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In recent years magnetic resonance imaging (MRI) has been shown to be an attractive method for fluid flow visualization. In this work, we show how MRI velocimetry techniques can be used to non-invasively investigate and visualize the hydrodynamics of exhaust gas in a diesel particulate filter (DPF), both when clean and after loading with diesel engine exhaust particulate matter. The measurements have been used to directly measure the gas flow in the inlet and outlet channels of the DPF, both axial profiles along the length and profiles across the channel diameter. Further, from this information we show that it is possible to indirectly ascertain the superficial wall-flow gas velocity and the soot loading profiles along the filter channel length.

Recent developments in diesel engines lead to increased fuel efficiency and reduced exhaust gas temperature. Therefore more energy efficient aftertreatment systems are required to comply with tight emission regulations. In this study, a computational fluid dynamics package was used to investigate the thermal behaviour of a diesel aftertreatment system. A parametric study was carried out to identify the most influential pipework material and insulation characteristics in terms of thermal performance. In the case of the aftertreatment pipework and canning material effect, an array of different potential materials was selected and their effects on the emission conversion efficiency of a Diesel Oxidation Catalyst (DOC) were numerically investigated over a driving cycle. Results indicate that although the pipework material's volumetric heat capacity was decreased by a factor of four, the total emission reduction was only considerable during the cold start.

Homogeneous Charge Compression Ignition (HCCI) has emerged as a promising technology for reduction of exhaust emissions and improvement of fuel economy of internal combustion engines. There are generally two proposed methods of realizing the HCCI operation. The first is through the control of gas temperature in the cylinder and the second is through the control of chemical reactivity of the fuel and air mixture. EGR trapping, i.e., recycling a large quantity of hot burned gases by using special valve-train events (e.g. negative valve overlap), seems to be practical for many engine configurations and can be combined with any of the other HCCI enabling technologies. While this method has been widely researched, it is understood that the operating window of the HCCI engine with negative valve overlap is constrained, and the upper and lower load boundaries are greatly affected by the in-cylinder temperature.

The traditional system design methodology (which follows a preliminary design, analysis, appraisal and redesign pattern) for automotive systems makes balancing contradicting design constraints such as cost, reliability and performance very difficult. Often all of the constraints are not met, and, even if they are, the resultant design may be sub-optimal. This paper outlines a new design approach using constraint satisfaction methods to create an optimal design, where all of the constraints are satisfied. Once the constraints are identified and represented in a suitable format, the design task can be semi-automated using a suitable algorithm. This paper explains how to identify and represent constraints in an automotive problem, the algorithms that can be used to solve the design problem, and how the outcome can be used as an extension to the existing design methodology.

In the automotive industry, engine downsizing has been widely accepted as an enabler to improving the fuel economy and reducing the CO₂ emissions. The Atkinson cycle is one of the key technologies. In this paper, the Atkinson cycle with different expansion ratios are compared and analyzed. The investigation is compared with the benchmark whose expansion and compression ratio are identical. The aim is to understand the inherent characteristics of the over-expansion and its effect on the engine performance and emissions. The simulation results show that, the Atkinson cycle produces higher efficiency due to over-expansion. The Atkinson cycle has higher internal EGR compared with the benchmark at equivalent conditions, which contributes to lower the NOx and CO emissions.

Aluminum metal matrix composites reinforced with particulates have attracted much attention in the automotive industry, due to their improved wear resistance in comparison to aluminum alloys, in recent years. The wear behavior is the critical factor influencing the product life and performance in engineering components. Carbon nanotubes (CNT) are one of the most promising candidates of reinforcements used to improve mechanical strength such as wear in metal matrix composites (MMCs). However, in industrial applications, wear tests are relatively expensive and prolonged. As a result, for several years, research has been increasingly concentrated on development of wear prediction models. In this study, prediction of wear behavior of aluminum (Al) matrix (MMCs) reinforced with different amounts (0, 0.5, 1 and 2 wt%) of CNTs was investigated. A nonlinear autoregressive exogenous (NARX) model structure was chosen for the modeling.

