = means compression ratio] Figure 1 shows the difference in crank angle between the crank angle when the “detailed” n-heptane mechanism reaches 10% cumulative heat released and the skeletal one. The maximum deviation between the skeletal and the starting mechanism is 3 degrees. The deviation increases for low compression ratios and richer mixtures. This is on the one hand possibly due to the fact, that the reaction path analysis was performed at ε = 16.6 and λ=3.8, and on the other hand may be also because at lower compression ratios the heat release is slower and thus the deviations are larger although the relative deviation is not larger.
Fig. 3: Difference in crank angle between the crank angle when the starting n-butane mechanism reaches 10% cumulative heat released and when the skeletal mechanism does. Calculations performed in a homogeneous reactor for different λ and ε. [1200 rpm, λ = 2 ÷ 4.5 , ε= 15 ÷ 18 , VH = 537.7 cm3 ] Figure 4 shows the difference in crank angle between the crank angle when the detailed n-butane mechanism reaches 50% cumulative heat released and the skeletal one. For a large combination of λ and ε the difference between the skeletal and the starting mechanism is less then 0.2 degrees.
Fig. 1: Difference in crank angle between the crank angle when the starting n-heptane mechanism reaches 10% cumulative heat released and when the skeletal mechanism. Calculations performed in a homogeneous reactor for different λ and ε. [1200 rpm, λ = 2 ÷ 4.5 , ε= 15 ÷ 18 , VH = 537.7 cm3 ] Figure 2 shows the difference in crank angle between the crank angle when the “detailed” n-heptane mechanism reaches 50% cumulative heat released and the skeletal one. For a large combination of λ and ε the difference between the skeletal and the starting mechanism is less then 1 degree.
Fig. 4: Difference in crank angle between the crank angle when the starting n-butane mechanism reaches 50% cumulative heat released and when the skeletal mechanism does. Calculations performed in a homogeneous reactor for different λ and ε. [1200 rpm, λ = 2 ÷ 4.5 , ε= 15 ÷ 18 , VH = 537.7 cm3 ]
COMPARISON OF SIMULATIONS WITH THE MULTIZONE MODEL AND EXPERIMENTS
Fig. 2: Difference in crank angle between the crank angle when the starting n-heptane mechanism reaches 50% cumulative heat released and when the skeletal mechanism. Calculations performed in a homogeneous reactor for different λ and ε. [1200 rpm, λ = 2 ÷ 4.5 , ε= 15 ÷ 18 , VH = 537.7 cm3 ]
Figure 3 shows the difference in crank angle between the crank angle when the detailed n-butane mechanism reaches 10% cumulative heat released and the skeletal one. The maximum difference between the detailed and the skeletal mechanism is 0.4 degrees.
The results presented in this section focus on portinjected, four-stroke HCCI combustion with n-butane. Table 2 contains the basic data of the single cylinder research engine located at the University of Stuttgart. The investigations with n-butane were all carried out with the thermodynamic compression ratio of 16.6. Before starting to compare the simulations with the experiments, a number of sensitivity analyses were performed. These analyses showed that the results are more sensitive to the number of zones resolving the temperature than the number of zones resolving the λ. If the number of zones resolving the initial temperature field is to small, discontinuities in the pressure and heat release curve can be observed. This is due to the fact, that with a low resolution the temperature difference
between the zones is high and the start of combustion is of each zone is then visible in the pressure curve. Manufacturer Stroke
Mercedes-Benz OM611 88.4
mm
Bore
88
mm
VD
537.6
cm3
connecting
149
mm
16.6 14.7 0.51
piston bowl 1 piston bowl 2 -
rod length εthermodynamic swirl rate (Tippelmann) Table 2: Data of the single cylinder research engine of the University Stuttgart (Germany) It was experienced that a choice of 20 temperature zones times 10 lambda zones (so the use of a total of 200 zones) leaded to smooth curves with reasonable computational effort. Over a couple of operating points, the use of a low initial standard deviation for both temperature and lambda, respectively, leaded to the best results. Additionally, best results were performed setting the factor αscaling for the heat losses to 0.5 [28]. OP λ [-] rpm [U/min] p @ IVC [bar] mF [mg] mAir [mg] T @ IVC [°K] residual gas [%]
i 3.8 120 0 1.36 9.6 568 352 8.84
ii 4.2 120 0 1.75 11.6 756 352 6.04
iii 5.4 120 0 2.25 11.7 974 352 6.19
iv 3.1 120 0 1.24 11.6 544 348 5.70
Table 3: Initial- and boundary conditions of the operating points fueled with n-butane In table 3 the analyzed operating points are shown. For all cases the rpm was kept constant at 1200, because increasing the rpm leaded to incomplete combustion. Figure 5 shows the comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point i. The computed heat release rate starts a few degrees earlier, but with low intensity. Therefore the peak pressure is a few bars higher and the peak value of the heat release rate also. The simulated combustion is a few degrees shorter. Nevertheless, the overall agreement is reasonable.
