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The work presented here seeks to compare different means of providing scavenging systems for an automotive 2-stroke engine. It follows on from previous work solely investigating uniflow scavenging systems, and aims to provide context for the results discovered there as well as to assess the benefits of a new scavenging system: the reverse-uniflow sleeve-valve. For the study the general performance of the engine was taken to be suitable to power a medium-duty truck, and all of the concepts discussed here were compared in terms of indicated fuel consumption for the same cylinder swept volume using a one-dimensional engine simulation package. In order to investigate the sleeve-valve designs layout drawings and analysis of the Rolls-Royce Crecy-type sleeve had to be undertaken.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Gas chromatographic methods for analyzing hydrocarbon species in vehicle exhaust emissions were compared in terms of their collection efficiency, detection limit, repeatability and number of species detected using cylinder gas and tailpipe emission samples. The main methods compared were a Tenax cold trap injection (TCT) method (C5-C12 HCs) and a cold trap injection (CTI) method (C2-C4 HCs; C5-C12 HCs). Our own direct (DIR) method was used to confirm the collection efficiencies. Both methods yielded good results, but the CTI method showed low collection efficiency for some C2-C4 HCs. Measurement of individual species is needed with this method for accurate analysis of tailpipe emissions. Both the CTI method and the TCT method combined with the DIR method for determining C2-C4 HCs yielded nearly the same ozone specific reactivity values for the NMHC species analyzed.

Driver behaviour can strongly affect fuel consumption, and driver training in eco-driving techniques has been shown to reduce fuel consumption by 10% on average. However the effects of this training can be short-lived, so there is an apparent need for continuous monitoring of driver behaviour. This study presents a driver advisory tool which encourages eco-driving, and its evaluation in the field. The system, developed by Ashwoods Automotive Ltd (UK) and the University of Bath (UK), is aimed at fleet operators of light commercial vehicles, where the driver is typically a company employee. A significant strength of the system is that it has been designed for easy integration with the vehicle CAN-bus, reducing complexity and cost. By considering the Inertial Power Surrogate (speed times acceleration) the core algorithm is able to identify behaviour which is likely to increase fuel consumption.

Gasoline engines employ various mechanisms for improvement of fuel consumption and reduction of exhaust emissions to deal with environmental problems. Direct fuel injection is one such technology. This paper presents a new quasi-dimensional combustion model applicable to direct injection gasoline engine. The Model consists of author's original in-cylinder turbulence and mixture homogeneity sub model suitable for direct fuel injection conditions. Model validation results exhibit good agreement with experimental and 3D CFD data at steady state and transient operating conditions.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio is an example of a technology for improving the thermal efficiency of gasoline engines. A significant issue of a high compression ratio engine for improving fuel economy and low-end torque is prevention of knocking under a low engine speed. Knocking is caused by autoignition of the air-fuel mixture in the cylinder and seems to be largely affected by heat transfer from the intake port and combustion chamber walls. In this study, the influence of heat transfer from the walls of each part was analyzed by the following three approaches using computational fluid dynamics (CFD) and experiments conducted with a multi-cooling engine system. First, the temperature rise of the air-fuel mixture by heat transfer from each part was analyzed.

This paper describes a study of drag reduction devices for production pick-up trucks with a body-on-frame structure using full-scale wind tunnel testing and Computational Fluid Dynamics (CFD) simulations. First, the flow structure around a pick-up truck was investigated and studied, focusing in particular on the flow structure between the cabin and tailgate. It was found that the flow structure around the tailgate was closely related to aerodynamic drag. A low drag flow structure was found by flow analysis, and the separation angle at the roof end was identified as being important to achieve the flow structure. While proceeding with the development of a new production model, a technical issue of the flow structure involving sensitivity to the vehicle velocity was identified in connection with optimization of the roof end shape. (1)A tailgate spoiler was examined for solving this issue.

A continuously variable valve event and lift (VEL) system, actuated by oscillating cams, can provide optimum lift and event angles matching the engine operating conditions, thereby improving fuel economy, exhaust emission performance and power output. The VEL system allows small lift and event angles even in the engine operating region where the required intake air volume is small and the influence of valvetrain friction is substantial, such as during idling. Therefore, the system can reduce friction to lower levels than conventional valvetrains, which works to improve fuel economy. On the other hand, a distinct feature of oscillating cams is that their sliding velocity is zero at the time of peak lift, which differs from the behavior of conventional rotating cams. For that reason, it is assumed that the friction and lubrication characteristics of oscillating cams may differ from those of conventional cams.

There have been strong demands recently for reductions in the fuel consumption and exhaust emissions of diesel engines from the standpoints of conserving energy and curbing global warming. A great deal of research is being done on new emission control technologies using direct-injection (DI) diesel engines that provide high thermal efficiency. This work includes dramatic improvements in the combustion process. The authors have developed a new combustion concept called Modulated Kinetics (MK), which reduces smoke and NOx levels simultaneously by reconciling low-temperature combustion with pre-mixed combustion [1, 2]. At present, research is under way on the second generation of MK combustion with the aim of improving emission performance further and achieving higher thermal efficiency [3]. Reducing heat rejection in the combustion chamber is effective in improving the thermal efficiency of DI diesel engines as well as that of MK combustion.

