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Exhaust Gas Recirculation (EGR) is one of several technologies that are being investigated to deliver future legislative emissions targets for diesel engines. Its application requires a detailed understanding of the thermo-fluidic processes within the engine's air system. A validated Computational Fluid Dynamics (CFD) process is one way of providing this understanding. This paper describes a CFD process to analyse unsteady manifold flows and mixing fields in the presence of realistic levels of EGR. The validation methodology was drawn from the American Institute of Aeronautics and Astronautics (AIAA) and divides the problem into smaller elemental problems. Detailed knowledge about these elemental problems is easily attainable, reducing the requirement for a large number of complex validation runs. The final validated process was compared to flow visualization and particle image velocimetry (PIV) data collected from a motored engine.

Modern automotive industry is driven by improved fuel efficiency, whilst simultaneously increasing output power and reducing size/weight of vehicle components. This trend has the drawback of inducing various Noise, Vibration and Harshness (NVH) concerns in the drivetrain, since fairly low energy excitation often suffices to excite natural modes of thin walled structures, such as the transmission bell housing. Transmission rattle is one of the many undesired NVH issues, originating from irregularities in engine torque output. The crankshaft speed fluctuations are transferred through the transmission input shaft. Transmission compactness also allows repetitive interaction of conjugate loose gear pairs. The engine fluctuations disturb the otherwise unintended, but orderly meshing of these loose gears. This often leads to radiation of a characteristic air-borne noise from the impact sites.

The automotive industry is subject to increasing pressure to reduce the CO2 emissions and improve fuel efficiency in internal combustion engines. Improvements may be achieved in a number of ways. The parasitic losses throughout the engine cycle emanate from friction in all engine contact conjunctions in addition to pumping losses. In particular one main contributory conjunction is the piston ring pack assembly. At low engine speeds, the contribution of friction to the total losses within the engine is increased significantly compared with the thermodynamic losses. Additionally, the sealing capability of the ring is crucial in determining the power output of the engine with any loss of sealing contributing to power loss, as well as blowby. Most reported studies on compression ring-cylinder conjunction do not take into account complex ring in-plane and out-of-plane elastodynamics.

Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program.

Diesel homogeneous charge compression ignition (HCCI) engines with early injection can result in significant spray/wall impingement which seriously affects the fuel efficiency and emissions. In this paper, the spray/wall interaction models which are available in the literatures are reviewed, and the characteristics of modeling including spray impingement regime, splash threshold, mass fraction, size and velocity of the second droplets are summarized. Then three well developed spray/wall interaction models, O'Rourke and Amsden (OA) model, Bai and Gosman (BG) model and Han, Xu and Trigui (HXT) model, are implemented into KIVA-3V code, and validated by the experimental data from recent literatures under the conditions related to diesel HCCI engines. By comparing the spray pattern, droplet mass, size and velocity after the impingement, the thickness of the wall film and vapor distribution with the experimental data, the performance of these three models are evaluated.

With the increasing stringent emissions legislation on ICEs, alongside requirements for enhanced fuel efficiency as key driving factors for many OEMs, there are many research activities supported by the automotive industry that focus on the development of hybrid and pure EVs. This change in direction from engine downsizing to the use of electric motors presents many new challenges concerning NVH performance, durability and component life. This paper presents the development of experimental methodology into the measurement of NVH characteristics in these new powertrains, thus characterizing the structure borne noise transmissibility through the shaft and the bearing to the housing. A feasibility study and design of a new system level test rig have been conducted to allow for sinusoidal radial loading of the shaft, which is synchronized with the shaft’s rotary frequency under high-speed transient conditions in order to evaluate the phenomena in the system.

Understanding and predicting in-cylinder flow structures that occur within compression-ignition engines is vital if further optimisation of combustion systems is to be achieved. To enable this prediction, fully validated computational models of the complex turbulent flow-fields generated during the intake and compression process are needed. However, generating, analysing and interpreting experimental data to achieve this validation remains a complex challenge due to the variability that occurs from cycle to cycle. The flow-velocity data gathered in this study, obtained from a single-cylinder CI engine with optical access using high-speed PIV, demonstrates that significantly different structures are generated over different cycles, resulting in the mean flow failing to adequately reflect the typical flow produced in-cylinder.

