Modeling and Simulation of Gasoline Auto-Ignition Engines

Proceedings of the 2009 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling IFP, Rueil-Malmaison, France, Nov 30 - Dec 2, 2009

Modeling and Simulation of Gasoline Auto-Ignition Engines K.G. Stapf*, D. Seebach*, S. Pischinger* P. Adomeit**, J. Ewald** *Institute for Combustion Engines, RWTH Aachen University, Schinkelstraße 8, 52062 Aachen Germany (Tel: +49 241 5689 9398; e-mail: [email protected]). **FEV Motorentechnik GmbH, Neuenhofstraße 181, 52078 Aachen Abstract: Both the customer demand for increasing mobility and the emission legislation lead to a challenge for engine researchers and developers in order to reduce emissions and fuel consumption. One approach that is presently under extensive investigation is to implement auto-ignition combustion in gasoline engines. This combustion mode offers the possibility to reduce emissions and fuel consumption during part load operation. Furthermore it offers the advantage that it does not need an expensive exhaust gas after treatment due to nearly zero NOx-emissions in contrast to stratified direct injection operation. The auto-ignition depends strongly on stratification of air, residual gas and fuel. Furthermore, the thermodynamic state of the charge is of major importance to control the combustion process. Detailed knowledge of ignition and its dependency on operating conditions is necessary to develop efficient control strategies. This paper gives a summary on modeling strategies for gasoline auto-ignition developed within the collaborative research centre “SFB 686 – Modellbasierte Regelung der homogenisierten Niedertemperatur-Verbrennung” [1]. The auto-ignition process is simulated with two different approaches. 3D CFD calculation of flow, injection and mixture formation, which is bi-directional coupled to a multi-zone reaction kinetics solver. This 3D approach enables to analyze the thermodynamic conditions in the combustion chamber that lead to the auto-ignition. Thus, the temporal and spatial occurrence of exothermic reactions and their influence on the engine process are specified in detail. To reduce the computational costs and enable multi-cycle calculations, a second simulation approach was developed to analyze the process under steady state and transient operating conditions. The approach uses 1D gas exchange calculation with embedded burn function calculations based on reaction kinetics. The simulation shows good correlation to the test bench results, but requires a computational time of approximately 5 min per cycle. The calculation time can be further reduced with an approach based on a polynomial combustion model. Multi-cycle calculations are performed and compared to test bench results. Due to the small computational effort, this approach offers the possibility of a coupling to a controller design environment for synchronous simulation and control.

Keywords: auto-ignition, gasoline engines, simulation, 3D CFD, 1D gas exchange, reaction kinetics

configuration. Good progress has been made in the area of direct injection, downsizing, turbocharging and throttle-free load control with variable valve timing.

1. INTRODUCTION Due to the ongoing discussion on CO2-limitation, the growing energy demand and the limitation of fossil fuel, the focus of current development of internal combustion engines is to increase the efficiency and hence reduce the fuel consumption. Furthermore, current and future emission standards have to be taken into account.

An additional potential to reduce the fuel consumption can be gained by combustion processes like gasoline auto-ignition and homogeneous lean combustion. Therefore, extensive research work was already done and is still ongoing [2, 3, 4]. This paper focuses on gasoline auto-ignition. With this combustion system both high efficiencies and near zero NOxemissions are achievable. Lean operation with a de-throttled gas exchange leads to an increased efficiency. Furthermore, the auto-ignition with its spatial distributed ignition locations reduces peak combustion temperatures and thus reduces NOx

Today, still most of the produced gasoline engines are characterized by throttle control, cylinder selective port fuel injection, multivalve technology and stoichiometric combustion in combination with a 3-way-catalyst. There are already available several technologies to reduce the fuel consumption of gasoline engines based on this conventional

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2009 IFAC E-CoSM (E-CoSM'09) Nov 30 - Dec 2, 2009, IFP, Rueil-Malmaison, France.

raw emissions. Therefore an expensive NOx after treatment can be avoided, which is typically necessary in other lean combustion concepts to reduce NOx-emissions. The autoignition is enabled by high residual gas mass fractions, in a way that the air/fuel mixture can ignite during the compression near top dead centre. In this context, the stratification of the mixture plays a central role to control the combustion rate and to achieve high efficiencies. Valve timing and injection timing strategies are used to directly affect this stratification. In [5] the results of parameter studies were published for the considered engine.

