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Motorcycle usage continues to expand globally. Motorcycles use various fuels in different countries and regions, and it is required that they comply with emissions and fuel consumption regulations as specified in UN-GTR No.2 (WMTC). In general, a motorcycle engine has a large bore diameter and a high compression ratio due to demands of high performance. Poor fuel quality may cause damage to the engine, mainly by knocking. Knock control systems utilizing high-frequency vibration detection strategies like knock sensors, which are equipped on several sport-touring motorcycles, are not used widely for reasons of complex construction and high cost. This research aims to develop a new concept of combustion control for common motorcycle as an alternative.

Two diagnostics were developed that are particularly suitable for use with natural gas-fuelled reciprocating engines that are used for power generation applications. The first diagnostic relates flame chemiluminescence to thermodynamic metrics relevant to engine combustion - Heat Release Rate (HRR) and in-cylinder bulk gas temperature. Studies were conducted in a single-cylinder natural gas-fired reciprocating engine that could simulate turbocharged conditions with Exhaust Gas Recirculation. Crank-angle-resolved spectra (266 to 795 nm) of flame luminosity were measured for various operational conditions by varying the ignition timing for MBT conditions and by holding the speed at 1800 rpm and Brake Mean Effective Pressure (BMEP) at 12 bar. The effect of dilution on CO₂* chemiluminescence intensities was studied, by varying the global equivalence ratio (0.6 - 1.0) and by varying the Exhaust Gas Recirculation rate.

Knock integrals and corresponding ignition delay (τ) correlations are often used in model-based control algorithms in order to predict ignition timing for kinetically modulated combustion regimes such as HCCI and PCCI. They can also be used to estimate knock-inception during conventional SI operation. The purpose of this study is to investigate the performance of various τ correlations proposed in the literature, including those developed based on fundamental data from shock tubes and rapid compression machines, those based on predictions from isochoric simulations using detailed chemical kinetic mechanisms, and those deduced from data of operating engines. A 0D engine simulation framework is used to compare the correlation performance where evaluations are based on the temperatures required at intake valve closure (TIVC) in order to achieve a fixed CA50 point over a range of conditions.

In internal combustion engine computational fluid dynamics (CFD) simulations, uncertainties arise from various sources, such as estimates of model parameters, experimental boundary conditions, estimates of chemical kinetic rates, etc. These uncertainties propagate through the model and may result in discrepancies compared to experimental measurements. The relative importance of the various sources of uncertainty can be quantified by performing a sensitivity analysis. In this work, global sensitivity analysis (GSA) was applied to engine CFD simulations of a low-temperature combustion concept called gasoline compression ignition, to understand the influence of experimental measurement uncertainties from various sources on specific targets of interest-spray penetration, ignition timing, combustion phasing, combustion duration, and emissions. The sensitivity of these targets was evaluated with respect to imposed uncertainties in experimental boundary conditions and fuel properties.

Fuels in the gasoline auto-ignition range (Research Octane Number (RON) > 60) have been demonstrated to be effective alternatives to diesel fuel in compression ignition engines. Such fuels allow more time for mixing with oxygen before combustion starts, owing to longer ignition delay. Moreover, by controlling fuel injection timing, it can be ensured that the in-cylinder mixture is “premixed enough” before combustion occurs to prevent soot formation while remaining “sufficiently inhomogeneous” in order to avoid excessive heat release rates. Gasoline compression ignition (GCI) has the potential to offer diesel-like efficiency at a lower cost and can be achieved with fuels such as low-octane straight run gasoline which require significantly less processing in the refinery compared to today’s fuels.

In automotive industry it has been a challenge to retain diesel-like thermal efficiency while maintaining low emissions. Numerous studies have shown significant progress in achieving low emissions through the introduction of common-rail injection systems, multiple injections and exhaust gas recirculation and by using a high octane number fuel, like gasoline, to achieve adequate premixing. On the other hand, low temperature combustion strategies, like HCCI and PCCI, have also shown promising results in terms of reducing both NOx and soot emissions simultaneously. With the increasing capacity of computers, multi-dimensional CFD engine modeling enables a reasonably good prediction of combustion characteristics and pollutant emissions, which is the motivation behind the present research. The current research effort presents an optimization study of light-duty compression ignition engine performance, while meeting the emission regulation targets.

Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. Hence, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region.