Fig. 5: Comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point i (1200 rpm, 20 temperature zones x 10 λ− zones, λ= 3.8, σT = 2.5 K, σλ = 0.05, fuel = n-butane, skeletal mechanism, αscaling = 0.5 ) Figure 6 shows the comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point ii. The cool-flames at this operating point are for both, experiment and simulation, more pronounced. Again the simulated heat release starts more intensive. This leads to a higher peak pressure and a higher peak value of the heat release rate. The simulated combustion duration is also shorter then the measured one. An increase of the standard deviation of the initial temperature of the zones, would lead to longer combustion duration but also to an earlier ignition. A higher standard deviation leads to zones with a high initial temperature, which ignite earlier. Figure 7 shows the comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point iii. As in operating point ii the cool-flames are very pronounced. It seems that the leaner the mixture is, the better can the cool-flames be observed.
Fig. 6: Comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point i (1200 rpm, 20 temperature zones x 10 λ− zones, λ= 4.2, σT = 2.5 K, σλ = 0.05, fuel = n-butane, skeletal mechanism, αscaling = 0.5 ) For this operating point the pressure curve matches very well with the experiment. The location of the heat release rate and the burn duration are also reasonable. Only the peak value of the heat release rate is too high compared to the experimental one. Figure 8 shows the comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point iv. This is the richest analyzed operating point. In this operating point neither for the simulation nor for the experiments, cool flames are observable. Again the computed heat release rate starts earlier, but at the beginning with low intensity. A few degree after TDC there is a fast combustion with a high peak heat release rate compared to the experiments. Also the simulated peak cylinder pressure is definitely higher than the experimental one. Maiwald [7] already reported, that it is easier to simulate HCCI combustion process under lean conditions than under riches one.
Fig. 7: Comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point i (1200 rpm, 20 temperature zones x 10 λ− zones, λ= 5.4, σT = 2.5 K, σλ = 0.05, fuel = n-butane, skeletal mechanism, αscaling = 0.5 ) To have the same initial and boundary conditions between experiments and simulation is challenging. Fiveland et al. [5] made in his publication a discussion of uncertainties in modeling and in experiments. In this work there are also a few uncertainties which could lead to differences between computation and measurement. N-butane is applied continuously by a gas tap and the fuel mass can only be determined by measurements of the exhaust gas and is therefore afflicted with an error of +- 5%. In addition there are measurement uncertainties in the cylinder pressure of +- 20 mbar and in the cylinder mass of +- 2%. If these uncertainties are corrected in the “right” direction, so a reasonable agreement between experiment and simulation can be achieved also in this operating point.
Table 4: Initial- and boundary conditions of the operating points fueled with diesel with direct injection For the simulation the above presented skeletal nheptane mechanism is used. The model fuel n-heptane is taken, because it has similar ignition behavior to commercial diesel. The two operating points differ in the SOI. In operating point one, the fuel is injected at 40 BTDC. In operating point two, the fuel is injected at 25 BTDC. Figure 9 shows the comparison between the 3DSimulation with CMC and the experimental pressure curve for operating point OP1.
