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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.

Advanced combustion concepts such as reactivity controlled compression ignition (RCCI) have been proven to be capable of fundamentally improve the conventional Diesel combustion by mitigating or avoiding the soot-NOx trade-off, while delivering comparable or better thermal efficiency. To further facilitate the development of the RCCI technology, a robust and possibly computationally efficient simulation framework is needed. While many successful studies have been published using 3D-CFD coupled with detailed combustion chemistry solvers, the maturity level of the 0D/1D based software solution offerings is relatively limited. The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available.

Today’s car manufactures inevitably have to focus on the reduction of fuel consumption while maintaining high performance standards. In this respect, the downsized turbocharged DISI (Direct Injection Spark Ignition) engine represents an appealing solution. However, downsizing is limited because of knocking phenomena occurring at high- and full-load conditions due to autoignition of the unburned mixture ahead the flame front. A common way of reducing knock tendencies is provided by Exhaust Gas Recirculation (EGR). However, EGR modifies the chemical composition of the cylinder charge and recirculated species like nitric oxide (NO) or unburned Hydrocarbons (HC) particularly increase the reactivity of the unburned mixture. In other words, the EGR influences the Octane Number (ON) of the in-cylinder gases.

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.

Previous work has shown that it may be advantageous to use gasoline type fuels with long ignition delays compared to today's diesel fuels in compression ignition engines. In the present work we investigate if high volatility is also needed along with low cetane (high octane) to get more premixed combustion leading to low NO and smoke. A single-cylinder light-duty compression ignition engine is run on four fuels in the diesel boiling range and three fuels in the gasoline boiling range. The lowest cetane diesel boiling range fuel (DCN = 22) also has very high aromatic content (75%vol) but the engine can be run on this to give very low NO (≺ 0.4 g/kWh) and smoke (FSN ≺ 0.1), e.g,. at 4 bar and 10 bar IMEP at 2000 RPM like the gasoline fuels but unlike the diesel fuels with DCNs of 40 and 56. If the combustion phasing and delay are matched for any two fuels at a given operating condition, their emissions behavior is also matched regardless of the differences in volatility and composition.

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.

A detailed analysis of the end-gas temperature and pressure in gasoline engines has been performed. This analysis leads to a simplified zero-dimensional model, that considers both, the compression and the expansion of the end-gas by the piston movement, and the compression by the flame front. If autoignition occurs in the end-gas the sudden rise of the pressure and the heat release is calculated. The rate form of the first law of thermodynamics for a control volume combined with the mass conservation equation for an unsteady and a uniform-flow process are applied. The heat of formation in the end-gas due to the chemical activity has been taken into account. In addition, a chemical kinetic model has been applied in order to study the occurrence of autoignition and prediction of knock.

Concentrations of hydroxyl radicals and formaldehyde were calculated using homogeneous (HRM) and stochastic reactor models (SRM), and the result was compared to LIF-measurements from an optically accessed iso-octane / n-heptane fuelled homogeneous charge compression ignition (HCCI) engine. The comparison was at first conducted from averaged total concentrations / signal strengths over the entire combustion volume, which showed a good qualitative agreement between experiments and calculations. Time- and the calculation inlet temperature resolved concentrations of formaldehyde and hydroxyl radicals obtained through HRM are presented. Probability density plots (PDPs) through SRM calculations and LIF-measurements are presented and compared, showing a very good agreement considering their delicate and sensitive nature.

High-speed video imaging in a swirl-supported (Rs = 1.7), direct-injection heavy-duty diesel engine operated with moderate-to-high EGR rates reveals a distinct correlation between the spatial distribution of luminous soot and mean flow vorticity in the horizontal plane. The temporal behavior of the experimental images, as well as the results of multi-dimensional numerical simulations, show that this soot-vorticity correlation is caused by the presence of a greater amount of soot on the windward side of the jet. The simulations indicate that while flow swirl can influence pre-ignition mixing processes as well as post-combustion soot oxidation processes, interactions between the swirl and the heat release can also influence mixing processes. Without swirl, combustion-generated gas flows influence mixing on both sides of the jet equally. In the presence of swirl, the heat release occurs on the leeward side of the fuel sprays.