Methyl esters derived from vegetable oils by the process of transesterification (commonly referred as ‘biodiesel’), can be used as an alternative fuel in compression ignition engines. In this study, three different vegetable oils (rape, soy and waste oil) were used to produce biodiesel fuels that were then tested in a four cylinder direct injection engine, typically used in small diesel genset applications. Engine performance and emissions were recorded at five load conditions and at two different speeds. This paper presents the results obtained for measurements of NOx and smoke opacity at the different speed and load conditions for the three biodiesels, and their blends (5 and 50% v/v) with mineral diesel. A simple combustion analysis was also performed where ignition delay, position and magnitude of peak cylinder pressure and heat release rate were examined to asses how the variation of chemical structure and blend percentage affects engine performance.

Natural gas as an alternative fuel offers the potential of clean combustion and emits relatively low CO2 emissions. The main constitute of natural gas is methane. Historically, the slow burning speed of methane has been a major concern for automotive applications. Literature on experimental methane-gasoline Dual Fuel (DF) studies on research engines showed that the DF strategy is improving methane combustion, leading to an enhanced initial establishment of burning speed even compared to that of gasoline. The mechanism of such an effect remains unclear. In the present study, pure methane (representing natural gas) and PRF95 (representing gasoline) were supplied to a constant volume combustion vessel to produce a DF air mixture. Methane was added to PRF95 in three different energy ratios 25%, 50% and 75%. Experiments have been conducted at equivalence ratios of 0.8, 1, 1.2, initial pressures of 2.5, 5 and 10 bar and a temperature of 373K.

For diesel engines, fuel path control plays a key role in achieving optimal emissions and fuel economy performance. There are several fuel path parameters that strongly affect the engine performance by changing the combustion process, by modifying for example, start of injection and fuel rail pressure. This is a multi-input multi-output problem. Linear Model Predictive Control (MPC) is a good approach for such a system with optimal solution. However, fuel path has fast dynamics. On-line optimisation MPC is not the good choice to cope with such fast dynamics. Explicit MPC uses off-line optimisation, therefore, it can be used to control the system with fast dynamics.

An application in the automotive filed for the Genetic Learning Automata Fuzzy Classifier System is presented in this work. As a non-linear model free-based strategy, the major advantages of this approach are its modularity and its extensibility. A controller designed using this method for a quarter-car model is applied to a 6-DOF model giving a reasonable performance. Comparisons with the LQR controller are also carried out.

In the globalization of the automotive businesses, manufacturing companies and their suppliers are forced to distribute the various lifecycle phases in different geographical locations. Misunderstandings arising from the variety of personnel involved, each with different requirements, backgrounds, roles, cultures and skills for example can result in increased cost and development time. To enable collaborating companies to have a common platform for interaction, the COMPANION project at Loughborough University has been undertaken to develop a common model-based environment for manufacturing automotive engines. Through the use of this environment, the stakeholders will be able to “visualize” consistently the evolution of automated systems at every lifecycle stage i.e. requirements definition, specification, design, analysis, build, evaluation, maintenance, diagnostics and recycle.

Thermoelectric generator (TEG) has received more and more attention in its application in the harvesting of waste thermal energy in automotive engines. Even though the commercial Bismuth Telluride thermoelectric material only have 5% efficiency and 250°C hot side temperature limit, it is possible to generate peak 1kW electrical energy from a heavy-duty engine. If being equipped with 500W TEG, a passenger car has potential to save more than 2% fuel consumption and hence CO2 emission reduction. TEG has advantages of compact and motionless parts over other thermal harvest technologies such as Organic Rankine Cycle (ORC) and Turbo-Compound (TC). Intense research works are being carried on improving the thermal efficiency of the thermoelectric materials and increasing the hot side temperature limit. Future thermoelectric modules are expected to have 10% to 20% efficiency and over 500°C hot side temperature limit.

This paper deals with experimental investigations of the in-cylinder flow structures under steady state conditions utilizing Particle Image Velocimetry (PIV). The experiments have been conducted on an engine head of a pent-roof type (Lotus) for a number of fixed valve lifts and different inlet valve configurations at two pressure drops, 250mm and 635mm of H2O that correlate with engine speeds of 2500 and 4000 RPM respectively. From the two-dimensional in-cylinder flow measurements, a tumble flow analysis is carried out for six planes parallel to the cylinder axis. In addition, a swirl flow analysis is carried out for one horizontal plane perpendicular to the cylinder axis at half bore downstream from the cylinder head (44mm). The results show the advantage of using the planar technique (PIV) for investigating the complete flow structures developed inside the cylinder.

