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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.

This paper describes a detailed study into the use of a pitot probe to measure air flow around an inlet valve under steady state conditions. The study was undertaken to assess the feasibility of the method for locating areas of a port and valve which may be contributing to a poor overall discharge coefficient. This method would provide a simple and cheap experimental tool for use throughout the industry. The method involves mounting a miniature internal chamfer pitot tube on a slider attached to the base of the valve. The probe can traverse the appropriate area by rotating the valve and moving it along the slide. Changing the probe allows measurements in different planes, allowing the whole region around the valve to be surveyed. The cylinder head complete with instrumentation is mounted on a steady flow rig. The paper presents the results obtained at different valve lifts on a production cylinder head.

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).

Closed-loop electronic control is a proven and efficient way to optimize spark ignition engine performance and to control pollutant emissions. In-cylinder pressure sensors provide accurate information on the quality of combustion. The conductivity of combustion flames can alternatively be used as a measure of combustion quality through ion-current measurements. In this paper, combustion diagnostics through ion-current sensing are studied. A single cylinder research engine was used to investigate the effects of misfire, ignition timing, air to fuel ratio, compression ratio, speed and load on the ion-current signal. The ion-current signal was obtained via one, or both, of two additional, remote in-cylinder ion sensors (rather than by via the firing spark plug, as is usually the case). The ion-current signals obtained from a single remote sensor, and then the two remote sensors are compared.

There is a great deal of interest in new technologies to assist in reducing the CO2 output of passenger vehicles, as part of the drive to meet the limits agreed by the EU and the European Automobile Manufacturer's Association ACEA, itself a result of the Kyoto Protocol. For the internal combustion engine, the most promising of these include gasoline direct injection, downsizing and fully variable valve trains. While new types of spray-guided gasoline direct injection (GDI) combustion systems are finally set to yield the level of fuel consumption improvement which was originally promised for the so-called ‘first generation’ wall- and air-guided types of GDI, injectors for spray-guided combustion systems are not yet in production to help justify the added complication and cost of the NOx trap necessary with a stratified combustion concept.

This paper presents a method to achieve a low order system model of the urea-based SCR catalyst coated filter (SCR-in-DPF or SCRF or SDPF), while preserving a high degree of fidelity. Proper orthogonal decomposition (POD), also known as principal component analysis (PCA), or Karhunen-Loéve decomposition (KLD), is a statistical method which achieves model order reduction by extracting the dominant characteristic modes of the system and devises a low-dimensional approximation on that basis. The motivation for using the POD approach is that the low-order model directly derives from the high-fidelity model (or experimental data) thereby retains the physics of the system. POD, with Galerkin projection, is applied to the 1D + 1D SCR-in-DPF model using ammonia surface coverage and wall temperature as the dominant system states to achieve model order reduction.

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.

Electromechanical actuation systems are being considered as an alternative to hydraulic systems for controlling clutches and gearshifts in transmissions, since they offer the potential for improved efficiency, better packaging and a reduction in component count. A high-force direct-drive linear electromechanical actuator has been developed which acts directly on the shift rails of either an Automated Manual Transmission (AMT) or a Dual Clutch Transmission (DCT) to facilitate gear selection and provide shift-by-wire functionality. This actuation scheme offers a number of advantages over electric motor and gearbox actuator designs, including simplified construction; the elimination of mechanical gearing, which reduces mechanical hysteresis, backlash and compliance; a low component count, which results in improved robustness; a better dynamic response and the potential for zero ‘off-state’ power consumption.

The paper presents a novel method for the measurement of lubricant film thickness in the piston-liner contact. Direct measurement of the film in this conjunction has always posed a problem, particularly under fired conditions. The principle is based on capturing and analysing the reflection of an ultrasonic pulse at the oil film. The proportion of the wave amplitude reflected can be related to the thickness of the oil film. A single cylinder 4-stroke engine on a dyno test platform was used for evaluation of the method. A piezo-electric transducer was bonded to the outside of the cylinder liner and used to emit high frequency short duration ultrasonic pulses. These pulses were used to determine the oil film thickness as the piston skirt passed over the sensor location. Oil films in the range 2 to 21 μm were recorded varying with engine speeds. The results have been shown to be in agreement with detailed numerical predictions.