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.

A transient interactive flamelet model and a transient flamelet library based model are used to model a medium-duty diesel fueled engine operating in PCCI mode. The simulations are performed with and without the source term accounting for evaporation in the mixture fraction variance equation. Reasonable agreement is found with the experiments with both models. The effect of the evaporation source term in the mixture fraction variance equation is different for the different transient flamelet approaches. For the transient interactive flamelet model the ignition onset is delayed as a consequence of the higher mixture fraction variance, which leads to a higher scalar dissipation rate. The evaporation source term does not affect the global characteristics of the ignition event for the transient flamelet progress variable model, but locally the initial combustion is occurring differently.

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.

The ability to predict cyclic variations is certainly useful in studying engine operating regimes, especially under unstable operating conditions where one single cycle may differ from another substantially and a single simulation may give rather misleading results. PDF based models such as Stochastic Reactor Models (SRM) are able to model cyclic variations, but these may be overpredicted if discretization is too coarse. The range of cyclic variations and the dependence of the ability to correctly assess their mean values on the number of cycles simulated were investigated. In most cases, the average values were assessed correctly on the basis of as few as 10 cycles, but assessing the complete range of cyclic variations could require a greater number of cycles. In studying average values, variations due too coarse discretization being employed are smaller than variations originating from changes in physical parameters, such as heat transfer and mixing parameters.

An investigation on reducing the set of modeling parameters for engine cycle simulation is presented. The investigation considers a detailed kinetic model for combustion and emissions predictions coupled to a complete cycle simulation tool applied to a modern Diesel engine. The analysis is based on a previously developed method that combines a 1-D gas dynamics model with a stochastic reactor model for direct injection engines (SRM-DI). Initially, the global and instantaneous performance parameters of a Diesel engine were simulated at different operating conditions. The model was validated and the simulated results were compared to experimental data to assess the quality of the model. Afterwards, the influence of the chosen modeling parameters on engine performance, such as in-cylinder pressure, emissions and global performances, were analyzed. The mixing time proved to be the most important modeling parameter for the stochastic reactor model.

Previous work has showed that it may be advantageous to use fuels of lower cetane numbers compared to today's diesel fuels in compression ignition engines. The benefits come from the longer ignition delays that these fuels have. There is more time available for the fuel and air to mix before combustion starts which is favourable for achieving low emissions of NOx and smoke though premixing usually leads to higher emissions of CO and unburned hydrocarbons. In the present work, operation of a single-cylinder light-duty compression ignition engine on four different fuels of different octane numbers, in the gasoline boiling range, is compared to running on a diesel fuel. The gasoline fuels have research octane numbers (RON) of 91, 84, 78, and 72. These are compared at a low load/low speed condition (4 bar IMEP / 1200 rpm) in SOI sweeps as well as at a higher load and speeds (10 bar IMEP / 2000 and 3000 rpm) in EGR sweeps.

The solution mapping method Adaptive Polynomial Tabulation (APT) for complex chemistry is presented. The method has the potential of reducing the computational time required for stochastic reactor model simulations of the HCCI combustion process. In this method the solution of the initial value chemical rate equation system is approximated in real-time with zero, first and second order polynomial expressions. These polynomials are algebraic functions of a progress variable, pressure and total enthalpy. The chemical composition space is divided a priori into block-shaped regions (hypercubes) of the same size. Each hypercube may be divided in real-time into adaptive hypercubes of different sizes. During computations, initial conditions are stored in the adaptive hypercubes. Two concentric Ellipsoids of Accuracy (EOA) are drawn around each stored initial condition.

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.