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The subject of this work is 3D numerical simulations of combustion and soot emissions for a passenger car diesel engine. The CFD code STAR-CD version 3.26 [1] is used to resolve the flowfield. Soot is modeled using a detailed kinetic soot model described by Mauss [2]. The model includes a detailed description of the formation of polyaromatic hydrocarbons. The coupling between the turbulent flowfield and the soot model is achieved through a flamelet library approach, with transport of the moments of the soot particle size distribution function as outlined by Wenzel et al. [3]. In this work we extended this approach by considering acetylene feedback between the soot model and the combustion model. The model was further improved by using new gas-phase kinetics and new fitting procedures for the flamelet soot library.

Interactions between in-cylinder combustion and emission aftertreatment need to be understood for optimizing the overall powertrain system. Numerical investigations can aid this process. For this purpose, simple and numerically fast, but still accurate models are needed for in-cylinder combustion and exhaust aftertreatment. The chemical processes must be represented in sufficient detail to predict engine power, fuel consumption, and tailpipe emission levels of NOx, soot, CO and unburned hydrocarbons. This paper reports on a new transient one-dimensional catalyst model. This model makes use of a detailed kinetic mechanism to describe the catalytic reactions. A single-channel or a set of representative channels are used in the presented approach. Each channel is discretized into a number of cells. Each cell is treated as a perfectly stirred reactor (PSR) with a thin film layer for washcoat treatment. Heat and mass transport coefficients are calculated from Nusselt and Sherwood laws.

This paper reports on a turbulent flame propagation model combined with a zero-dimensional two-zone stochastic reactor model (SRM) for efficient predictive SI in-cylinder combustion calculations. The SRM is a probability density function based model utilizing detailed chemistry, which allows for accurate knock prediction. The new model makes it possible to - in addition - study the effects of fuel chemistry on flame propagation, yielding a predictive tool for efficient SI in-cylinder calculations with all benefits of detailed kinetics. The turbulent flame propagation model is based on a recent analytically derived formula by Kolla et al. It was simplified to better suit SI engine modelling, while retaining the features allowing for general application. Parameters which could be assumed constant for a large spectrum of situations were replaced with a small number of user parameters, for which assumed default values were found to provide a good fit to a range of cases.

The Homogeneous Charge Compression Ignition (HCCI) is the third alternative for combustion in the reciprocating engine. Here, a homogeneous charge is used as in a spark ignited engine, but the charge is compressed to auto-ignition as in a diesel. The main difference compared with the Spark Ignition (SI) engine is the lack of flame propagation and hence the independence from turbulence. Compared with the diesel engine, HCCI has a homogeneous charge and hence no problems associated with soot and NOX formation. Earlier research on HCCI showed high efficiency and very low amounts of NOX, but HC and CO were higher than in SI mode. It was not possible to achieve high IMEP values with HCCI, the limit being 5 bar. Supercharging is one way to dramatically increase IMEP. The influence of supercharging on HCCI was therefore experimentally investigated. Three different fuels were used during the experiments: iso-octane, ethanol and natural gas.

Cycle-resolved end-gas temperatures were measured using dual-broadband rotational CARS in a single-cylinder spark-ignition engine. Simultaneous cylinder pressure measurements were used as an indicator for knock and as input data to numerical calculations. The chemical processes in the end-gas have been analysed with a detailed kinetic mechanism for mixtures of iso-octane and n-heptane at different Research Octane Numbers (RON'S). The end-gas is modelled as a homogeneous reactor that is compressed or expanded by the piston movement and the flame propagation in the cylinder. The calculated temperatures are in agreement with the temperatures evaluated from CARS measurements. It is found that calculations with different RON'S of the fuel lead to different levels of radical concentrations in the end-gas. The apperance of the first stage of the autoignition process is marginally influenced by the RON, while the ignition delay of the second stage is increased with increasing RON.

In one-dimensional engine simulation programs the simulation of engine performance is mostly done by parameter fitting in order to match simulations with experimental data. The extensive fitting procedure is especially needed for emissions formation - CO, HC, NO, soot - simulations. An alternative to this approach is, to calculate the emissions based on detailed kinetic models. This however demands that the in-cylinder combustion-flow interaction can be modeled accurately, and that the CPU time needed for the model is still acceptable. PDF based stochastic reactor models offer one possible solution. They usually introduce only one (time dependent) parameter - the mixing time - to model the influence of flow on the chemistry. They offer the prediction of the heat release, together with all emission formation, if the optimum mixing time is given.

