Search Results

The paper discusses the concept, design and final results from the ‘Ultra Boost for Economy’ collaborative project, which was part-funded by the Technology Strategy Board, the UK's innovation agency. The project comprised industry- and academia-wide expertise to demonstrate that it is possible to reduce engine capacity by 60% and still achieve the torque curve of a modern, large-capacity naturally-aspirated engine, while encompassing the attributes necessary to employ such a concept in premium vehicles. In addition to achieving the torque curve of the Jaguar Land Rover naturally-aspirated 5.0 litre V8 engine (which included generating 25 bar BMEP at 1000 rpm), the main project target was to show that such a downsized engine could, in itself, provide a major proportion of a route towards a 35% reduction in vehicle tailpipe CO2 on the New European Drive Cycle, together with some vehicle-based modifications and the assumption of stop-start technology being used instead of hybridization.

Increasingly stringent regulations and rising fuel costs require that automotive manufacturers reduce their fleet CO2 emissions. Gasoline engine downsizing is one such technology at the forefront of improvements in fuel economy. As engine downsizing becomes more aggressive, normal engine operating points are moving into higher load regions, typically requiring over-fuelling to maintain exhaust gas temperatures within component protection limits and retarded ignition timings in order to mitigate knock and pre-ignition events. These two mechanisms are counterproductive, since the retarded ignition timing delays combustion, in turn raising exhaust gas temperature. A key process being used to inhibit the occurrence of these knock and pre-ignition phenomena is cooled exhaust gas recirculation (EGR). Cooled EGR lowers temperatures during the combustion process, reducing the possibility of knock, and can thus reduce or eliminate the need for over-fuelling.

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.

The paper discusses investigations into improving the full-load and transient performance of the Ultraboost extreme downsizing engine by the application of the SuperGen variable-speed centrifugal supercharger. Since its output stage speed is decoupled from that of the crankshaft, SuperGen is potentially especially attractive in a compound pressure-charging system. Such systems typically comprise a turbocharger, which is used as the main charging device, compounded at lower charge mass flow rates by a supercharger used as a second boosting stage. Because of its variable drive ratio, SuperGen can be blended in and out continuously to provide seamless driveability, as opposed to the alternative of a clutched, single-drive-ratio positive-displacement device. In this respect its operation is very similar to that of an electrically-driven compressor, although it is voltage agnostic and can supply other hybrid functionality, too.

Due to the variability of real traffic conditions for vehicle testing, real-world vehicle performance estimation using simulation method become vital. Especially for heavy duty vehicles (e.g. 40 t trucks), which are used for international freight transport, real-world tests are difficult, complex and expensive. Vehicle simulations use mathematical methods or commercial software, which take given driving cycles as inputs. However, the road situations in real driving are different from the driving cycles, whose speed profiles are obtained under specific conditions. In this paper, a real-world vehicle performance estimation method using simulation was proposed, also it took traffic and real road situations into consideration, which made it possible to investigate the performance of vehicles operating on any roads and traffic conditions. The proposed approach is applicable to all kind of road vehicles, e.g. trucks, buses, etc. In the method, the real-road network includes road elevation.

The use of Wankel rotary engines as a range extender has been recognised as an appealing method to enhance the performance of Hybrid Electric Vehicles (HEV). They are effective alternatives to conventional reciprocating piston engines due to their considerable merits such as lightness, compactness, and higher power-to-weight ratio. However, further improvements on Wankel engines in terms of fuel economy and emissions are still needed. The objective of this work is to investigate the engine modelling methodology that is particularly suitable for the theoretical studies on Wankel engine dynamics and new control development. In this paper, control-oriented models are developed for a 225CS Wankel rotary engine produced by Advanced Innovative Engineering (AIE) UK Ltd. Through a synthesis approach that involves State Space (SS) principles and the artificial Neural Networks (NN), the Wankel engine models are derived by leveraging both first-principle knowledge and engine test data.

This paper describes the characterisation of heat transfer in a series of 11 test sections designed to represent a range of configurations seen in production exhaust systems, which is part of a larger activity aimed at the accurate modeling of heat transfer and subsequent catalyst light off in production exhaust systems comprised of similar geometries. These sections include variations in wall thickness, diameter, bend angle and radius. For each section a range of transient and steady state tests were performed on a dynamic test cell using a port injected gasoline engine. In each case a correlation between observed Reynolds number (Re) and Nusselt number (Nu) was developed. A model of the system was implemented in Matlab/Simulink in which each pipe element was split into 25 sub-elements by dividing the pipe into five both axially and radially. The modeling approach was validated using the experimental data.