Fig. 9: Comparison between the 3D-Simulation with CMC and the experimental pressure curve for operating point OP1 (2000 rpm, λ ≈ 1.1, pinj = 1200 bar, SOI 40 BTDC, EGR = 60 %, fuel = diesel (experiment), n-heptane (simulation), skeletal mechanism, ) Fig. 8: Comparison between the simulated and the experimental pressure curve (above) and the heat release rate (below), respectively, for operating point i (1200 rpm, 20 temperature zones x 10 λ− zones, λ= 3.1, σT = 2.5 K, σλ = 0.05, fuel = n-butane, skeletal mechanism, αscaling = 0.5 )
COMPARISON OF SIMULATIONS WITH THE 3D-CFD MODEL WITH CONDITIONAL MOMENT CLOSURE (CMC) AND EXPERIMENTS The results presented in this section focus on directinjected, four-stroke HCCI combustion with diesel. RPM Injected Volume pinj SOI (effektive) EGR residual gas Spray hole cone angle Hole angle NOx FSN
OP1 2000 1 x 18.5 1200 40 60 6 120
OP2 2000 1 x 18.5 1200 25 62 6 120
U/min mm3 bar v. OTP % % °
8 1 0.0
8 1 0.86
[-] ppm [-]
Fig. 10: Comparison between the 3D-Simulation with CMC and the experimental pressure curve for operating point OP1 (2000 rpm, λ ≈ 1.1, pinj = 1200 bar, SOI 25 BTDC, EGR = 62 %, fuel = diesel (experiment), n-heptane (simulation), skeletal mechanism, ) Figure 10 shows the comparison between the 3DSimulation with CMC and the experimental pressure curve for operating point OP2. In both operating points the simulated pressure starts to increase due to
combustion later than the experimental one. The value of the peak pressure and its location is reasonable reproduced for both cases. Variation of spray parameters (such us critical Weber number for droplet break up, spray cone angle, initial droplet size) did not influence much the pressure curve. Therefore, the results with standard parameters are shown. For the CMC mean quantities (i.e. temperature initialization, scalar dissipation rate, etc.) of the flow field are used. Several variations of these quantities have been performed with no major influence on ignition. The HCCI combustion process is at this high amount of EGR quite unstable. A small variation in EGR leads to misfire. It has to be investigated how this can influence the start of ignition.
EXPERIMENTAL SETUP Up to the present stage, a constant volume test rig [23, 24] as well as a rapid compression machine (RCM) has been used. The later simulates the compression and expansion stroke of an engine in the area of TDC. Stroke, compression ratio, heating and swirl can be controlled independently and the excellent optical access (4 sapphire windows are installed in the upper part of the cylinder as well as a transparent piston) allow the simultaneous use of various measurement techniques.
bore
84 mm
stroke
120 mm – 250 mm
compression ratio
5 - 25
max cylinder pressure
200 bar
heating
part of cylinder, cylinder head and piston can be preheated up to 150 °C
Table 5: operation regions of the RCM A comparison of piston motion and cylinder gas pressure in the RCM with an OM 611 (bore 88 mm, stroke 88.4 mm, 2000 rpm) reveals that the RCM simulation results in slightly higher cylinder pressure envelope around TDC. Regarding an interval of +/- 15 °CA, a pressure increase of 4.5 bar is measured at a simulated engine speed of 2000 rpm. This is the result of a supercharged compression chamber before start the experiment (pcyl 1.3 bar).
Both direct and port injection is installed and the use of a wide range of gaseous and liquid fuel is possible at the same time. The driving concept is based on two cylindrical and concentrically mounted driving pistons moving in opposite directions [25]. This concept guarantees a mass balanced motion for any operating condition which allows a nearly vibration free operation. Figure 12: Comparison between pressure curve of an engine and a RCM around TDC First experiments simulating an engine speed of 2000 rpm with 175 mm stroke showed an excellent reproducibility concerning piston motion and cylinder pressure. Figure 12 illustrates an average of 20 consecutive measurements, without combustion. Average peak pressure was found at 45.25 bar (min 44.4 bar, max 46.1 bar).
Figure 11: Basic concept Rapid Compression Machine Engine speed is mainly controlled by the ratio of air pressure in the combustion chamber and the driving oil pressure. simulated engine speed
1000 rpm – 3000 rpm
So far, an appropriate determination of measured λ is not yet possible. As the repetition rate of experiments is lower than on a real engine and thus having an exhaust mass flow which does not allow the use of a lambda sensor, the A/F is based on calculated values.
EXPERIMENTAL RESULTS Experiments were conducted under the following conditions: •
early direct injection of diesel fuel
•
port-injection of liquid n-butane
In both cases, a piston used for conventional diesel combustion with a piston bowl (Ø 46 mm, bowl depth 17 mm) was used. The combustion chamber was charged to 1.2 bar prior compression stroke.