2. OPERATING STRATEGIES AND RANGES 2.1 Steady state engine operation Auto-ignition of the fresh cylinder charge is initiated when exceeding the necessary thermodynamic state near top dead centre. The thermodynamic state is mainly controlled by the residual gas mass fraction, the injection strategy and the resulting mixture stratification of air, residual gas and fuel. The increased engine efficiency is a result of the de-throttling of the engine by residual gas, its effect on the gas properties and a fast fuel conversion. However the operating range of gasoline auto-ignition is limited to part load operation. The stability limitation at low loads and the pressure gradient limitation at high loads were presented in [6]. The influence of different valve timing strategies on the operating range was discussed in [5]. With the valve timing strategies Combustion Chamber Recirculation (CCR) and Exhaust Port Recirculation (EPR) different EGR rates and temperatures can be achieved which extends the operating range for gasoline auto-ignition. In Figure 2 the utilized valve lifts for intake and exhaust valves are shown together with the operating ranges for CCR and EPR as well as the operating range extension to low loads with direct injection and to high loads with turbocharging. While the CCR strategy traps exhaust gas inside the cylinder due to an early exhaust valve closing before TDC of the gas exchange stroke, the EPR strategy recycles exhaust gas from the exhaust port. Therefore, the exhaust valves are kept open after TDC. Both strategies are capable to provide the high amount of exhaust gas needed for auto-ignition. The intake valve is opened at the end of the gas exchange stroke.

The presented test bench data are measured on a single cylinder research engine with an electro mechanical valve train (EMVT). The mixture formation can be switched between internal and external. Only direct injection is regarded here. This work introduces two numerical models to gain a detailed understanding of the processes in the combustion chamber and to design a future controller concept. Figure 1 shows the investigation methodology defined within the involved subprojects of SFB 686. Starting with experimental investigations of the gasoline auto-ignition combustion system at the test bench and by using simulation tools of different modeling depth like 0D (i.e. perfectly stirred) reaction kinetics, 1D gas exchange calculation and 3D CFD (Computational Fluid Dynamics) simulation, a fundamental understanding of the auto-ignition combustion process is gained. Subsequently the tools are coupled to be able to simulate a complete combustion cycle in two level of detail and hence accuracy and predictability. In the last step the computational costs have to be decreased to realize a real time capable engine model for controller layout and adjustment. The actuation of the gasoline auto-ignition process finalizes the cycle.

Driving cycle simulations for the New European Driving Cycle (NEDC) were performed, based on stationary thermodynamic results. For a midsize vehicle with a 2 l DI engine capable for CCR a fuel consumption reduction potential up to 10 % has been simulated. This potential can be increased by broadening the auto-ignition operating area with EPR and turbo-charging.

Actuation of auto-ignition process Controller Adjustment Control layout

Test bench investigation 1D gas exchange simulation

Real time capable engine model

3D Computational Fluid Dynamics (CFD) Reaction kinetics

1D gas exchange with multi zone reaction kinetics

3D CFD and multi zone reaction kinetics

Fig. 1. Methodology

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Exhaust

investigation. Therefore, the operating points can be considered as stable.

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EPR BDC

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3.50 Exhaust Port Recirculation (EPR) with PFI Combustion Chamber Recirculation (CCR) with PFI Extension EPR with Boosting and Direct Injection Extension CCR by Direct Injection

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Limitation of Operation Area due to max. Pressure Rise

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Fig. 2. Operating area and schematic valve lift timings of investigated EGR strategies

Cyclic Data Steady-state Data

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Fig. 3. Operating mode change as an example of transient engine operation at n = 2000 min-1

2.2 Transient engine operation The main challenge of gasoline auto-ignition operation is the realization of a proper transient behavior together with an extension of the operating range.

