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Two-stage fuel direct injection (DI) has the potential to expand the operating region and control the auto-ignition timing in a Diesel fuelled homogeneous charge compression ignition (HCCI) engine. In this work, to investigate the dual-injection HCCI combustion, a stochastic reactor model, based on a probability density function (PDF) approach, is utilized. A new wall-impingement sub-model is incorporated into the stochastic spray model for direct injection. The model is then validated against measurements for combustion parameters and emissions carried out on a four stroke HCCI engine. The initial results of our numerical simulation reveal that the two-stage injection is capable of triggering the charge ignition on account of locally rich fuel parcels under certain operating conditions, and consequently extending the HCCI operating range.

A detailed chemical model was implemented in the KIVA-3V two dimensional CFD code to investigate the effects of the spray cone angle and injection timing on the PCCI combustion process and emissions in an optical research diesel engine. A detailed chemical model for Primary Reference Fuel (PRF) consisting of 157 species and 1552 reactions was used to simulate diesel fuel chemistry. The model validation shows good agreement between the predicted and measured pressure and emissions data in the selected cases with various spray angles and injection timings. If the injection is retarded to -50° ATDC, the spray impingement at the edge of the piston corner with 100° injection angle was shown to enhance the mixing of air and fuel. The minimum fuel loss and more widely distributed fuel vapor contribute to improving combustion efficiency and lowering uHC and CO emissions in the engine idle condition.

This research describes the potential to adopt detailed chemical kinetics for practical and potential future fuels using tri-component surrogate mixtures capable of simulating fuel octane “sensitivity” . Since the combustion characteristics of modern fuels are routinely measured using the RON and MON of the fuel, a methodology to generate detailed chemical kinetic mechanisms for these fuels based on these data is presented. Firstly, a novel correlation between various tri-component blends (comprised of i-octane, n-heptane and toluene) and fuel RON and MON was obtained by carrying out standard octane tests. Secondly, a chemical kinetic mechanism for tri-component fuels was validated using a Stochastic Reactor Model (SRM) suite, an in-cylinder engine combustion simulator, and a series of engine experiments conducted in HCCI operating mode.

Calculations using homogeneous and stochastic reactor models were performed in order to find an explanation to observed properties of NOx HCCI engines. It was found that for moderate NOx levels, N2O reactions play an important role in the NOx formation. Further, the high proportions of NO2 found in from some HCCI engines is due to high temperature inhomogeneities, poor mixing and slow overall combustion. N2O is often emitted from HCCI combustion. The levels of NOx in the exhausts are highly sensitive to temperature; however N2O has a weak negative dependence on temperature. While fuel rich operation naturally leads to high temperatures and thus high NOx levels; once the temperature effects are decoupled the fuel rich conditions themselves has a favorable effect on low-NOx engine operation.

Analyzing the combustion characteristics, engine performance, and emissions pathways of the internal combustion (IC) engine requires management of complex and an increasing quantity of data. With this in mind, effective management to deliver increased knowledge from these data over shorter timescales is a priority for development engineers. This paper describes how this can be achieved by combining conventional engine research methods with the latest developments in process informatics and statistical analysis. Process informatics enables engineers to combine data, instrumental and application models to carry out automated model development including optimization and validation against large data repositories of experimental data.

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.

We present a computational tool to develop an exhaust gas recirculation (EGR) - air-fuel ratio (AFR) operating range for homogeneous charge compression ignition (HCCI) engines. A single cylinder Ricardo E-6 engine running in HCCI mode, with external EGR is simulated using an improved probability density function (PDF) based engine cycle model. For a base case, the in-cylinder temperature and unburned hydrocarbon emissions predicted by the model show a satisfactory agreement with measurements [Oakley et al., SAE Paper 2001-01-3606]. Furthermore, the model is applied to develop the operating range for various combustion parameters, emissions and engine parameters with respect to the air-fuel ratio and the amount of EGR used. The model predictions agree reasonably well with the experimental results for various parameters over the entire EGR-AFR operating range thus proving the robustness of the PDF based model.