Market demand for high performance gasoline vehicles and increasingly strict government emissions regulations are driving the development of highly downsized, boosted direct injection engines. The in-cylinder temperatures and pressures of these emerging technologies tend to no longer adhere to the test conditions defining the RON and MON octane rating scales. This divergence between fuel knock rating methods and fuel performance in modern engines has previously led to the development of an engine and operating condition dependent scaling factor, K, which allows for extrapolation of RON and MON values. Downsized, boosted DISI engines have been generally shown to have negative K-values when knock limited, indicating a preference for fuels of higher sensitivity and challenging the relevance of a lower limit to the MON specification.

This paper describes the development and automated calibration of a compact analytically based model of the wall-wetting phenomenon of modern port fuel-injected (PFI) spark-ignition (SI) gasoline engines. The wall-wetting model, based on the physics of forced convection with phase change, is to be used in an automated model-based calibration program. The first stage of work was to develop a model of the wall-wetting phenomenon in Matlab. The model was then calibrated using experimental data collected from a 1.8-litre turbocharged I4 engine coupled to a dynamic 200kW AC dynamometer. The calibration was accomplished by adopting a two stage optimization approach. Firstly, a design of experiments (DoE) approach was used to establish the effect of the principal model parameters on a set of metrics that characterized the magnitude and duration of the measured lambda deviation during a transient.

Noise emitted from the pump can be a major influence on the overall noise created by a power steering system. Dynamic simulation can aid the designer by showing the effect of the pump geometry and oil properties on noise before the prototype has been built. This paper discusses a simulation of suction port flow ripple in a power steering vane pump, which is validated against experimental data. Results show that the mean pressure in the delivery line affects the amplitude of suction port flow ripple. Internal leakage in the pump was found to have little effect on suction port flow ripple. The level of high-frequency flow ripple from the suction port was found to be comparable with or greater than that from the delivery port. The simulation is used to recommend the addition of relief grooves to reduce the high-frequency flow ripple.

As emissions regulations become more stringent, an efficient and effective method of rig-based transient engine calibration becomes increasingly desirable. It is known that approximately 80% of total drive-cycle exhaust emissions can be produced in the initial warm-up phase before catalyst ‘light-off’ is achieved and catalyst conversion efficiency increases. During this period, there is a clear trade-off that can be made in the strategy between the amount of thermal energy that is delivered to the catalyst and the amount of exhaust emissions produced during the time before catalyst ‘light-off’ is achieved. This paper examines whether an automated expert-knowledge based decision-making methodology can be used to find a satisfactory trade-off between these two parameters whilst reducing the iteration time and level of input required from a calibration engineer.

This paper proposes an advanced control strategy to improve vehicle handling and directional stability by integrating either Active Front Steering (AFS) or Active Rear Steering (ARS) with Variable Torque Distribution (VTD) control. Both AFS and ARS serve as the steerability controller and are designed to achieve the improved yaw rate tracking in low to mid-range lateral acceleration using Sliding Mode Control (SMC); while VTD is used as the stability controller and employs differential driving torque between left and right wheels on the same axle to produce a relatively large stabilizing yaw moment when the vehicle states (sideslip angle and its angular velocity) exceed the reference stable region defined in the phase plane. Based on these stand-alone subsystems, an integrated control scheme which coordinates the control actions of both AFS/ARS and VTD is proposed. The functional difference between AFS and ARS when integrated with VTD is explained physically.

The Milner CVT is a patented [1] rolling traction transmission offering advantages of high power density and simplicity of construction and operation. A 90 mm diameter prototype variator is described which was sized for a maximum rated input power of 12 kW. Experimental data are presented demonstrating high efficiency and low shift forces. Resistance to overload torque is shown to be exceptional and preliminary durability trials indicate a highly viable concept for series production. Based upon the measured data, characteristics of larger variators are predicted and prospects for automotive applications discussed.