3. MODELLING OF GASOLINE AUTO-IGNITION 3.1 Detailed CFD approach

Therefore the combustion process was analyzed during mode changes from conventional spark ignition operation to autoignition and vice versa. Additionally the auto-ignition valve timing strategy was varied. Figure 3 shows exemplarily the change between CCR auto-ignition, spark ignition (SI) and EPR auto-ignition at n = 2000 min-1 and IMEP = 3 bar. Similar steps in valve timing strategy, injection duration, and injection timing were used for identification of the control path and for the ongoing layout of the controller. Figure 3 shows that a transient operation is possible, and simultaneously shows the challenges for highly transient operations. During the mode change from spark ignition to gasoline auto-ignition an advanced combustion can be observed, which results in an undesirable high peak pressure. Such operating conditions have to be avoided by controller intervention, to consider the increased customer comfort awareness. With the knowledge of this base analysis, different engine models for a setup and layout of a closedloop controller will be investigated. The steady-state data in Figure 3 are the expectation values, which are the averaged results of previously performed steady-state investigation. In comparison to the transient values the typical cycle variations can be observed in all parameters, which are caused by slightly different combustions. However, the standard deviation of IMEP is less than 0.1 bar in the steady-state

For the fundamental analysis of gasoline auto-ignition different CAE tools are used. The focus of this work is the description of the utilized reduction steps from a detailed 3D CFD model with a high demand for computational time to a reduced model formulation with decreased CPU cost. 3D CFD simulations are used to investigate the flow field, injection, and mixture formation inside the combustion chamber. Therefore, a mesh containing approx. 1.3 million cells including the combustion chamber and gas exchange ports was prepared within the commercial CFD code StarCD. From the calculated results, the distribution functions of fuel and residual gas inside the cylinder are obtained and summarized in characteristic values. It was shown in [5] that the distributions of fuel, residual gas, and air in the combustion chamber have an influence on the burn function and can be controlled by injection timing and valve timing strategy. Furthermore the calculation of reaction kinetics within the open-source chemistry solver Cantera [7] is coupled to the CFD simulation. The used mechanism for iso-Octane from Golovitchev [8] contains 84 species and 412 reactions and is

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inside the combustion chamber. This accompanies with the high demand for computational cost. One high pressure cycle can be calculated within 24 hours in parallel on four 2.8 GHz processors.

Residual Gas Mass Fraction [-]

capable to calculate the auto-ignition under engine conditions. Within the CFD calculations the influence on the thermodynamic state by the heat release of reaction progress during fuel conversion is regarded. A combustion model for the detailed calculation of gasoline auto-ignition has to account for the influence of global values of residual gas mass fraction and air/fuel ratio on fuel conversion and also the different distributions of both for varying operating conditions. For this reason a multi-zone reaction kinetics approach is chosen [9]. The individual zones are defined in the phase space. A classification in up to three dimensions is conceivable. The mixture can be considered by residual gas and fuel mass fraction. Furthermore a classification by temperature or enthalpy is possible. Correlating distributions of the mentioned coordinates were verified in [6] and [10] for the considered operating point with an early direct injection timing of EOI = 420 °CA ATDC and both residual gas recirculation strategies CCR and EPR. Figure 4 shows exemplarily the mass distribution in phase space for CCR strategy at n = 2000 min-1 and IMEP = 3 bar with an injection timing EOI = 420 °CA ATDC at the crank angle position ϕ = 10 °CA BTDC. A correlation between the mixture fraction Z and the residual gas mass fraction in the upper diagram is obvious. The second diagram shows the relation between the mixture fraction and temperature. Even if the correlation is not as clear as in the previous case one can see that especially the phase space coordinates which contain most of the mass can be described by only one dimension. For this reason a one dimensional multi-zone model is introduced here.

2e-6

Temperature [K]

2e-5

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

900

From CFD calculations the information of mixture fraction Z, residual gas mass fraction xR, temperature T, pressure p and mass m of all cells are analyzed and transferred into a one dimensional classification according to e.g. temperature. The mixture, temperature and pressure are treated as homogenous within each zone by providing mean quantities. The model calculates the heat release from chemical reactions at every time step of the CFD simulation according to the thermodynamic boundary conditions during compression and expansion of the engine and the mixture composition from previous time steps.. Additionally, the mass transport between the zones is considered by an attached transport model. The heat release and accumulated heat release are transferred back to CFD. Furthermore the changing material properties due to combustion and the density as a function of the gas constant are committed.

