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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.

Along the last years, engine researchers are more and more focusing their efforts on the advanced low temperature combustion (LTC) concepts with the aim of achieving the stringent limits of the current emission legislations. In this regard, several studies based on highly premixed combustion concepts such as HCCI has been confirmed as a promising way to decrease drastically the most relevant CI diesel engine-out emissions, NOx and soot. However, the major HCCI drawbacks are the narrow load range, bounded by either misfiring (low load, low speed) or hardware limitations (higher load, higher speeds) and the combustion control (cycle-to-cylce control and combustion phasing). Although several techniques have been widely investigated in order to overcome these drawbacks, the high chemical reactivity of the diesel fuel remains as the main limitation for the combustion control.

Emissions regulations for engine and vehicle manufacturers are bound to become more limiting to prevent greenhouse gas emissions and mitigate the negative effects that potentiate global warming. To fulfill the energy demand necessary in the transportation sector for the short-to-medium term, a parallel optimization of the internal combustion engine, powertrain and fuels is necessary. The combination of novel combustion modes like the reactivity-controlled compression ignition (RCCI), that seeks the benefits of both compression ignition and spark ignition engines, with the so-called e-fuels, that reduce the carbon footprint from well-to-wheel, is worth exploring. This work investigates the potential of the RCCI concept using OMEx-gasoline to reduce the engine-out emissions beyond the current EURO VI legislation. To do so, eight representative operating conditions from several driving cycles for heavy-duty vehicles will be explored experimentally.

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 work investigates the particulates size distribution of reactivity controlled compression ignition combustion, a dual-fuel concept which combines the port fuel injection of low-reactive/gasoline-like fuels with direct injection of highly reactive/diesel-like fuels. The particulates size distributions from 5-250 nm were measured using a scanning mobility particle sizer at six engine speeds, from 950 to 2200 rpm, and 25% engine load. The same procedure was followed for conventional diesel combustion. The study was performed in a single-cylinder engine derived from a stock medium-duty multi-cylinder diesel engine of 15.3:1 compression ratio. The combustion strategy proposed during the tests campaign was limited to accomplish both mechanical and emissions constraints. The results confirms that reactivity controlled compression ignition promotes ultra-low levels of nitrogen oxides and smoke emissions in the points tested.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

The G-equation model was implemented in the commercial code ANSYS CFX and validated against experimental data in order to successfully simulate turbulent premixed combustion in internal combustion engines. The model is based on the level-set approach. Two transport equations are solved respectively for the G-scalar mean value, representing the local distance function from the time-averaged mean flame front, and its variance, correlated to the turbulent flame brush thickness. The model closure for tracking the flame front is based on an algebraic expression for the turbulent burning velocity. The composition of the reacted mixture is evaluated by coupling the code with flamelet libraries generated with the ANSYS CFX-RIF package by means of a reaction progress variable computed as a function of the G-related quantities.

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.

Dual-mode dual-fuel combustion is a promising combustion concept to achieve the required emissions and CO2 reductions imposed by the next standards. Nonetheless, the fuel formulation requirements are stricter than for the single-fuel combustion concepts as the combustion concept relies on the reactivity of two different fuels. This work investigates the effect of the low reactivity fuel sensitivity (S=RON-MON) and the octane number at different operating conditions representative of the different combustion regimes found during the dual-mode dual-fuel operation. For this purpose, experimental tests were performed using a PRF 95 with three different sensitivities (S0, S5 and S10) at operating conditions of 25% load/950 rpm, 50%/1800 rpm and 100%/2200 rpm. Moreover, air sweeps varying ±10% around a reference air mass were performed at 25%/1800 rpm and 50%/1800 rpm. Conventional diesel fuel was used as high reactivity fuel in all the 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.

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.

In internal combustion engines operating in Controlled Auto Ignition (CAI) mode, combustion phasing and heat-release rate is controlled by stratification of fuel, fresh air, and hot internally recirculated exhaust gases. Based on the Representative Interactive Flamelet (RIF) model, a two-dimensional flamelet approach is developed. As independent parameters, firstly the fuel mixture fraction and secondly the mixture fraction of internally recirculated exhaust gases are considered. The flamelet equations are derived from the transport equations for species mass fraction and total enthalpy, employing an asymptotic analysis. A subsequent coordinate transformation leads to the phase space formulation of the two-dimensional flamelet equations. By the use of detailed chemical reaction mechanisms, the effects of dilution, temperature, and chemical species composition due to the internally recirculated exhaust gases are represented.

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.