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The combustion of gaseous fuels like methane in internal combustion engines is an interesting alternative to the conventional gasoline and diesel fuels. Reasons are the availability of the resource and the significant advantage in terms of CO2 emissions due to the beneficial C/H ratio. One difficulty of gaseous fuels is the preparation of the gas/air mixtures for all operation points, since the volumetric energy density of the fuel is lower compared to conventional liquid fuels. Low-pressure port-injected systems suffer from substantially reduced volumetric efficiencies. Direct injection systems avoid such losses; in order to deliver enough fuel into the cylinder, high pressures are however needed for the gas injection which forces the fuel to enter the cylinder at supersonic speed followed by a Mach disk. The detailed modeling of these physical effects is very challenging, since the fluid velocities and pressure and velocity gradients at the Mach disc are very high.

This study investigates n-dodecane split injections of “Spray A” from the Engine Combustion Network (ECN) using two different turbulence treatments (RANS and LES) in conjunction with a Conditional Moment Closure combustion model (CMC). The two modeling approaches are first assessed in terms of vapor spray penetration evolutions of non-reacting split injections showing a clearly superior performance of the LES compared to RANS: while the former successfully reproduces the experimental results for both first and second injection events, the slipstream effect in the wake of the first injection jet is not accurately captured by RANS leading to an over-predicted spray tip penetration of the second pulse. In a second step, two reactive operating conditions with the same ambient density were investigated, namely one at a diesel-like condition (900K, 60bar) and one at a lower temperature (750K, 50bar).

Three-dimensional reactive computational fluid dynamics (CFD) plays a crucial role in IC engine development tasks complementing experimental efforts by providing improved understanding of the combustion process. A widely adopted combustion model in the engine community for (partially) premixed combustion is the G-Equation where the flame front is represented by an iso-level of an arbitrary scalar G. A convective-reactive equation for this iso-surface is solved, for which the turbulent flame speed ST must be provided. In this study, the commonly used and well-established Damköhler approach is compared to a novel correlation, derived from an algebraic closure for the scalar dissipation of reaction progress as proposed by Kolla et al. [1].

An existing three-stage ignition delay model which has seen successful application to Primary Reference Fuels (PRFs) has been extended to six surrogate fuels which constitute potential candidates for future Homogeneous Charge Compression Ignition (HCCI) engines. The fuels include petroleum-derived and oxygenated components and can be divided into low, intermediate and high cetane number groups. A new methodology to obtain the model parameters is presented which relies jointly on simulation and experimental data: in a first step, constant volume adiabatic reactor simulations using chemical kinetic mechanisms are performed to generate ignition delays for a very wide range of conditions, namely variations in equivalence ratio, Exhaust Gas Recirculation (EGR), pressure and temperature.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Modern Diesel engines have become ever more complex systems with many degrees of freedom. Simultaneously, with increasing computational power, simulations of engines have become more popular, and can be used to find the optimum set up of engine operation parameters which result in the desired point in the emission-efficiency trade off. With increasing number of engine operation parameter combinations, the number of calculations increase exponentially. Therefore, adequate models for combustion and emissions with limited calculation costs are required. For obvious reasons, the accuracy of the ignition timing is a key point for the following combustion and emission model quality. Furthermore, the combination of mixing and chemical processes during the ignition delay is very challenging to model in a fast way for a wide range of operation conditions.

The NO reduction in an ammonia SCR converter has been simulated by a 1D+1D model for a single representative channel to parametrically study the characteristics of the system under typical operating conditions. An appropriate model has been selected interpreting the chemical behavior of the system and the parameters are calibrated based on a comprehensive set of experiments with an Fe-Zeolite washcoated monolith for different feed concentrations, temperatures and flow rates. Physical and chemical properties are determined as well as kinetics and rate parameters and the model has been verified by experimental data at different operating conditions. Three different mechanisms for the surface kinetics to model NO reduction have been assessed and the results have been compared in the cases of steady DeNO performance and transient response of the system. Ammonia inhibition is considered in the model since it has a major effect specifically under transient operating conditions.

Large Eddy Simulations (LES) provide instantaneous values indispensable to conduct statistical studies of relevant fluctuating quantities for diesel sprays. However, numerous realizations are generally necessary for LES to derive statistically averaged quantities necessary for validation of the numerical framework by means of measurements and for conducting sensitivity studies, leading to extremely high computational efforts. In this context, the aim of this work is to explore and validate alternatives to the simulation of 20-50 single realizations at considerably lower computational costs, by taking advantage of the axisymmetric geometry and the Quasi-Steady-State (QSS) condition of the near nozzle flow at a certain time after start-of-injection (SOI).

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

The new simulation tool consists of an iterative loop of a 3-D code in parallel to a 1-D code that is employed to simulate transient engine cycles. The 1-D code yields the basic pattern of initial and boundary conditions and the 3-D simulations at several typical engine operating points are used to crosscheck the performance as well as aid in the model calibration. A flexible regression model of the fuel burn rate and the associated ROHR has been developed in conjunction with the 3-D simulations using a combination of three added Vibe functions. The emissions at the end of the expansion stroke are also predicted. The parameters of the Vibe functions and emissions are found via nonlinear regression based on state parameters such as engine speed, relative A/F ratio, EGR/rest gas contents, injection timings, etc. Additional 3-D simulations that are made at specific engine operating points complement this compact burn rate parameter library.