Mass [kg]

Mixture Fraction Z [-]

850 800 750 700 650 600 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Mixture Fraction [-] Fig. 4. Correlation between mixture and temperature from CFD simulation, CCR strategy 3.2 Model reduction of high pressure cycle simulation To minimize the computational costs for the simulation of the auto-ignition and combustion as stated before, a reduction of the detailed model is introduced. The simulation of the gas exchange stroke and the compression with CFD was done for a large number of operating points of the engine and validated against experimental results from the test bench. To resolve the distributions of fuel, residual gas, fresh air and temperature, the characteristic values mean and normalized standard deviation are used to initialize a limited number of discrete zones for reaction kinetic calculations. Again, the operating point with an injection timing EOI = 420 °CA ATDC is considered. The reduced formulation does not contain a transport model so far. The individual reactors are coupled by pressure exchange. Hence,

Figure 5 shows the result of a detailed calculation with CFD and coupled combustion model with 100 zones of CCR gasoline auto-ignition operation at n = 2000 min-1 and IMEP = 3 bar with an injection timing EOI = 420 °CA ATDC. The spatial distribution of ignition is shown by an iso-surface of 50 % mass fraction burnt in the combustion chamber. Several spots of auto-ignition can be found across the combustion chamber for this operating point, mainly close to the exhaust valves as can be seen in the lower part of the picture. The timing of this image is ϕ = 2 °CA ATDC. The 3D CFD calculation delivers detailed information about the thermodynamic state and the mixture

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a uniform pressure is assumed in the combustion chamber. With the consideration of statistical values of the mixture and temperature stratification in the reaction kinetics calculation, the approach still uses the knowledge of the CFD analysis [5].

good. While the CFD model overpredicts the maximum pressure, the reduced formulation underpredicts it in the order of 1 bar. The location of MFB 50 % agrees well. During compression and expansion the traces from simulations fit the measured one. 50

Cylinder pressure [bar]

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Crank angle [°CA ATDC] Fig. 6. Comparison of the pressure traces from experiment and simulation Within the reduced model the high pressure cycle is calculated regarding the piston work and heat transfer losses according to the approach of Hohenberg [11]. In Figure 7 the individual temperature traces from the individual zones as calculated are plotted. Depending on mixture and temperature the reactors ignite at different times. There are also reactors that can not converse the complete mixture and remain at relatively low temperatures. In these zones, the thermodynamic state for complete conversion is not reached during compression. Either the mixture or the temperature avoids complete combustion. Figure 8 shows the calculated pressure traces of a residual gas mass fraction variation in comparison to test bench results. It can be seen that both the center of combustion and the maximum pressure rise can be calculated in good agreement with the experimental results.

Intake

2500

Temperature [K]

Fig. 5. Spatial distributed, CCR gasoline auto-ignition Again, stratification of air/fuel ratio, residual gas and gas temperature are possible factors. Since gas temperature, residual gas mass fraction and mixture fraction correlate, two dimensions are reduced again in this approach as was already described for the detailed model. The individual reactors are initialized with mass according to a Gaussian distribution. Therefore mean values and standard deviations of rel. air/fuel ratio, residual gas mass fraction or mixture fraction are necessary and can be extracted from the CFD analysis. Figure 6 shows pressure traces of the CCR operating point already shown in Figure 5. A comparison between measured trace from experiment with the results of CFD calculation and reduced modeling are depicted. The reduced model was used with nine zones. The agreement between the traces is

2000 1500 1000 500 0 -40

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Crank angle [°CA ATDC] Fig.7. Calculated temperature traces of individual zones

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The calculation time needed for one high pressure cycle is less than 5 minutes on a 2 GHz processor. This tremendous decrease in computational cost comes along with the loss of spatial resolution in the combustion chamber. A statistical understanding of the mixture state is also needed which increases the computational effort again.

Therefore this approach exceeds a suitable time frame for larger multi-cycle simulation.

Cylinder Pressure [bar]

40 30 20 10 0 -40

Sim. 53.9 % 50.5 % 49.0 %

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Crank angle [°CA ATDC] Fig.8. Calculated pressure traces of residual gas mass fraction variation with reduced model

1600 1200 800 400 1.00

Mass Fraction Burned [-]

3.3 Gas exchange calculation with kinetic burn function To further reduce the computational time for the calculation of the auto-ignition process under stationary and transient operating conditions by means of 1D gas exchange calculation, a second simulation tool was developed to analyze the process with embedded burn function.

