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A method of predicting brake specific fuel consumption characteristics from limited specifications of engine design has been investigated. For spark ignition engines operating on homogeneous mixtures, indicated specific fuel consumption based on gross indicated power is related to compression ratio and spark timing relative to optimum values. The influence of burn rate is approximately accounted for by the differences in spark timings required to correctly phase combustion. Data from engines of contemporary design shows that indicated specific fuel consumption can be defined as a generic function of relative spark timing, mixture air/fuel ratio and exhaust gas recirculation rate. The additional information required to generate brake specific performance maps is cylinder volumetric efficiency, rubbing friction, auxiliary loads, and exhaust back pressure characteristics.

A computational model has been developed to support investigations of temperature, heat flow and friction characteristics, particularly in connection with warm-up behaviour. A lumped capacity model of the engine block and head, empirically derived correlations for local heat transfer and friction losses, and oil and coolant circuit descriptions form the core of the model. Validation of the model and illustrative results are reported.

The oil distribution system of an automotive light duty engine typically has an oil pump mechanically driven through the front-endancillaries-drive or directly off the crankshaft. Delivery pressure is regulated by a relief valve to provide an oil gallery pressure of typically 3 to 4 bar absolute at fully-warm engine running conditions. Electrification of the oil pump drive is one way to decouple pump delivery from engine speed, but this does not alter the flow distribution between parts of the engine requiring lubrication. Here, the behaviour and benefits of a system with an electrically driven, fixed displacement pump and a distributor providing control over flow to crankshaft main bearings and big end bearings is examined. The aim has been to demonstrate that by controlling flow to these bearings, without changing flow to other parts of the engine, significant reductions in engine friction can be achieved.

The largest contribution to engine rubbing friction is made by the piston and piston rings running in the cylinder liner. The magnitude and characteristics of the friction behaviour and the influence on these of factors such as surface roughness, piston design and lubricant properties are of keen interest. Investigating presents experimental challenges, including potential problems of uncontrolled build-to-build variability when component changes are made. These are addressed in the design of a new motored piston and floating liner rig. The design constrains transverse movement of a single liner using cantilevered mounts at the top and bottom. The mounts and two high stiffness strain gauged load cells constrain vertical movement. The outputs of the load cells are processed to extract the force contribution associated with friction. The liner, piston and crankshaft parts were taken from a EuroV-compliant, HPCR diesel engine with a swept capacity of 550cc per cylinder.

The determination of size distribution of soot particles and agglomerates in oil samples using a Nanosight LM14 to perform Nanoparticle Tracking Analysis (NTA) is described. This is the first application of the technique to sizing soot-in-oil agglomerates and offers the advantages of relatively high rates of sample analysis and low cost compared to Transmission Electron Microscopy (TEM). Lubricating oil samples were drawn from the sump of automotive diesel engines run under a mix of light duty operating conditions. The oil samples were diluted with heptane before analysing. Results from NTA analysis were compared with the outputs of a more conventional analysis based on Dynamic Light Scattering (DLS). This work shows that soot-in-oil exists as agglomerates with average size of 115 nm. This is also in good agreement with TEM analysis carried out in a previous work. NTA can measure soot particles in polydisperse oil solutions and report the size distribution of soot-in-oil aggregates.

In order to identify predictive models for a diesel engine combustion process, combustion cylinder pressure together with other fuel path variables such as rail pressure, injector current and sleeve pressure of 1000 continuous cycles were sampled and collected at high resolution. Using these engine steady state test data, three types of modeling approach have been studied. The first is the Auto-Regressive-Moving-Average (ARMA) model which had limited prediction ability for both peak combustion pressure (Pmax) and Indicated Mean Effective Pressure (IMEP). By applying correlation analysis, proper inputs were found for a linear predictive model of Pmax and IMEP respectively. The prediction performance of this linear model is excellent with a 30% fit number for both Pmax and IMEP. Further nonlinear modeling work shows that even a nonlinear Neural Network (NN) model does not have improved prediction performance compared to the linear predictive model.

