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A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing.

Controlled Auto Ignition (CAI), also known as Homogeneous Charge Compression Ignition (HCCI), is one of the most promising combustion technologies to reduce the fuel consumption and NOx emissions. Currently, CAI combustion is constrained at part load operation conditions because of misfire at low load and knocking combustion at high load, and the lack of effective means to control the combustion process. Extending its operating range including high load boundary towards full load and low load boundary towards idle in order to allow the CAI engine to meet the demand of whole vehicle driving cycles, has become one of the key issues facing the industrialisation of CAI/HCCI technology. Furthermore, this combustion mode should be compatible with different fuels, and can switch back to conventional spark ignition operation when necessary. In this paper, the CAI operation is demonstrated on a 2-stroke gasoline direct injection (GDI) engine equipped with a poppet valve train.

Controlled Auto-Ignition (CAI) also known as Homogeneous Charge Compression Ignition (HCCI) is increasingly seen as a very effective way of lowering both fuel consumption and emissions. Hence, it is regarded as one of the best ways to meet stringent future emissions legislation. It has however, still many problems to overcome, such as limited operating range. This combustion concept was achieved in a production type, 4-cylinder gasoline engine, in two separated tests: naturally aspirated and turbocharged. Very few modifications to the original engine were needed. These consisted basically of a new set of camshafts for the naturally aspirated test and new camshafts plus turbocharger for the test with forced induction. After previous experiments with naturally aspirated CAI operation, it was decided to investigate the capability of turbocharging for extended CAI load and speed range.

Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

The use of complex reaction schemes is accompanied by high computational cost in 3D CFD simulations but is particularly important to predict pollutant emissions in internal combustion engine simulations. One solution to tackle this problem is to solve the chemistry prior the CFD run and store the chemistry information in look-up tables. The approach presented combines pre-tabulated progress variable-based source terms for auto-ignition as well as soot and NOx source terms for emission predictions. The method is coupled to the 3D CFD code CONVERGE v2.4 via user-coding and tested over various speed and load passenger-car Diesel engine conditions. This work includes the comparison between the combustion progress variable (CPV) model and the online chemistry solver in CONVERGE 2.4. Both models are compared by means of combustion and emission parameters. A detailed n-decane/α-methyl-naphthalene mechanism, comprising 189 species, is used for both online and tabulated chemistry simulations.

This paper reports on a fast predictive combustion tool employing detailed chemistry. The model is a stochastic reactor based, discretised probability density function model, without spatial resolution. Employing detailed chemistry has the potential of predicting emissions, but generally results in very high CPU costs. Here it is shown that CPU times of a couple of minutes per cycle can be reached when applying detailed chemistry, and CPU times below 10 seconds per cycle can be reached when using reduced chemistry while still catching in-cylinder in-homogeneities. This makes the tool usable for efficient engine performance mapping and optimisation. To meet CPU time requirements, automatically load balancing parallelisation was included in the model. This allowed for an almost linear CPU speed-up with number of cores available.

The measurement of the instantaneous flame temperature and soot concentration in the combustion chamber of a running diesel engine can provide useful information relating to the formation of two important exhaust pollutants, NOx and particulates. The two-colour method is based on optical pyrometry and it can provide estimates of the instantaneous flame temperature and soot concentration. The theoretical basis of the method is outlined in a companion paper. This paper deals with the practical problems involved in the construction of a working system, including suitable calibration techniques. The accuracy of the measurements of flame temperature and soot concentration is also discussed using results from a various sources.

The two-colour method is based on optical pyrometry and can readily be implemented at a modest cost for the measurement of the instantaneous flame temperature and soot concentration in the cylinders of diesel engines. With appropriate modification, this method can be applied to other continuous and intermittent combustion systems, such as those for gas turbine and boiler burners. This paper outlines the theoretical basis of the method, with particular attention being paid to the assumptions relating to the evaluation of the flame temperature and soot concentration. A companion paper deals with the practical problems involved in constructing a working system, including suitable calibration techniques, and assessment of the method accuracy.

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.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

This work was concerned with evaluation of the performance and emissions of potential future biofuels during advanced spark ignition engine operation. The fuels prepared included three variants of gasoline, three gasoline-ethanol blends and a gasoline-butanol fuel altogether covering a range of oxygen mass concentrations and octane numbers to identify key influencing parameters. The combustion of the fuels was evaluated in a turbocharged multi-cylinder direct fuel injection research engine equipped with a standard three-way catalyst and an external EGR circuit that allowed use of either cooled or non-cooled EGR. The engine operating effects studied at both part and boosted high load conditions included fuel injection timing and pressure, excess air tolerance, EGR tolerance and spark retard limits. A number of blends were also mapped at suitable sites across the European drive cycle under downsized engine conditions.