The discrete droplet model is widely used to describe two-phase flows such as high-velocity dense sprays. The interaction between the liquid and the gas phase is modeled via appropriate source terms in the gas phase equations. This approach can lead to a strong dependence of the liquid-gas coupling on the spatial resolution of the gas phase. The liquid-gas coupling requires the computation of source terms using the gas phase properties, and, subsequently, these sources are then distributed onto the gas phase mesh. In this study, a Lagrange polynomial interpolation method has been developed to evaluate the source terms and also to distribute these source terms onto the gas mesh. The focus of this investigation has been on the momentum exchange between the two phases. The Lagrange polynomial interpolation and source term distribution methods are evaluated for non-evaporating sprays using KIVA3 as a modeling platform.

The addition of hydrogen-rich gas to gasoline in an Internal Combustion Engine seems to be particularly suitable to arrive at a near-zero emission Otto engine, which would be able to easily meet the most stringent regulations. In order to simulate the output of an on-board reformer that partially oxidizes gasoline, providing the hydrogen-rich gas, a bottled gas has been used. Detailed results of our measurements are here shown, such as fuel consumption, engine efficiency, exhaust emissions, analysis of the heat release rates and combustion duration, for both pure gasoline and blends with reformer gas. Additionally simulations have been performed to better understand the engine behaviour and NOx formation.

Non-evaporating diesel sprays have been simulated utilizing the ETAB and the WAVE atomization and breakup models and have been compared with experimental data. The experimental penetrations and widths were determined from back-lit spray images and the droplet sizes have been measured by means of a Malvern particle sizer. The model evaluation criteria include the spray penetration, the spray width and the local droplet size. The comparisons have been performed for variations of the injection pressure, the gas density and the fuel viscosity. The fuel nozzle exit velocities used in the simulations have been computed with a special code that considers the effect of in-nozzle cavitation. The simulations showed good overall agreement with experimental data. However, the capabilities of the models to predict the droplet size for different fuels could be improved.

A phenomenological model for heat release rate predictions taking into account the characteristic processes inside a direct injection gasoline engine is presented. Fuel evaporation and preparation as well as the specifics of premixed and mixing controlled combustion phase are regarded. Only a few model constants need to be set which have been fit empirically for the application in a one-cylinder research engine. This jet guided direct injection gasoline engine employs a modern common-rail injection system and runs predominantly in stratified mode. The model allows the prediction of the influence of numerous parameter variations, e.g. injection-ignition phasing, load, engine speed, swirl, etc. on the combustion process. Furthermore efficient simulations can be carried out without using expensive three-dimensional CFD (computational fluid dynamics) calculations.

A gradient-based optimization tool has been developed and, in conjunction with a CFD code, utilized in the search of optimal fuel injection strategies. The approach taken uses a steepest descent method with an adaptive cost function, where the line search is performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for a non-road version of the Sulzer S20 DI diesel engine which, for these simulations, is equipped with a multi-orifice, asynchronous injection system. This system permits an independent timing of the fuel pulses, and each orifice has its own diameter and injection direction.

Large Eddy Simulation (LES) of premixed turbulent combustion in a confined cylinder setup at engine relevant conditions has been carried out for three different initial turbulence intensities, mimicking different flame propagation regimes. Direct Numerical Simulation (DNS) of the setup under investigation provides the reference data to be compared against. The DNS fields have been filtered on the LES grid and are used as initial conditions for the LES at onset of combustion, guaranteeing a direct comparability of the single realizations between the modeled and reference data. Two different combustion models, the G-Equation and CMC-premixed (Conditional Moment Closure) are compared with respect to their predictive capabilities as well as their usability and computational cost. While the G-Equation is a widely adopted approach for industrial applications and usually relies on a tunable turbulent flame speed closure, the novel LES-CMC comes as a tuning parameter free model.

A recently developed auto-ignition model based on a single transport equation in combination with a reduced kinetic scheme has been validated and tested in combination with a cascade jet and droplet breakup model. The validation has been performed by comparing ignition locations and delays for various thermodynamic conditions with experimental data from a high-pressure combustion cell. Also for medium-size diesel engine applications, predictions of ignition delay are in good agreement with experimental observations. In addition, a new approach to the modeling of the early flame development in diesel engine combustion is introduced. The reaction rate in the transition phase from the premixed to the mixing-controlled combustion mode is determined by means of a sub-grid scale model, which describes the evolution of a turbulent diffusion flame. The model has been tested during the early combustion phase of a medium-size, medium-speed DI diesel engine.

This investigation is a continuation of a previous study by these authors in which a Lagrange polynomial interpolation method was developed to evaluate spray source terms and also to distribute the source terms onto the gas mesh; the method was applied to the liquid-gas momentum exchange. For this investigation, the method has been extended to the mass exchange between the liquid and gas phases due to evaporation. The Lagrange polynomial interpolation and source term distribution methods are applied to the liquid-gas mass and momentum exchange and are evaluated for evaporating sprays using KIVA3 as a modeling platform. These methods are compared with the standard “nearest neighbor” method of KIVA3, and experimental data are used to establish their validity. The evaluation criteria used include the liquid and vapor spray penetration, gas velocities and the computational stability.

A new approach within the well-known trade-off in combustion process simulations between computational efforts (and thus the capability for engine operating map calculations) on the one hand, and accuracy of predictions on the other, has been developed and applied successfully to diesel combustion, in particular to energy release and pollutant formation. Using phenomenological models in combination with bio-inspired algorithms (for parameter identification), it is now possible to predict thermal, chemical and injection related engine characteristics over an entire operating map including different types of fuel (e.g. diesel, water-in-diesel emulsions and oxygenated diesel).