The use of Direct Injection for spark ignition engines is increasing, with a noticeable trend towards smaller flow orifices as the requirement for improved atomisation increases and improved manufacturing capabilities allow micron sized holes to be mass produced. It is necessary therefore to develop test rigs and diagnostic techniques that will allow the collection of data from inside real sized nozzles in order to validate CFD models and allow optimized nozzle geometries to be rapidly designed and produced. This paper demonstrates real sized optical nozzles and diagnostic techniques that have allowed geometry evaluation and optimization in pressure swirl and plain orifice nozzles as small as 150μm.

Limiting problematic Noise, Vibration and Harshness (NVH) phenomena in the modern automotive drivetrain is a task of critical importance. The result of such phenomena is the aggravation of the driver, which results in a reduced perception of vehicle quality. Each phenomenon can be characterized by a distinct frequency range. The aim of the current study is to assess the influence of the interfacial frictional behavior of the dry friction clutch components on the drivetrain dynamic behavior. The dynamics of the system (in terms of its stability) are studied. Surface data from the clutch components are critical to understanding the complex engagement process. The coefficient of friction was measured using a rotary tribometer at representative slip speeds and contact pressures. To aid the analysis infinite focus microscopy was used to measure the geometric properties of the constituent components of the drivetrain.

Particulate Matter (PM) emissions reduction is an imminent challenge for Direct Injection Spark Ignition (DISI) engine designers due to the introduction of Particulate Number (PN) standards in the proposed Euro 6 emissions legislation aimed at delivering the next phase of air quality improvements. An understanding of how the formation of combustion-derived nanoparticulates in engines is affected by the engine operating temperature is important for air quality improvement and will influence future engine design and control strategies. This investigation has examined the effect on combustion and PM formation when reducing the engine operating temperature to -7°C. A DISI single-cylinder optical research engine was modified to simulate a range of operating temperatures down to the proposed -7°C.

The control of Homogeneous Charge Compression Ignition (HCCI) (also known as Controlled Auto Ignition (CAI)) has been a major research topic recently, since this type of combustion has the potential to be highly efficient and to produce low NOx and particulate matter emissions. Ion current has proven itself as a closed loop control feedback for SI engines. Based on previous work by the authors, ion current was acquired through HCCI operation too, with promising results. However, for best utilization of this feedback signal, advanced interpretation techniques such as artificial neural networks can be used. In this paper the use of these advanced techniques on experimental data is explored and discussed. The experiments are performed on a single cylinder cam-less (equipped with a Fully Variable Valve Timing (FVVT) system) research engine fueled with commercially available gasoline (95 ON).

In this work, cyclic combustion simulations of a spark ignition engine were performed using the Large Eddy Simulation techniques. The KIVA-4 RANS code was modified to incorporate the LES capability. The flame surface density approach was implemented to model the combustion process. Ignition and flame kernel models were also developed to simulate the early stage of flame propagation. A dynamic procedure was formulated where all model coefficients were locally evaluated using the resolved and test filtered flow properties during the fully developed phase of combustion. A test filtering technique was adopted to use in wall bounded systems. The developed methodology was then applied to simulate the combustion and associated unsteady effects in a spark ignition engine. The implementation was validated using the experimental data taken from the same engine.

This paper presents research into a novel autoselective electric discharge method for regenerating monolithic wall flow diesel particulate filters using low power over the entire range of temperatures and oxygen concentrations experienced within the exhaust systems of modern diesel engines. The ability to regenerate the filter independently of exhaust gas temperature and composition significantly reduces system complexity compared to other systems. In addition, the system does not require catalyst loading and uses only mass- produced electronic and electrical components, thus reducing the cost of the after-treatment package. Purpose built exhaust gas simulation test rigs were used to evaluate, develop and optimise the autoselective regeneration system. On-engine testing demonstrated the performance of the autoselective regeneration process under real engine conditions.