The combination with a driving air pressure of 30 bar simulates an engine speed of 2000 rpm with a resulting compression ratio of 15.5, V1 1027 cm3. Early direct injection of diesel fuel Diesel fuel CN 55 was injected with 500 bar during 1.9 ms (λnominal = 3.0) at 50° CA BTDC. A 8 hole injector was used, with a hole diameter of 0.112 mm, and a cone angle of 120°. The volumetric flow is qhyd 315 cm3 in 30 s using a injection pressure of 100 bar. Images were recorded through the transparent piston bottom window (Ø 46 mm) using a PCO DiCam allowing partial optical access into the combustion chamber (Ø 84 mm). With the setup used, one image recording per cycle was possible. Time of ignition was derived from photo multiplier signals. Sensors were placed on the upper part of the cylinder (optical ring) as well as on the window in the cylinder head. Start of ignition was measured at 12.5 °CA BTDC.
a) both images at 12°CA BTDC
b) both images at 7.2°CA BTDC Figure 15a: Recorded signals during experiment
c) both images at 5.4°CA BTDC
d) both images at TDC Figure 14: Passive chemiluminescence, early injection of diesel fuel, 50° CA BTDC
Figure 15b: 3D-CFD Simulation with CMC, using detailed n-heptane mechanism During ignition phase, multiple locations of ignition were detected which is typical for HCCI processes. Flame propagation was not observed. During injection, diesel
was applied on the cold cylinder liner resulting in diesel deposits. This effect is visible in images 14c and 14d, showing 8 spots of inflammation. Figure 15a illustrates the recorded cylinder pressure trace. Time position of acquired chemiluminescence images is marked with arrows in the photomultiplier signal trace. Comparing these experimental results with simulation using a detailed n-heptane mechanism a difference of 5.5 °CA of start of ignition was found, as illustrated in Figure 15a and 15b. This difference is due to the fact, that the simulation were done under engine conditions. Earlier experiments in the high-pressure hightemperature cell showed that ignition delay between nheptane and diesel fuel under diesel conditions is almost identical [24]. Simulation in the RCM was conducted with a compression ratio of 16.5 which leads to higher temperature in TDC. As wall losses are significantly higher in the RCM this explains the tendency to later ignition timing in the RCM. Port injection of n-butane N-butane, being gaseous under atmospheric conditions (pv 2.06 bar at 293 K) leads to a perfectly homogenized mixture when injected into the combustion chamber. Disadvantageous is the low CN 37, meaning that preheating of intake air, enrichment of mixture, reduction of engine speed or an increase of compression ratio must be taken into account for a stable and repeatable combustion. Lacking a crank motion, a trade off must be taken into account between engine speed and compression ratio leading to higher compression ratio and to higher engine speed.
Figure 16: Influence of cylinder wall temperature on pressure curve Preheating influences the beginning of HTR by 3° CA leading to a higher peak pressure as combustion starts earlier. The measured peak rise of 45 bar remains constant in both cases. Elevated temperature results in a higher cylinder pressure in TDC. It is assumed, that LTR starts at an earlier time and leads to earlier pressure increase. The influence of λ is demonstrated in figure 17 as well as shown in [26, 27]. Measurements were conducted at 293 K with the following injection parameters: • •
mn-Butan 40.5 mg, tinj 20 ms, pinj 500 bar, λnom = 2.2 mn-Butan 34.8 mg, tinj 17 ms, pinj 500 bar, λnom = 2.6
Up to the present stage, measurements were conducted at elevated temperatures (Twall, Tpiston 353 K) and enriched A/F ratios. Figure 16 illustrates the influence of TWall on cylinder pressure and ignition timing. The combustion chamber was pre-charged in both cases at 1.2 bar varying the wall temperature of 293 K and 353 K. Fuel mass was adjusted in both cases to λnom. 1.9 • •
TWall 293 K, mn-Butan 47 mg, tinj 23 ms, pinj 500 bar TWall 353 K, mn-Butan 42 mg, tinj 20.5 ms, pinj 500 bar
A BOSCH HDEV 1.1 gasoline fuel direct injector was used injecting n-butane in liquid phase. Fuel was injected into a swirl channel leading to the combustion chamber allowing the mixture to homogenize perfectly.
Figure 17: Influence of λ on pressure curve A dependence of lambda and HTR is obvious. HTR was measured at an earlier time in a mixture at λ=2.2 compared with λ=2.6. HTR at a later time leads to a decrease in peak pressure. Further experiments are ongoing. Figure 18 shows an exemplarily recording of combustion of n-butane, λ=2.6 at 1.1 ms ATDC. Ignition occurred in two regions. It is believed, that the inhomogenity of temperature distribution (4 heating elements are placed
inside the optical ring) has an influence in ignition location.