The mechanism causing in-cylinder injector tip soot formation, which is the main source of particle number (PN) emissions under operating conditions after engine warm-up, was analyzed in this study. The results made clear a key parameter for reducing injector tip soot PN emissions. An evaluation of PN emissions for different amounts of injector tip wetting revealed that an injector with larger tip wetting forms higher PN emissions. The results also clarified that the amount of deposits does not have much impact on PN emissions. The key parameter for reducing injector tip soot is injector tip wetting that has a linear relationship with injector tip soot PN emissions.

This paper concerns research on an emission control system aimed at reducing emission levels to well below the ULEV standards. As emission levels are further reduced in the coming years, it is projected that measurement error will increase substantially. Therefore, an analysis was made of the conventional measurement system, which revealed the following major problems. 1. The conventional analyzer, having a minimum full-scale THC range of 10 ppmC, cannot measure lower concentration emissions with high accuracy. 2. Hydrocarbons are produced in various components of the measurement system, increasing measurement error. 3. Even if an analyzer with a minimum full-scale THC range of 1 ppmC is used in an effort to measure low concentrations, the 1 ppmC measurement range cannot be applied when the dilution air contains a high THC concentration. This makes it impossible to obtain highly accurate measurements. 4.

Since the stable operating region of a gasoline-fueled HCCI engine is limited to the part load condition, a mode change between SI and HCCI combustion is required, which poses an issue due to the difference in combustion characteristics. This report focuses on the combustion characteristics in the transitional range. The combustion mode in the transitional range is investigated by varying the internal EGR rate, intake air pressure, and spark advance timing in steady-state experiments. In this parametric study, stable SI-CI combustion is observed. This indicates that the combustion mode transition is possible without misfiring or knocking, regardless of the speed of variable valve mechanism which includes VVA, VVEL, VTEC, VVL and so on, though the response of intake air pressure still remains as a subject to be examined in the actual application.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio for improving thermal efficiency and downsizing the engine based on fuel-efficient operating conditions are good examples of technologies for enhancing gasoline engine fuel economy. A direct-injection system is adopted for most of these engines. Direct injection can prevent knocking by lowering the in-cylinder temperature through fuel evaporation in the cylinder. Therefore, direct injection is highly compatible with downsized engines that frequently operate under severe supercharging conditions for improving fuel economy as well as with high compression ratio engines for which susceptibility to knocking is a disadvantage.

The thermal environment in the automotive engine compartment is expected to become increasingly severe in the years ahead owing to the installation of a large-size manifold catalyst to reduce exhaust emissions, among other factors. This will make it even more important to analyze the engine compartment layout in terms of heat flow considerations at the design conceptualization stage of a new vehicle. In this research, a flow analysis program called DRAG4D was applied to find the flow velocity distribution and ambient air temperature distribution in the engine compartment during driving, idling and after the engine was turned off. This original program developed at Nissan takes into account the effects of the energy balance and buoyancy, and provides a practical level of prediction accuracy. The time required to create an analytical model and perform the computations has been shortened by using an automatic grid generation function, based on a solid model, and experimental equations.

A new method for measuring unregulated substances in the exhaust gas is being investigated to clarify the influence of the vehicles' exhaust emissions into the environment. This paper explains our work on developing an analysis method for detecting and quantifying trace substances in the exhaust gas. A new analysis method was examined that uses thermal desorption to analyze trace amounts of polycyclic aromatic hydrocarbons (PAHs) in vehicle exhaust gas. This technique is faster than conventional methods and does not require any preconditioning of the samples before analysis. While lead and chloromethane were detected in the exhaust gas samples, it was made clear that these substances did not originate in the engine system. Accordingly, the results of this study indicate that careful attention must be paid to the test environment and the presence of measurement interfering substances in exhaust samples when measuring trace constituents in the exhaust gas from low-emission vehicles.

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.

Turbocharging has become the favored approach for downsizing internal combustion engines to reduce fuel consumption and CO2 emissions, without sacrificing performance. Matching a turbocharger to an engine requires a balance of various design variables in order to meet the desired performance. Once an initial selection of potential compressor and turbine options is made, corresponding performance maps are evaluated in 1D engine cycle simulations to down-select the best combination. This is the conventional matching procedure used in industry and is ‘passive’ since it relies on measured maps, thus only existing designs may be evaluated. In other words, turbine characteristics cannot be changed during matching so as to explore the effect of design adjustments. Instead, this paper presents an ‘adaptive’ matching methodology for the turbocharger turbine.

This study describes an innovative monolith structure designed for applications in automotive catalysis using an advanced manufacturing approach developed at Imperial College London. The production process combines extrusion with phase inversion of a ceramic-polymer-solvent mixture in order to design highly ordered substrate micro-structures that offer improvements in performance, including reduced PGM loading, reduced catalyst ageing and reduced backpressure. This study compares the performance of the novel substrate for CO oxidation against commercially available 400 cpsi and 900 cpsi catalysts using gas concentrations and a flow rate equivalent to those experienced by a full catalyst brick when attached to a vehicle. Due to the novel micro-structure, no washcoat was required for the initial testing and 13 g/ft3 of Pd was deposited directly throughout the substrate structure in the absence of a washcoat.