Electric coolant pumps for IC engines are under development by a number of suppliers. They offer packaging and flexibility benefits to vehicle manufacturers. Their full potential will not be realised, however, unless an integrated approach is taken to the entire cooling system. The paper describes such a system comprising an advanced electric pump with the necessary flow controls and a supervisory strategy running on an automotive microprocessor. The hardware and control strategy are described together with the simulation developed to allow its calibration and validation before fitting in a B/C class European passenger car. Simulation results are presented which show the system to be controllable and responsive to deliver optimum fuel consumption, emissions and driver comfort.

The detailed, dynamic properties of dampers are known to influence substantially some of the subtle - and yet nevertheless hugely important - refinement aspects or ride and handling. Despite this, most of the current work on damping characterization relies on steady-state properties and transient aspects are left largely to subjective in-car assessments by test drivers. The paper describes research work aimed at improving our understanding of the transient properties of dampers through mathematical modeling and then attempting to link these properties to detailed aspects of the vehicle ride and handling. Further experimental work is planned to follow later. From a moderately complex mathematical model of a damper, an attempt is made to identify (a) those transient characteristics which are important in influencing the vehicle responses perceived by test drivers, and (b) which design features of the damper control those characteristics.

In this paper a gearshift controller for twin clutch transmissions is developed. The controller incorporates the control of engine variables to achieve synchronization whilst the transfer of engine torque from clutch to clutch is managed by a clutch slip control. On top of this gearshift controller and as an extension to the basic control scheme a transmission output torque control is included as a means to directly influence shift character and add robustness to the control. The transmission output torque control also provides the foundation for an integrated torque management scheme of powertrain components. Simulation results for upshift and downshift are presented and discussed in the final chapter of this paper.

A number of handling models of a small high performance formula type racing car have been produced. These have been used to optimise the performance of the vehicle whilst under going simple manoeuvres and around a complete race track. Recently the vehicle was fitted with a data acquisition system and objective data was taken of the vehicle's handling performance. The paper details an investigation into the accuracy of two (a simple and more sophisticated) vehicle handling models in predicting the actual vehicle's performance from the data collected by comparing measured and simulated results. The investigation studies the steady state and transient response of the vehicle up to the limit of the vehicle's handling performance. A description is also given of the use of the more sophisticated model in a virtual race track simulation where it is used as a development tool to tune the performance of future vehicles.

This paper presents a method of control for a 6×6 series-configured Hybrid Electric Off-road Vehicle (HEOV). The vehicle concerned is an eight-tonne logistics support vehicle which utilizes Hub Mounted Electric Drives (HMED) at each of its six wheel stations. This set-up allows Individual Wheel Control (IWC) to be implemented to improve vehicle handling and mobility. Direct Yaw-moment Control (DYC) is a method of regulating individual wheel torque to control vehicle yaw motion, providing greater stability in cornering. When combined with both a Traction Control System (TCS) and an Anti-lock Braking System (ABS) the tire/road interaction is fully controlled, leading to improved control over vehicle dynamics, whilst also improving vehicle safety.

The major contribution of this paper is the general description of a complete integrating procedure of autonomous vehicle system. Using Robot Operating System (ROS) as the framework, process from senor integration to path planning and path tracking were performed. Based on an off-road All-Terrain Vehicle, an Extended Kalman filter based autonomous control strategy was developed on the ROS. Both the position estimation and autonomous control were performed on the ROS platform. For the position estimation phase, sensory measurements from GPS, IMU and wheel odometry were acquired and processed on ROS. In accordance with the ROS architecture, separate packages were developed for each sensor to gather and publish corresponding measurements. Furthermore, Extended Kalman filtering was performed to fuse all sensory measurements to achieve an optimizing accuracy.

Motion cueing algorithms can improve the perceived realism of a driving simulator, however, data on the effects on driver performance and simulator sickness remain scarce. Two novel motion cueing algorithms varying in concept and complexity were developed for a limited maneuvering workspace, hexapod/Stuart type motion platform. The RideCue algorithm uses a simple swing motion concept while OverTilt Track algorithm uses optimal pre-positioning to account for maneuver characteristics for coordinating tilt adjustments. An experiment was conducted on the US Army Tank Automotive Research, Development and Engineering Center (TARDEC) Ride Motion Simulator (RMS) platform comparing the two novel motion cueing algorithms to a pre-existing algorithm and a no-motion condition.