This paper explains the principle and advantages of the Ignition Progress Variable Library (IPV-Library) approach and its use in predicting engine related premixed, non-premixed and compression ignited combustion events. The implementation of IPV-Library model in the engine-focused CFD code VECTIS is described. To demonstrate the application of the model in predicting various types of combustion, computational results from a 2-stroke HCCI engine, a premixed spark ignition engine and an HSDI diesel engine are presented, together with some comparisons with engine test data.

The formation of exothermic centers was modeled with a Stochastic Reactor Model (SRM) to investigate their impact on HCCI combustion. By varying the exhaust valve temperature, and thus assigning more realistic wall temperatures, the formation of exothermic centers and the ignition timing was shifted in time. To be able to study the exothermic centers, their formation and their distribution, Scatter plots, standard deviation plots and Probability Density Function (PDF) plots were constructed on the basis of the data the SRM calculations provided. The standard deviation for the particle temperatures was found to be an useful indicator of the degree of homogeneity within the combustion chamber, and thus of how efficient the combustion process was. It was observed that when the standard deviation of the temperature was higher, the emissions of CO and of hydrocarbons present at the end of the closed cycle were higher.

Operating the HCCI engine with dual fuels with a large difference in auto-ignition characteristics (octane number) is one way to control the HCCI operation. The effect of octane number on combustion, emissions and engine performance in a 6 cylinder SCANIA truck engine, fuelled with n-heptane and isooctane, and running in HCCI mode, are investigated numerically and compared with measurements taken from Olsson et al. [SAE 2000-01-2867]. To correctly simulate the HCCI engine operation, we implement a probability density function (PDF) based stochastic reactor model (including detailed chemical kinetics and accounting for inhomogeneities in composition and temperature) coupled with GT-POWER, a 1-D fluid dynamics based engine cycle simulator. Such a coupling proves to be ideal for the understanding of the combustion phenomenon as well as the gas dynamics processes intrinsic to the engine cycle.

SI Engine knock is caused by autoignition in the unburnt part of the mixture (end-gas) ahead of the propagating flame. Autoignition of the end-gas occurs when the temperature and pressure exceeds a critical limit when comparatively slow reactions-releasing moderate amounts of heat-transform into ignition and rapid heat release. In this paper the difference in the heat released in the end-gas-by low temperature chemistry-between lean, rich, stochiometric, and stoichiometric mixtures diluted with cooled EGR was examined by measuring the temperature in the end-gas with Dual Broadband Rotational CARS. The measured temperature history was compared with an isentropic temperature calculated from the cylinder pressure trace. The experimentally obtained values for knock onset were compared with results from a two-zone thermodynamic model including detailed chemistry modeling of the end-gas reactions.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

The three-way catalytic converter (TWC) is the most common catalyst for gasoline engine exhaust gas after treatment. The reduction of carbon monoxide (CO), nitrogen oxides (NOx) and unburned hydrocarbons (HC) is achieved via oxidation of carbon monoxide and hydrocarbons, and reduction of nitrogen oxides. These conversion effects were simulated in previous works using single-channel approaches and detailed kinetic models. In addition to the single-channel model multiple representative catalyst channels are used in this work to take heat transfer between the channels into account. Furthermore, inlet temperature distribution is considered. Each channel is split into a user given number of cells and each cell is treated like a perfectly stirred reactor (PSR). The simulation is validated against an experimental four-stroke engine setup with emission outputs fed into a TWC.

Stringent exhaust emission limits and new vehicle test cycles require sophisticated operating strategies for future diesel engines. Therefore, a methodology for predictive combustion simulation, focused on multiple injection operating points is proposed in this paper. The model is designated for engine performance map simulations, to improve prediction of NOx, CO and HC emissions. The combustion process is calculated using a zero dimensional direct injection stochastic reactor model based on a probability density function approach. Further, the formation of exhaust emissions is described using a detailed reaction mechanism for n-heptane, which involves 56 Species and 206 reactions. The model includes the interaction between turbulence and chemistry effects by using a variable mixing time profile. Thus, one is able to capture the effects of mixture inhomogeneities on NOx, CO and HC emission formation.

