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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.

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.

Water injection is a promising technology to improve the fuel efficiency of turbocharged gasoline engines due to the possibility to suppress engine knock. Additionally, this technology is believed to enable the efficient operation of the three-way catalyst also at high-load conditions, through limiting the exhaust temperature. In this numerical study, we investigate the effect of water on the chemical and thermodynamic processes using 3D computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) with detailed chemistry. In the first step, the influence of different amounts of water vapor on ignition delay time, laminar flame speed, and heat capacity is investigated. In the second step, the impact of water vaporization is analyzed for port and direct injection. For this purpose, the water mass flow and the injection pressure are varied.

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.

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.

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.

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.

In this paper an online method for automatically reducing complex chemical mechanisms for simulations of combustion phenomena has been developed. The method is based on the Quasi Steady State Assumption (QSSA). In contrast to previous reduction schemes where chemical species are selected only when they are in steady state throughout the whole process, the present method allows for species to be selected at each operating point separately generating an adaptive chemical kinetics. The method is used for calculations of a natural gas fueled engine operating under Homogenous Charge Compression Ignition (HCCI) conditions. We discuss criteria for selecting steady state species and the influence of these criteria on the results such as concentration profiles and temperature.

This paper focuses on the performance and efficiency of an HCCI (Homogenous Charge Compression Ignition) engine system running on natural gas or landfill gas for stationary applications. Zero dimensional modeling and simulation of the engine, turbo, inlet and exhaust manifolds and inlet air conditioner (intercooler/heater) are used to study the effect of compression ratio and exhaust turbine size on maximum mean effective pressure and efficiency. The extended Zeldovich mechanism is used to estimate NO-formation in order to determine operation limits. Detailed chemical kinetics is used to predict ignition timing. Simulation of the in-cylinder process gives a minimum λ-value of 2.4 for natural gas, regardless of compression ratio. This is restricted by the NO formation for richer mixtures. Lower compression ratios allow higher inlet pressure and hence higher load, but it also reduces indicated efficiency.

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.

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions.

Large two-stroke marine Diesel engines have special injector geometries, which differ substantially from the configurations used in most other Diesel engine applications. One of the major differences is that injector orifices are distributed in a highly non-symmetric fashion affecting the spray characteristics. Earlier investigations demonstrated the dependency of the spray morphology on the location of the spray orifice and therefore on the resulting flow conditions at the nozzle tip. Thus, spray structure is directly influenced by the flow formation within the orifice. Following recent Large Eddy Simulation resolved spray primary breakup studies, the present paper focuses on spray secondary breakup modelling of asymmetric spray structures in Euler-Lagrangian framework based on previously obtained droplet distributions of primary breakup.

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.