Increasing the efficiency of the spark-ignition engine can help to reduce the environmental impact of the transportation sector. Engine knock obstructs the increased efficiency that could be gained by increasing the compression ratio in a spark-ignition (SI) engine. A fuel’s propensity to knock is measured by the research octane number (RON) and the motor octane number (MON) in a co-operative fuel research (CFR) engine. A fuel’s octane sensitivity (OS) is the difference between the RON and MON. Modern downsized and turbocharged engines operate at what is considered to be beyond-RON conditions. Studies have shown that having a fuel with higher OS improves knock resistance at beyond-RON conditions. This study aims to gain a better understanding of the role of intermediate-temperature heat release (ITHR) in defining OS and its subsequent impact on SI operation through the experimental framework. The ITHR of toluene primary reference fuels (TPRFs) fuels with matching RON and varying OS was studied at RON-like and MON-like homogeneous charge compression ignition (HCCI) conditions for two different matching criteria. The first criterion was to control the combustion phasing by matching half of the heat release (CA50) to 3 crank angle degrees after top dead center. The second criterion was to match the compression ratios. Results showed that at RON-like HCCI conditions, TPRF fuels display decreasing ITHR with increasing OS. Furthermore, it was shown that TPRF fuels with low sensitivity displayed a greater increase in ITHR from MON-like conditions to RON-like conditions. Thus, the sensitivity of ITHR to changes in operating conditions was found to be a contributing factor to OS. In the beyond-RON conditions (relevant to current modern engines), there is a potential for improved engine efficiency by using fuels with high OS to allow for higher compression ratios. The experimental results of this work show that OS is negatively correlated with ITHR. Thus, high-sensitivity fuels can be designed by choosing components and additives that reduce the amount of ITHR.

Experimental measurement of fuel properties are expensive, require sophisticated instrumentation and are time consuming. Mathematical models and approaches for predicting fuel properties can help reduce time and costs. A new approach for characterizing petroleum fuels called the functional group approach was developed by disassembling the innumerable fuel molecules into a finite number of molecular fragments or ‘functional groups’. This thesis proposes and tests the following hypothesis, Can a fuels functional groups be used to predict its combustion properties? Analytical techniques like NMR spectroscopy that are ideally suited to identify and quantify the various functional groups present in the fuels was used. Branching index (BI), a new parameter that quantifies the degree and quality of branching in a molecule was defined. The proposed hypothesis was tested on three classes of fuels namely gasolines, diesel and heavy fuel oil. Five key functional groups namely paraffinic CH3, paraffinic CH2, paraffinic CH, naphthenic CH-CH2 and aromatic C-CH groups along with BI were used as matching targets to formulate simple surrogates of one or two molecules that reproduce the combustion characteristics. Using this approach, termed as the minimalist functional group (MFG) approach surrogates were formulated for a number of standard gasoline, diesel and jet fuels. The surrogates were experimentally validated using measurements from Ignition quality tester (IQT), Rapid compression machine (RCM) and smoke point (SP) apparatus. The functional group approach was also employed to predict research octane number (RON) and motor octane number (MON) of fuels blended with ethanol using artificial neural networks (ANN). A multiple linear regression (MLR) based model for predicting derived cetane number (DCN) of hydrocarbon fuels was also developed. The functional group approach was also extended to study heavy fuel oil (HFO), a viscous residual fuel that contains heteroatoms like S, N and O. It is used in ships as marine fuel and also in boilers for electricity generation. 1H NMR and 13C NMR measurements were made to analyze the average molecular parameters (AMP) of HFO molecules. The fuel was divided into 19 different functional groups and their concentrations were calculated from the AMP values. A surrogate molecule that represents the average structure of HFO was then formulated and its properties were predicted using QSPR approaches.

Yes / Steady state and dynamic modelling and simulation of catalytic reforming unit of Kaduna Refining & Petrochemical Company, NNPC (Nigeria) was carried to find out the behaviour of the reactions under both steady and unsteady state conditions. The basic model together with kinetic and thermodynamic parameters and properties were taken from the literature but is developed in gPROMS (an equation oriented modelling software) model building platform for the first time rather than in MATLAB or other modelling platform used by other researchers in the past. The simulation was performed using gPROMS and the predictions were validated against those available in the literature. The validated model was then used to monitor the behaviour of the temperature, concentrations of parafins, naphthenes and aromatics with respect to both time and height of the reactor of the industrial refinery of Nigeria. Hydrogen yield, Research octane number (RON) and temperature profiles are also reported. The components behave similarly in terms of reactions in the reactors but the time to attain quasi-steady state is different. The results are in good agreement with the industrial plant data.