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.

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.

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.

Direct injection gasoline engines have the potential for improved fuel economy through principally the engine down-sizing, stratified charge combustion, and Controlled Auto Ignition (CAI). However, due to the limited time available for complete fuel evaporation and the mixing of fuel and air mixture, locally fuel rich mixture or even liquid fuel can be present during the combustion process of a direct injection gasoline engine. This can result in significant increase in UHC, CO and Particulate Matter (PM) emissions from direct injection gasoline engines which are of major concerns because of the environmental and health implications. In order to investigate and develop a more efficient DI gasoline engine, a camless single cylinder DI gasoline engine has been developed. Fully flexible electro-hydraulically controlled valve train was used to achieve spark ignition (SI) and Controlled Autoignition (CAI) combustion in both 4-stroke and 2-stroke cycles.

Tumble and swirl motions in the cylinder of a four-valve SI engine with production type cylinder head were investigated using a cross-correlation digital Particle Image Velocimetry (PIV). Tumble motion was measured on the vertical symmetric plane of the combustion chamber. Swirl motion was measured on a plane parallel to the piston crown with one of intake ports blocked. Large-scale flow behaviours and their cyclic variations were analysed from the measured two-dimensional velocity data. Results show that swirl motion is generated at the end of the intake stroke and persists to the end of the compression stroke. Tumble vortex is produced in the early stage of the compression stroke and distorted in the late stage of the stroke. The cyclic variation of swirl motion is noticeable. The cyclic variation in tumble dominated flow field is much greater.

The development of future gasoline engines is dominated by the study of new technologies aimed at reducing the engine negative environmental impact and increase its thermal efficiency. One common trend is to develop smaller engines able to operate in stoichiometric conditions across the whole engine map for better efficiency, lower fuel consumption, and optimal conversion rate of the three-way catalyst (TWC). Water injection is one promising technique, as it significantly reduces the engine knock tendency and avoids fuel enrichment for exhaust temperature mitigation at high power operation. With the focus on reducing the carbon footprint of the automotive sector, another vital topic of research is the investigation of new alternative CO2-neutral fuels or so-called eFuels. Several studies have already shown how these new synthetic fuels can be produced by exploiting renewable energy sources and can significantly reduce engine emissions.

In this study, the effect of the intake plenum design on the scavenging process in a newly proposed 2-stroke Boosted Uniflow Scavenged Direct Injection Gasoline (BUSDIG) engine was studied in detail by three dimensional (3D) computational fluid dynamics (CFD) simulations. In the BUSDIG engine, the intake scavenge ports are integrated into the cylinder liner and their opening and closure are controlled by the movement of piston top while exhaust valves are placed in the cylinder head. In order to accommodate the optimized scavenge ports in the real engine application, the intake plenum with an inlet pipe and a scavenge chamber was designed and connected to the 12 evenly distributed scavenge ports in a single cylinder BUSDIG engine.

Morphology plays an important role in determining behaviour and impact of soot nanoparticles, including effect on human health, atmospheric optical properties, contribution to engine wear, and role in marine ecology. However, its nanoscopic size has limited the ability to directly measure useful morphological parameters such as surface area and effective volume. Recently, 3D morphology characterization of soot nanoparticles via electron tomography has been the subject of several introductory studies. So-called ‘3D-TEM’ has been posited as an improvement over traditional 2D-TEM characterization due to the elimination of the error-inducing information gap that exists between 3-dimensional soot structures and 2-dimensional TEM projections. Little follow-up work has been performed due to difficulties with developing methodologies into robust high-throughput techniques.

A method for automatic reduction of detailed reaction mechanisms using simultaneous sensitivity, reaction flow and lifetime analysis has been developed and applied to a two-zone model of an SI engine fuelled with Primary Reference Fuel (PRF). Species which are less relevant for the occurrence of autoignition in the end gas are declared redundant. They are identified and eliminated for different pre-set minimum levels of reaction flow and sensitivity. The resulting skeletal mechanism is valid in the ranges of initial and boundary values for which the analyses have been performed. A measure of species lifetime is calculated from the chemical source terms, and the species with the lifetime shorter than and mass-fraction less than specified limits are selected for removal.