Millimetre wave radar sensors are being actively developed for automotive applications including Intelligent Cruise Control (ICC), Collision Warning (CW), and Collision Avoidance (CA). Knowledge of the road geometry is of fundamental importance to these future intelligent automotive systems. The interest in such systems is evidenced by manufacturers now starting to incorporate radars in production luxury vehicles. Determination of the road geometry, day and night, under all weather conditions, is a challenging problem requiring both fundamental research and systems studies. Current automotive radar systems rely heavily on the use of extrapolating yaw rate data generated within the vehicle to produce a prediction of the path of the road ahead. This use of historical data is only satisfactory if the road trajectory is uniform. Sudden discontinuities in the path, such as bends, cause this method of path prediction to produce significant errors.

Computational Fluid Dynamics (CFD) is used to simulate chemical reactions and transport phenomena occurring in a single channel of a honeycomb-type automotive catalytic converter under lean burn combustion. Microkinetic analysis is adopted to develop a detailed elementary reaction mechanism for propane oxidation on a silver catalyst. Activation energies are calculated based on the theory of the Unity Bond Index-Quadratic Exponential Potential (UBI-QEP) method. The order-of-magnitude of the pre-exponential factors is obtained from Transition State Theory (TST). Sensitivity analysis is applied to identify the important elementary steps and refine the pre-exponential factors of these reactions. These pre-exponential factors depend on inlet temperatures and propane concentration; therefore optimised pre-exponential factors are written in polynomial forms. The results of numerical simulations are validated by comparison with experimental data.

The use of accurate tire material properties is a major requirement for conducting a successful tire analysis using finite element method (FEM). Obtaining these material properties however poses a major challenge for tire modelers and researchers due to the complex nature of tire material and associated proprietary protections of constituent material properties by tire manufactures. In view of this limitation, a simple and effective procedure for generating tire materials data used in tire finite element analysis (FEA) is presented in this paper. All the tire test specimens were extracted from a tire product based on special considerations such as specimen dimension and shape, test standard, precondition of specimen and test condition for cords. The required material properties of tire rubber component, including hyperelasticity and viscoelasticity were obtained using simple uni-axial tension test.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

The lubricating properties of two sustainable alternative diesels blended with ultra low sulphur diesel (ULSD) were investigated. The candidate fuels were a biodiesel consisting of fatty acid methyl esters derived from rapeseed (RME) and gas-to-liquid (GTL). Lubricity tests were conducted on a high frequency reciprocating rig (HFRR). The mating specimen surfaces were analysed using optical microscopy and profilometery for wear scar diameters and profiles respectively. Microscopic surface topography and deposit composition was evaluated using a scanning electronic microscope (SEM) with an energy dispersive spectrometer (EDS). Like all modern zero sulphur diesel fuel (ZSD), GTL fuels need a lubricity agent to meet modern lubricity specifications. It has been proven that GTL responds well to typical lubricity additives in the marketplace.

Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

Diesel engines are the versatile power source and is widely used in passenger car and commercial vehicle applications. Environmental temperature conditions, fuel quality, fuel injection strategies and lubricant have influence on cold start performance of the diesel engines. Strategies to overcome the cold start problem at very low ambient temperature include preheating of intake air, coolant, cylinder block. The present research work investigates the effect of coolant temperatures on passenger car diesel engine’s performance and exhaust emission characteristics during the cold start at cold ambient temperature conditions. The engine is soaked in the -7°C environment for 6 hours. The engine coolant is preheated to the desired coolant temperatures of 10 and 20°C by an external heater and the start ability tests were performed.

Due to the emission benefits of the oxygen in the fuel molecule, the interest for the use of ethanol as fuel blend components in compression ignition engines has been increased. However the use of fuel blends with high percentage of ethanol can lead to poor fuel blend quality (e.g. fuel miscibility, cetane number, viscosity and lubricity). An approach which can be used to improve these properties is the addition of biodiesel forming ternary blends (ethanol-biodiesel-diesel). The addition of castor oil-derived biodiesel (COME) containing a high proportion of methyl ricinoleate (C18:1 OH) is an attractive approach in order to i) reduce the use of first generation biodiesel derived from edible sources, ii) balance the reduction in viscosity and lubricity of ethanol-diesel blends due to the high viscosity and excellent lubricity of methyl ricinoleate.