Homogeneous charge compression ignition (HCCI), combustion has the potential to be highly efficient and to produce low NOx, carbon dioxide and particulate matter emissions, but experiences problems with cold start, running at idle and producing high power density. A solution to these is to operate the engine in a ‘hybrid mode’, where the engine operates in spark ignition mode at cold start, idle and high loads and HCCI mode elsewhere during the drive cycle, demanding a seamless transition between the two modes of combustion through spark assisted controlled auto ignition. Moreover; HCCI requires considerable control to maintain consistent start of combustion and heat release rate, which has thus far limited HCCI's practical application. In order to provide a suitable control method, a feedback signal is required.

Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form.

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.

GTDI engines are becoming more efficient, whether individually or part of a HEV (Hybrid Electric Vehicle) powertrain. For the latter, this efficiency manifests itself as increase in zero emissions vehicle mileage. An ideal device for energy recovery is a turbogenerator (TG), and, when placed downstream the conventional turbine, it has minimal impact on catalyst light-off and can be used as a bolt-on aftermarket device. A Ricardo WAVE model of a representative GTDI engine was adapted to include a TG (Turbogenerator) and TBV (Turbine Bypass Valve) with the TG in a mechanical turbocompounding configuration, calibrated using steady state mapping data. This was integrated into a co-simulation environment with a SISO (Single-Input, Single-Output) dynamic controller developed in SIMULINK for the actuator control (with BMEP, manifold air pressure and TG pressure ratio as the controlled variables).

Vehicle emissions and fuel economy in real-world driving conditions are currently under considerable scrutiny. Key to achieving optimum performance for a given hardware set and control scheme is a calibration that optimizes controller gains such that inputs are scheduled over the operating space to minimize emissions and maximize fuel economy. Generating a suitable calibration requires data that is both precise and accurate, this data is used to generate models that are deployed as part of the calibration optimization process. This paper evaluates the repeatability of typical steady-state measurements used for calibration of engine controllers that will ultimately determine vehicle level emissions for homologation include Real Driving Emissions (RDE). Stabilization requirements as indicated by three different measurements are evaluated and shown to be different within the same experiment, depending on the metric used.

In modern powertrains systems, sensors are critical elements for advanced control. The identification of sensing requirements for such highly nonlinear systems is technically challenging. To support the sensor selection process, this paper proposes a methodology to quantify the information gained from sensors used to control nonlinear dynamic systems using a dynamic probabilistic framework. This builds on previous work to design a Bayesian observer to deal with nonlinear systems. This was applied to a bimodal model of the SCR aftertreatment system. Despite correctly observing the bimodal distribution of the internal Ammonia-NOx Ratio (ANR) state, it could not distinguish which state is the true state. This causes issues for a control engineer who is less interested in how precise a measurement is and more interested in the location within control parameter space. Information regarding the dynamics of the systems is required to resolve the bimodality.

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

As part of an ongoing programme of Exhaust Gas Recirculation (EGR) wear investigations, this paper reports a study into the effect of Exhaust Gas Recirculation, and a variety of interacting factors, on the wear rate of the top piston ring and the liner top ring reversal point on a 1.0 litre/cylinder medium duty four cylinder diesel engine. Thin Layer Activation (TLA - also known as Surface Layer Activation in the US) has been used to provide individual wear rates for these components when engine operating conditions have been varied. The effects of oil condition, EGR level, fuel sulphur content and engine coolant temperature have been investigated at one engine speed at full load. The effects of engine load and uncooled EGR have also been assessed. The effects of these parameters on engine wear are presented and discussed. When EGR was applied a significant increase in wear was observed at EGR levels of between 10% and 15%.

The efficient generation of relatively large quantities of electrical energy in vehicles is becoming an increasingly important issue, as a result of the increasing demands of ancillary electrical equipment and the emergence of hybrid power-train vehicles. An attractive solution to meeting these demands is to extract the electrical energy by means of a generator driven by a high speed exhaust mounted turbine, a technology which is beginning to emerge commercially. This paper is concerned with the design of a system, which extends this concept to enable both electrical generation and highly flexible air management. The heart of the system is a high-speed switched reluctance (SR) electrical machine, the rotor of which is located on a common shaft with the turbine and compressor wheels of a standard commercially available turbocharger.

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.

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.