A self-calibrating model for Diesel engine simulations is presented. The overall model consists of a zero-dimensional direct injection stochastic reactor model (DI-SRM) for engine in-cylinder processes simulations and a package of optimization algorithms (OPAL) suitable for solving various optimization, automatization and search problems. In the DI-SRM, based on an extensive model parameters study, the mixing time history that affects the level of in-cylinder turbulence was selected as a main calibration parameter. As targets during calibration against the experimental data, in-cylinder pressure history and engine-out emissions, including nitrogen oxides and unburned hydrocarbons were chosen. The calibration task was solved using DI-SRM and OPAL working as an integrated tool. Within OPAL, genetic algorithms (GA) were used to determine model constants necessary for calibrating. Engine-out emissions in DI-SRM were calculated based on the reduced mechanism of n-heptane.

This paper reports on a fast predictive combustion tool employing detailed chemistry. The model is a stochastic reactor based, discretised probability density function model, without spatial resolution. Employing detailed chemistry has the potential of predicting emissions, but generally results in very high CPU costs. Here it is shown that CPU times of a couple of minutes per cycle can be reached when applying detailed chemistry, and CPU times below 10 seconds per cycle can be reached when using reduced chemistry while still catching in-cylinder in-homogeneities. This makes the tool usable for efficient engine performance mapping and optimisation. To meet CPU time requirements, automatically load balancing parallelisation was included in the model. This allowed for an almost linear CPU speed-up with number of cores available.

The influence of variable air-fuel ratio inside a spark ignition engine is examined by the use of an ionization sensor. The measured ion currents are used for predicting the local air-fuel ratio in the vicinity of the spark plug. In order to support the results, a theoretical analysis has been made. An instationary chemical kinetic model burning a mixture of iso-octane and n-heptane is used for the calculations. The results are used to reconstruct the crank angle resolved ion current that has been measured in an engine. This technique has been developed in order to offer a supplementary low-cost facility of controlling the air-fuel ratio within the combustion chamber of an engine.

We present a computational tool to develop an exhaust gas recirculation (EGR) - air-fuel ratio (AFR) operating range for homogeneous charge compression ignition (HCCI) engines. A single cylinder Ricardo E-6 engine running in HCCI mode, with external EGR is simulated using an improved probability density function (PDF) based engine cycle model. For a base case, the in-cylinder temperature and unburned hydrocarbon emissions predicted by the model show a satisfactory agreement with measurements [Oakley et al., SAE Paper 2001-01-3606]. Furthermore, the model is applied to develop the operating range for various combustion parameters, emissions and engine parameters with respect to the air-fuel ratio and the amount of EGR used. The model predictions agree reasonably well with the experimental results for various parameters over the entire EGR-AFR operating range thus proving the robustness of the PDF based model.

Calculations using homogeneous and stochastic reactor models were performed in order to find an explanation to observed properties of NOx HCCI engines. It was found that for moderate NOx levels, N2O reactions play an important role in the NOx formation. Further, the high proportions of NO2 found in from some HCCI engines is due to high temperature inhomogeneities, poor mixing and slow overall combustion. N2O is often emitted from HCCI combustion. The levels of NOx in the exhausts are highly sensitive to temperature; however N2O has a weak negative dependence on temperature. While fuel rich operation naturally leads to high temperatures and thus high NOx levels; once the temperature effects are decoupled the fuel rich conditions themselves has a favorable effect on low-NOx engine operation.

The development of future gasoline engines is dominated by the study of new technologies aimed at reducing the engine negative environmental impact and increase its thermal efficiency. One common trend is to develop smaller engines able to operate in stoichiometric conditions across the whole engine map for better efficiency, lower fuel consumption, and optimal conversion rate of the three-way catalyst (TWC). Water injection is one promising technique, as it significantly reduces the engine knock tendency and avoids fuel enrichment for exhaust temperature mitigation at high power operation. With the focus on reducing the carbon footprint of the automotive sector, another vital topic of research is the investigation of new alternative CO2-neutral fuels or so-called eFuels. Several studies have already shown how these new synthetic fuels can be produced by exploiting renewable energy sources and can significantly reduce engine emissions.

This paper reports an one–dimensional modeling procedure of the hot spot autoignition with a detailed chemistry and multi–species transport in the end gas in an SI engine. The governing equations for continuity of mass, momentum, energy and species for an one–dimensional, unsteady, compressible, laminar, reacting flow and thermal fields are discretized and solved by a fully implicit method. A chemical kinetic mechanism is used for the primary reference fuels n–heptane and iso–octane. This mechanism contains 510 chemical reactions and 75 species. The change of the cylinder pressure is calculated from both flame propagation and piston movement. The turbulent velocity of the propagating flame is modeled by the Wiebe function. Adiabatic conditions, calculated by minimizing Gibb's free energy at each time step, are assumed behind the flame front in the burned gas.