Dieseline combustion as a concept combines the advantages of gasoline and diesel by offline or online blending the two fuels. Dieseline has become an attractive new compression ignition combustion concept in recent years and furthermore an approach to a full-boiling-range fuel. High speed imaging with near-parallel backlit light was used to investigate the spray characteristics of dieseline and pure fuels with a common rail diesel injection system in a constant volume vessel. The results were acquired at different blend ratios, and at different temperatures and back pressures at an injection pressure of 100MPa. The penetrations and the evaporation states were compared with those of gasoline and diesel. The spray profile was analyzed in both area and shape with statistical methods. The effect of gasoline percentage on the evaporation in the fuel spray was evaluated.

In this work, a detailed process for manufacturing 3D alumina composite microengine pistons is presented. A novel moulding process is developed for shaping alumina composites into accurate micrometer-sized parts with a combination of softlithography micromoulding techniques and colloidal ceramic powder process. Ultrathick SU-8 UV-lithography is used for making master moulds followed by mirror duplication of PDMS softmoulds. A preceramic coating resin (PCR) was used as the binder instead of the traditionally organic binders and the PCR turns into an additive to the composite after the sintering process. The sedimentation of Al2O3/acetone suspensions has been characterized with varying poly vinyl pyrrolidone (PVP) as a dispersant. Optimized PCR and curing conditions have been investigated in the soft moulding process, and prove successful in achieving dense and uniform microcomponents.

The development of intelligent tire technology from concept to application covers multi-disciplinary fields. During the course of development, the computational method can play a significant role in understanding tire behavior, assisting in the design of the intelligent tire prototype system and in developing tire parameters estimation algorithm, etc. In this paper, a finite element tire model was adopted for developing a strain-based intelligent tire system. The finite element tire model was created considering the tire's composite structure and nonlinear properties of its constituent materials, and the FE model was also validated by physical tests. The FE model is used to study tire strain characteristics by steady state simulation for straight line rolling, traction and braking, as well as cornering. Tire loading conditions were estimated by feature extraction and data fitting.

Biofuels development and specification are currently driven by the engine (mainly gasoline- and diesel-type) technology, existing fossil fuel specification and availability of feedstock. The ability to use biofuels with conventional fuels without jeopardising the standard fuel specifications is a very effective means for the implementation of these fuels. In this work the effect of dual fuelling with in-cylinder injected ULSD fuel or synthetic second generation biofuels (a Gas-To-Liquid GTL fuel as a surrogate of these biofuels as its composition, specifications and production process are very similar to second generation biofuels) and with inlet port injected bioethanol on the engine performance and emissions were investigated. The introduction of anhydrous bioethanol improved the NOx and smoke emissions, but increased total hydrocarbons and carbon monoxide.

This paper presents a computational investigation of the in-cylinder charge characteristics within a motored 4-valve direct injection HCCI engine cylinder with applied negative valve overlapping. Non-typical intake valve strategy was investigated; whereby the pair of intake valves was assumed to follow the same low-lift short-duration valve-lift profile but actuated at different timings. The phase of intake-valve-opening relative to that of exhaust-valve-closing was optimized in terms of pumping losses. The flow fields generated with such an intake valve strategy were compared to those produced in the same engine cylinder but with typical early and late intake-valve-timing. The computational results of such an approach showed modifications in the in-cylinder swirl and tumble motions during the intake and compression strokes.

Disc brake noise is recognized as a major problem of the automotive industry. Various experimental and numerical techniques have been developed to model the noisy brake and investigate possible solutions. Developing a virtual model of the disc brake which can accurately reproduce the behavior of the brake unit under different conditions is a considerable step forward towards reaching this goal. Among various aspects of the analytical model of a disc brake, application of the correct value of damping based on the material properties and functional frequency range of each component is a significant factor in ensuring correct prediction of the brake system behavior. Complex Eigenvalue Analysis is well established as a tool for predicting brake instabilities which can potentially lead to brake noise. However, it is known to over-predict instabilities i.e. predict instabilities which do not occur in the real brake system.