ACKNOWLEDGMENT The authors thank Mr. Dipl. Ing. Simon Haas and Prof. Dr.-Ing. M. Bargende of the Research Institute for Automotive Engineering and Vehicle Engines, Stuttgart (FKFS) for the experimental engine data and the good cooperation. Additional thank to the „Forschungsvereinigung Verbrennungskraftmaschinen e.V.“ (FVV, Frankfurt) and the Swiss Federal Office of Energy for the funding of this project.
Figure 18: exemplarily singles-shot recording of HCCI combustion, n-butane λ=2.6 at 1.1 ms ATDC.
We express our gratitude to both chairmen of the project, Mr. Dipl. Ing. Markus Weßlau (GM Powertrain Europe – Germany) and Dr. Ing. Arne Schneemann (MTU Friedrichshafen), and to the entire working party for the great support.
CONCLUSION Numerical and experimental investigations were presented with regard to homogeneous-chargecompression-ignition for two different fuels. Starting from detailed chemical mechanisms for both fuels, reaction path analysis was used to derive reduced mechanisms, which were validated in homogeneous reactors and showed a good agreement with the detailed mechanism. The reduced chemistry was coupled with multi zone models (reactors network) and 3D-CFD through the Conditional Moment Closure (CMC) approach. Autoignition and heat release rates in an I.C. engine was successfully predicted, for HCCI port-injection technology and for direct-injection technology. Comparison with experimental results for a passenger car engine – obtained at the University of Stuttgart – yield good agreement. Nevertheless, richer operating points with port injection were more difficult to predict. On the one hand there exist not negligible uncertainties on the experimental side. But it is difficult to say, if the discrepancies between experiments and simulations are due to that or they are coming due to model weaknesses. 3D-CFD with Conditional Moment Closure had reasonable agreement with the experiment with not extensive computational effort. Nevertheless, the simulated start of combustion seemed to have a systematic delay. Various sensitivity investigations could not clarify this issue. In the experimental part of the ongoing work, using a rapid compression machine, first experiments were conducted with early diesel direct injection as well as port injection of liquid n-butane. Variations concerned different wall temperatures as well as variations of A/F ratio. Richer A/F ratios as well as higher temperatures lead to an earlier HTR. Ignition timing was derived from cylinder pressure and chemiluminescence. Recording ignition location of an early diesel injection showed, that ignition started at different locations at the same time in the combustion chamber.
NOMENCLATURE
A − cylinder surface area ATDC − after top dead center α scaling − scaling factor heat losses
αW − heat transfer coefficient B − bore BTDC − before top dead center C1,2 − constants heat transfer model CA − crank angle CN − cetane number cm − mean piston velocity cv − specific heat capacity cχ − model constant for scalar dissipation rate Di − diffusivity constant species i Di , j − destruction of species i in reaction j H − stroke HTR − high temperature reaction EGR − exhaust gas recirculation
ε − compression ratio ε − turbulence dissipation rate η − mixture fraction in mixture fraction space ϕ − crank angle IVC − intake valve closes κ − turbulence kinetic energy Ls − ratio crank radius to connecting rod length
LTR − low temperature reaction m − mass mcyl − cylinder mass
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M i − molar mass species i N R − number of reactions N Z − number of zones
λ − air fuel ratio
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p − pressure pZs − pressure without combustion Pi , j − production of species i in reaction j P − probability density function
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dQB − heat release rate dt dQW − wall heat losses dt Qi − conditional expectation of species i QT − conditional expectation of temperature R − gas constant
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RCM − rapid compression machine
ρ − density S (ϕ ) − piston way σ T , σ λ − temperature or λ standard deviation
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T − temperature T1 − temperature TW − wall temperature
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TDC − top dead center ui − internal energy species i u − velocity Vc − compression volume VD − displacement volume
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V1 − cylindervolume at start of kompression V (ϕ ) − cylinder volume
w i − molar specific production rate species i Yi − mass fraction species i
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yi ( x, t ) − deviation ( fluctuation ) of species i
ξ − mixture fraction ξ ′′ − variance of mixture fraction
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CONTACT Gabriel Barroso / Andreas Escher Swiss Federal Institute of Technology ETHZ ETH Zentrum CLTB 4 / Clausiusstrasse 33 8092 Zürich Switzerland
[email protected] [email protected] www.lav.ethz.ch