The integration of selective catalytic reduction catalysts (SCR) into diesel particulate filters (DPF) as a way to treat nitrogen oxides (NOx) and particulate matter (PM) emission is an emerging technology in diesel exhaust aftertreatment. This is driven by ever-tightening limits on NOx and PM emission. In an integrated SCR-in-DPF (also known as SCRF®, SCR-on-DPF, SDPF, or SCR coated filter), the SCR catalyst is impregnated within the porous walls of the DPF. The compact, low weight/volume of the integrated unit provides improvement in the diesel engine cold start emission performance. Experimental investigations have shown comparable performance with standard SCR and DPF units for NOx conversion and PM control, respectively. The modelling of the integrated unit is complicated.

Gear oscillations are one of the most common sources of Noise, Vibration and Harshness (NVH) issues manifested in automotive powertrains. These oscillations are generated mainly due to impacts of the meshing gear teeth over a broad frequency range. To mitigate NVH phenomena, automotive manufacturers traditionally couple linear tuned vibration absorbers to the driveline. Common palliatives used are clutch dampers and dual mass flywheels, which generally suppress vibrations effectively only over narrow frequency bands. Nonlinear Energy Sinks (NESs) are a class of vibration absorbers with essentially nonlinear characteristics that are designed for dissipating vibration energy over broad frequency ranges (due to the employed nonlinearity). The NES does not have a preferential natural frequency; this is rather characterized by the nonlinear stiffness.

One of the most critical challenges currently facing the diesel engine industry is how to improve fuel economy under emission regulations. Improvement in fuel economy can be achieved by precisely controlling Air/Fuel ratio and by monitoring fuel consumption in real time. Accurate and repeatable measurements of fuel rate play a critical role in successfully controlling air/fuel ratio and in monitoring fuel consumption. Volumetric and gravimetric measurements are well-known methods for measuring fuel consumption of internal combustion engines. However, these methods are not suitable for obtaining fuel flow rate data used in real-time control/measurement. In this paper, neural networks are used to solve the problem concerning discontinuous data of fuel flow rate measured by using an AVL 733 s fuel meter. The continuous parts of discontinuous fuel flow rate are used to train and validate a neural network, which can then be used to predict the discontinuous parts of the fuel flow rate.

Variable compression ratio in conjunction with a control system is an effective way to improve performance and reduce emissions in a diesel engine. There are various methods that may be employed that include geometry changes and varying valve timing to change the effective compression ratio. In this paper, a simulation study is presented that is based on a modern, multi-cylinder, fixed compression ratio diesel engine equipped with exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT). The engine is represented using the GT-Power code, and includes a predictive combustion model. The aim of the investigation is to identify the impact of variable compression ratio on fuel economy and emission reduction and whether realistic optimal conditions exist. This paper describes how a formal design of experiments procedure is used to define the simulation conditions. Cost functions are defined with different weights for fuel consumption, NOx and soot emissions.

In motorsport power transmission systems, high-speed operation can be associated with significant rotordynamic effects. Changes in the natural frequencies of lateral (bending) vibrational modes as a function of spin speed are brought about by gyroscopic action linked to flexible shafts and mounted gear components. In the investigation of high-speed systems, it is important that these effects are included in the analysis in order to accurately predict the critical speeds encountered due to the action of the gear mesh and other sources of excitation. The rotordynamic behaviour of the system can interact with crucial physical parameters of the transmission, such as the stiffnesses of the gear mesh and rolling element-to-raceway contact in the bearings. In addition, the presence of the gear mesh acts to couple the lateral and torsional vibration modes of a dual-shaft transmission through which a torque flows.

Modeling the combustion process of a diesel-biodiesel fuel spray in a 3-dimensional (3D) computational fluid dynamics (CFD) domain remains challenging and time-consuming despite the recent advancement in computing technologies. Accurate representation of the in-cylinder processes is essential for CFD studies to provide invaluable insights into these events, which are typically limited when using conventional experimental measurement techniques. This is especially true for emerging new fuels such as biodiesels since fundamental understanding of these fuels under combusting environment is still largely unknown. The reported work here is dedicated to evaluating the Adaptive Local Mesh Refinement (ALMR) approach in OpenFOAM® for improved simulation of reacting biodiesel fuel spray. An in-house model for thermo-physical and transport properties is integrated to the code, along with a chemical mechanism comprising 113 species and 399 reactions.