0.20

0.75

0.15 0.50 0.10 0.25 0.00 -40 -30 -20 -10 0 10 20 30 Crank angle [°CA ATDC]

In a first step, the calculation of reaction kinetics as stated above within the reduced model is coupled to 1D gas exchange calculations with the commercial tool GT-Power. The heat release is calculated by reaction kinetics depending on the cyclic boundary conditions of mixture and thermodynamic state. The boundary conditions of each cycle are simulated within the gas exchange calculation. Figure 9 shows a simulation result of a single cycle combustion at n = 2000 min-1 and IMEP = 3 bar compared to the test bench result. The cylinder fresh charge again was divided into nine zones. A very good agreement compared to the test bench result can be achieved. The highest deviation in the cylinder pressure trace is approximately 2 bar. This is a result of the reaction kinetic, which starts conversion earlier than the thermodynamic analysis. However, after a maximum deviation of 5 % at a BMF of 25 % the deviation decreases. Therefore the transfer from the stand alone reduced reaction kinetic to the coupled 1D gas exchange with the reduced reaction kinetic is successfully performed. The coupled model is now able to reflect the engine behavior regarding residual gas mass fraction, injection duration and timing variations. However, the total computational time is mainly dominated by the computational time of the reaction kinetics.

0.25

0.05 40

∆ Mass Fraction Burned [-]

Exp.

Cylinder Temperature [K]

Cylinder pressure [bar]

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∆ Cyl. Pressure [bar]

Combustion Chamber Recirculation n = 2000 min-1, IMEP = 3 bar, EGR = 48.9 % Test Bench Data Simulation with 9-Zones Difference between Test Bench and Model

0.00

Fig. 9. Simulation results of a reaction kinetics with 1D gas exchange calculation For this reason, the next step is to avoid the online calculation of the reaction kinetics. Therefore it is planned to model the combustion process with a polynomial or a neuronal network approach using an approximation of the combustion trace. A design of experiment setup will be used for the initialization of the reduced reaction kinetics. The resulting traces of the burned mass fraction will be fitted to a mathematic approximation whereby the parameters of this approximation will be modeled with a polynomial approach. In a first step the polynomial functions are based on test bench data and not on the reaction kinetic. An outlook to that approach is given in Figure 10. The test bench data where gathered from a closed loop controlled auto-ignition test with a fixed injection timing. In the top two graphs IMEP, and the location of 50 % MFB are shown of the test bench data (solid line) and the target value (dashed line). The output signals of the controller are the injection duration and the NVO (Negative Valve Overlap) of the EMVT and are plotted in the bottom two graphs. The load point of IMEP = 2.5 bar has a stable

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combustion with a standard deviation below 0.1 bar. However, due to cycle deviations, the standard deviation of the MFB 50 % is 2.6 °CA. Even in the transient behavior between IMEP = 1.5 to 4 bar, the actual value of IMEP can be controlled to the target value. Approaching the boarder of the operation area at IMEP = 4 bar to high load the operating conditions become unstable. Whereby unstable operation is considered at IMEP standard deviation above 0.15 bar, resulting also in higher standard deviations of the MFB 50 %. However, this will be improved by optimizing the injection timing strategy.

based on the reaction kinetic data. Additionally a coupling of this model to a controller design environment for synchronous simulation and control will be investigated. 4. SUMMARY High efficiency and near zero NOx-emissions, which exclude an expensive exhaust gas after treatment are the main motivation for ongoing research on gasoline auto-ignition. However, this sensitive combustion process is limited to part load conditions. At high loads and high engine speeds the combustion is limited by steep pressure gradients, at low loads and low speeds the combustion is limited by combustion stability. The first part of this paper deals with experimental results from transient test bench investigations. The operating limits for gasoline auto-ignition are shown and the need for a future controller concept is presented by means of the example to avoid an unintentional acoustic behavior during a mode change from conventional SI mode to autoignition operation.

The controller values of this actuation test where used as input data of the 1D gas exchange model using a polynomial approach for the combustion behavior to check the functionality of this approach. The results are plotted as grey solid line. A good correlation between the test bench data and the simulation values can be detected, especially for the IMEP. However, the cycle deviations of the real engine are not yet implemented in the model.

