Chemical kinetics modelling of combustion processes in SI engines

• Main Author: Khan, Ahmed Faraz
• Other Authors: Burluka, A.
• Published: University of Leeds 2014
• Subjects: 621
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.634282

The need for improving the efficiency and reducing emissions is a constant challenge in combustion engine design. For spark ignition engines, these challenges have been targeted in the past decade or so, through ‘engine downsizing’ which refers to a reduction in engine displacement accompanied by turbocharging. Besides the benefits of this, it is expected to aggravate the already serious issue of engine knock owing to increased cylinder pressure. Engine knock which is a consequence of an abnormal mode of combustion in SI engines, is a performance limiting phenomenon and potentially damaging to the engine parts. It is therefore of great interest to develop capability to predict autoignition which leads to engine knock. Traditionally, rather rudimentary skeletal chemical kinetics models have been used for autoignition modelling, however, they either produce incorrect predictions or are only limited to certain fuels. In this work, realistic chemical kinetics of gasoline surrogate oxidation has been employed to address these issues. A holistic modelling approach has been employed to predict combustion, cyclic variability, end gas autoignition and knock propensity of a turbocharged SI engine. This was achieved by first developing a Fortran code for chemical kinetics calculations which was then coupled with a quasi-dimensional thermodynamic combustion modelling code called LUSIE and the commercial package, GT-Power. The resulting code allowed fast and appreciably accurate predictions of the effects of operating condition on autoignition. Modelling was validated through comparisons with engine experimental data at all stages. Constant volume chemical kinetics modelling of the autoignition of various gasoline surrogate components, i.e. iso-octane, n-heptane, toluene and ethanol, by using three reduced mechanisms revealed how the conversion rate of relatively less reactive blend components, toluene and ethanol, is accelerated as they scavenge active radical formed during the oxidation of n-heptane and iso-octane. Autoignition modelling in engines offered an insight into the fuel-engine interactions and that how the composition of a gasoline surrogate should be selected. The simulations also demonstrated the reduced relevance of research and motor octane numbers to the determination of gasoline surrogates and that it is crucial for a gasoline surrogate to reflect the composition of the target gasoline and that optimising its physicochemical properties and octane numbers to match those of the gasoline does not guarantee that the surrogate will mimic the autoignition behaviour of gasoline. During combustion modelling, possible deficiencies in in-cylinder turbulence predictions and possible inaccuracies in turbulent entrainment velocity model required an optimisation of the turbulent length scale in the eddy burn-up model to achieve the correct combustion rate. After the prediction of a correct mean cycle at a certain engine speed, effects of variation in intake air temperature and spark timing were studied without the need for any model adjustment. Autoignition predictions at various conditions of a downsized, turbocharged engine agreed remarkably well with experimental values. When coupled with a simple cyclic variability model, the autoignition predictions for the full spectrum of cylinder pressures allowed determination of a percentage of the severely autoigniting cycles at any given spark timing or intake temperature. Based on that, a knock-limited spark advance was predicted within an accuracy of 2° of crank angle.