The in cylinder air motion, fuel air mixing, evaporation, combustion and exhaust emissions have been simulated for a four stroke direct injection gasoline engine using the KIVA II code. A strong controlled tumbling air motion was created in the cylinder, through a combination of a conventional pentroof four valve cylinder head, in conjunction with a piston having a stepped crown and offset combustion bowl. A range of injection strategies were employed to optimise combustion rate and exhaust emission (NOx and unburned hydrocarbons (fuel)), at two operating conditions - one with a stoichiometric air fuel mixture and the other with a lean mixture of 30:1 air/fuel ratio. Injection directed towards the piston bowl with a hollow cone jet, in a single pulse, has shown the best results regarding burned mass fraction and level of unburned HC. Fuel concentration, air motion, combustion characteristics and pollutants level are presented for lean and stoichiometric cases.

The process of autoignition in an internal combustion engine cylinder produces large amplitude high frequency gas pressure waves accompanied by significant increases in gas temperature and velocity, and as a consequence large convective heat fluxes to piston and cylinder surfaces. Extended exposure of these surfaces to autoignition, results in their damage through thermal fatigue, particularly in regions where small clearances between the piston and cylinder or cylinder head, lie in the path of the oscillatory gas pressure waves. The ability to predict spatial and temporal' variations in cylinder gas pressure, temperature and velocity during autoignition and hence obtain reasonable estimates of surface heat flux, makes it possible to assess levels of surface fatigue at critical zones of the piston and cylinder head, and hence improve their tolerance to autoignition.

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.

Experimental studies of fuel utilisation during the early stages of engine warm-up after cold-starts are reported. The investigation has been carried out on a 1.81, 4 cylinder spark-ignition engine with port electronic fuel injection. The relationship between fuel supplied and fuel accounted for by the analysis of exhaust gas composition shows that a significant mass of fuel supplied is temporarily stored or permanently lost. An interpretation of data is made which allows time-dependent variations of these to be separately resolved and estimates of fuel quantities made. The data covers a range of cold-start conditions down to -5°C at which, on a per cylinder basis, fuel stored peaks typically at around 0.75g and a total of 1g is returned over 100 seconds of engine running. Fuel lost past the piston typically accounts for 2g over 200 to 300 seconds of running.

Through improving the 48V hybrid vehicle archetype, governmental emission targets could be more easily met without incurring the high costs associated with increasing levels of electrification. The braking energy recovery function of hybrid vehicles is recognised as an effective solution to reduce emissions and fuel consumption in the short to medium term. The aim of this study was to evaluate methods to maximise the braking energy recovery capability of the 48V hybrid electric vehicle over pre-selected drive cycles using appropriately sized electrified components. The strategy adopted was based upon optimising the battery chemistry type via specific power capability, so that overall brake power is equal to the maximum battery charging power in a typical medium-sized passenger car under typical driving. This will maximise the regenerative braking energy whilst providing a larger torque assistance for a lower battery capacity.

Cold idle operation of a modern design light duty diesel engine and the effect of multiple pilot injections on stability were investigated. The investigation was initially carried out experimentally at 1000rpm and at −20°C. Benefits of mixture preparation were initially explored by a heat release analysis. Kiva 3v was then used to model the effect of multiple pilots on in-cylinder mixture distribution. A 60° sector of mesh was used taking advantage of rotational symmetry. The combustion system and injector arrangements mimic the HPCR diesel engine used in the experimental investigation. The CFD analysis covers evolutions from intake valve closing to start of combustion. The number of injections was varied from 1 to 4, but the total fuel injected was kept constant at 17mm3/stroke. Start of main injection timing was fixed at 7.5°BTDC.

An experimental study of the performance of a reverse tumble, DISI engine is reported. Specific fuel consumption and engine-out emissions have been investigated for both homogeneous and stratified modes of fuel injection. Trends in performance with varying AFR, EGR, spark and injection timings have been explored. It is shown that neural networks can be trained to describe these trends accurately for even the most complex case of stratified charge operation with exhaust gas recirculation.

A three-pulse fuel injection mode has been studied by implementing two-input-two-output (2I2O) control of both peak combustion pressure (Pmax) and indicated mean effective pressure (IMEP). The engine test results show that at low engine speed, the first main injection duration and the second main injection duration are able to be used to control Pmax and IMEP respectively. This control is exercised within a limited but promising area of the engine map. However, at high engine speed, Pmax and IMEP are strongly coupled together and then can not be separately controlled by the two control variables: the first and the second main injection duration. A simple zero-dimensional (0D) combustion model together with correlation analysis method was used to find out why the coupling strength of Pmax and IMEP increases with engine speed increased.