The goal of the combustion development is to analyze the low temperature combustion and to model its process. Therefore, several simulation tools are developed and discussed which allow the calculation of the complex process in different detail levels. The gained knowledge will be used for the controller layout for transient operation, an extension of the operating area as well as a stabilization of the combustion process.

Combustion Chamber Recirculation at n = 2000 min-1 Actual Values Target Values Simulated Values Control Values 5

IMEP

[bar]

4

A coupled CFD model with reaction kinetics is presented to calculate the combustion and to identify the thermodynamic boundary conditions and stratification effects of the autoignition. Results of the CFD simulation for Combustion Chamber Recirculation are presented with a good agreement to experimental investigations. Based on these results a reduced combustion model is developed to decrease the computational costs for the calculation. Again, good agreement with experimental results is obtained.

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[°CA ATDC]

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Location of MFB 50 %

10 0

In the last part of this report, the coupling of the reduced model with a 1D gas exchange simulation is presented. This coupling allows a multi-cycle simulation in an appropriate time frame and can be used for future training of the controller or for a valve train layout.

[°CA]

[ms]

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Injection Duration

EMVT Negativ Valve Overlap

ACKNOWLEDGEMENTS

200

The authors would like to thank the German Society of Research (DFG) for the financial funding of this work in the Collaborative Research Centre “SFB 686 – Modellbasierte Regelung der homogenisierten Niedertemperatur-Verbrennung”.

100 1200 1300 1400 1500 1600 1700 1800 1900 2000 Cycle [-]

Fig. 10. Simulation results of 1D gas exchange calculation compared to a controlled test bench sequence at n = 2000 min-1

Further thanks to the Institute for Automatic Control IRT, RWTH-Aachen University.

With this model approach the calculation time can be reduced to approximately 2 sec per cycle or to approximately 1 h for 2000 cycles. In future work the polynomial model will be

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REFERENCES [1] Collaborative Research Centre „SFB 686 – Modellbasierte Regelung der homogenisierten NiedertemperaturVerbrennung“, RWTH Aachen University and University Bielefeld http://www.sfb686.rwth-aachen.de [2] Lavy, J., Dabadie, J.-C., Duret, P., Angelberger, C., Le Coz, J.-F. and Charel, J. (2001). Controlled Auto-Ignition (CAI): A new highly efficient and near-zero NOx-emission combustion process for gasoline engine application. IFP International Congress 2001 [3] Jelitto, C., Willand, J., Jakobs, J., Magnor, O., Schultalbers, M. and Schnaubelt, M. (2008). Das GCIBrennverfahren von Volkswagen. MTZ 04/2008 Volume 69. [4] Thring, R.H. (1989). Homogeneous Charge Compression Ignition (Hcci) Engines. SAE 892068 [5] Pischinger, S., Stapf, K.G., Seebach, D., Bücker, C., Adomeit, P. and Ewald, J. (2008). Controlled Auto-Ignition: Combustion Rate Shaping by Mixture Stratification. Vienna Motor Symposium 2008 [6] Stapf, K.G., Seebach, D., Fricke, F., Pischinger S., Hoffmann, K. and Abel, D. (2007). CAI-Engines: Modern combustion system to face future challenges. SIA International Conference – The Spark Ignition Engine of the Future 2007 [7] cantera – An object-oriented software toolkit for chemical kinetics, thermodynamics, and transport processes. http://code.google.com/p/cantera/ [8] Golovitchev, V. Semi-detailed mechanism for iso-octane auto-ignition, (accessed 2006) http://www.tfd.chalmers.se/~valeri/MECH.html [9] Stapf, K.G., Seebach, D., Pischinger, S., Hoffmann, K., Abel, D. (2009). Aspects of Gasoline Controlled Auto Ignition – Development of a Controller Concept. MTZ 04/2009 Volume 70 [10] Adomeit, P., Ewald, J., Stapf, K.G., Seebach, D. and Pischinger S. (2008). Control and Prediction of the Stochastic Ignition Process for a Gasoline CAI Combustion System. 8. Internationales Symposium für Verbrennungsdiagnostik 2008 [11] Hohenberg, G.F. Advanced Approaches for Heat Transfer Calculations (1979). SAE 790825

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