Simulation Of The Diesel Engine Combustion Process Using The Stochastic Reactor Model

The present work is concerned with the simulation of combustion, emission formation and fuel effects in Diesel engines. The simulation process is built around a zero-dimensional (0D) direct injection stochastic reactor model (DI-SRM), which is based on a probability density function (PDF) approach. An emphasis is put on the modelling of mixing time to improve the representation of turbulence-chemistry interactions in the 0D DI-SRM. The mixing time model describes the intensity of mixing in the gas-phase for scalars such as enthalpy and species mass fraction. On a crank angle basis, it governs the composition of the gas mixture that is described by PDF distributions for the scalars. The derivation of the mixing time is based on an extended heat release analysis that has been fully automated using a genetic algorithm. The predictive nature of simulations is achieved through the parametrisation of the mixing time model with known engine operating parameters such as speed, load and fuel injection strategy. It is shown that crank angle dependency of the mixing time improves the modelling of local inhomogeneity in the gas-phase for species mass fraction and temperature. In combination with an exact treatment of the non-linearity of reaction kinetics, it enables an accurate prediction of the rate of heat release, in-cylinder pressure and exhaust emissions, such as nitrogen oxides, unburned hydrocarbons and soot, from differently composed fuels. The method developed is particularly tailored for computationally efficient applications that focus on the details of reaction kinetics and the locality of combustion and emission formation in Diesel engines.

Phenomenology of Diesel Combustion and Modeling Diesel is the most efficient combustion engine today and it plays an important role in transport of goods and passengers on land and on high seas. The emissions must be controlled as stipulated by the society without sacrificing the legendary fuel economy of the diesel engines. These important drivers caused innovations in diesel engineering like re-entrant combustion chambers in the piston, lower swirl support and high pressure injection, in turn reducing the ignition delay and hence the nitric oxides. The limits on emissions are being continually reduced. The- fore, the required accuracy of the models to predict the emissions and efficiency of the engines is high. The phenomenological combustion models based on physical and chemical description of the processes in the engine are practical to describe diesel engine combustion and to carry out parametric studies. This is because the injection process, which can be relatively well predicted, has the dominant effect on mixture formation and subsequent course of combustion. The need for improving these models by incorporating new developments in engine designs is explained in Chapter 2. With “model based control programs” used in the Electronic Control Units of the engines, phenomenological models are assuming more importance now because the detailed CFD based models are too slow to be handled by the Electronic Control Units. Experimental work is necessary to develop the basic understanding of the pr- esses.

In order to satisfy the growing demand for the reduction of fuel consumption and pollutant emissions, various technologies have been employed in diesel engines. Consequently, to determine the optimal combustion control strategy, many parameters such as injection pressure, nozzle diameter, injection timing, injection quantity, and exhaust gas recirculation (EGR) rate should be selected properly corresponding to the engine operating conditions. It is difficult to obtain the appropriate strategies without understanding the change in combustion process when varying these parameters. To realize parametric studies on combustion control strategy of modern diesel engines, a phenomenological combustion model based on stochastic method was developed. In this model, the modeling of the spray tip and tail penetration after the end of injection, and interaction between the sprays of sequent injection stages were focused on to modify the stochastic combustion model for combustion simulation with multiple injection. The effects of swirl, wall impingement, and adjacent spray interaction are formulated simply to make the combustion model more accurate and computationally efficient. The simulation results were compared with experimental data from a single-cylinder test engine for pilot/main two-stage injection. The results reveal that the model has capability to accurately predict the combustion characteristics and emissions of diesel engine with pilot/main two-stage injection.

A new coalescence/dispersion model for stochastic turbulent mixings is proposed. The new model provides a more realistic description of the initial phase of mixing which strongly affects burn rate predictions.

In order to fulfil future emissions legislations, new combustion systems are to be investigated. One way of improving exhaust emissions is the application of multiple injection strategies and conventional or partially premixed combustion conditions to a Diesel engine. The application of numerical techniques as CFD supports and improves the quality of engine developments. Unfortunately, current spray and combustion models are not accurate enough to simulate multiple injection systems, being in this way a topic of research. The goal of this study was the development of a novel simulation method for the investigation of Diesel engines operated with multiple injection strategies and different combustion modes. The first part of this work focused in improving the spray modelling. The inform ation of 3D CFD simulations of the injector nozzle was introduced in the spray simulation as boundary conditions developing coupling subroutines for this issue. The atomisation modelling was also improved using validated presumed droplet size distributions. Moreover, to avoid the simulation of the injector nozzle for every investigated operating point, a novel interpolating tool was developed in order to create spray boundary conditions based on few 3D CFD simulations of the nozzle under certain initial and boundary conditions. The second part of this thesis dealt with the combustion modelling of Diesel engines. For this issue, a laminar flamelet approach called Representative Interactive Flamelet model (RIF) was selected and implemented. Afterwards, an extended combustion model based on RIF was developed in order to take into account multiple injection strategies. Finally, this new model was validated with a wide range of operating points: applying multiple injection strategies under conventional and partially premixed combustion conditions.

Three models were implemented, which are important for pollutant prediction in Diesel engines: ignition, chemistry and radiation. Ignition was tracked by means of a representative species (here CO), whose concentration remains small during the ignition period and which shows an increase at ignition. Its reaction rate was obtained from a detailed mechanism and combined with a presumed probability density function (pdf). The intrinsic low-dimensional manifold (ILDM) method was used as a chemistry model. It is an automatic reduction of a detailed chemical mechanism based on a local timescale analysis. It was also combined with a presumed pdf method. NOx and soot were predicted using a Zeldovich model and a phenomenological two-equation model, respectively. The radiative properties of the gases were described with a weighted sum of grey gases model (WSGGM). The radiative properties of soot were described by a grey model. The RTE was solved using the discrete ordinates method (DOM), which involves solving the RTE in discrete directions. The ignition and chemistry models were implemented in a standard CFD code, KIVA and used to simulate the combustion in a Caterpillar engine, for which experimental data were available. Ignition was observed to occur at the edge of the spray, in the lean region. Simulated pressure curves and mean NO concentrations were compared to experimental data and showed good agreement. Soot was strongly under-predicted due to the inability to identify the ILDM in the rich region. The DOM radiation model was tested in a furnace, and the wall fluxes were compared to analytical data. It was not used in the engine due to low quantities of soot predicted. Instead, an optically thin model was used in the engine and the radiative losses were seen to be negligible.

Qirui Yang develops a model chain for the simulation of combustion and emissions of diesel engine with fully variable valve train (VVT) based on extensive 3D-CFD simulations, and experimental measurements on the engine test bench. The focus of the work is the development of a quasi-dimensional (QDM) flow model, which sets up a series of sub-models to describe phenomenologically the swirl, squish and axial charge motions as well as the shear-related turbulence production and dissipation. The QDM flow model is coupled with a QDM combustion model and a nitrogen oxides (NOx) / soot emission model. With the established model chain, VVT operating strategies of diesel engine can be developed and optimized as part of the simulation for specific engine performance parameters and the lowest NOx and soot emissions.