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Fuel efficiency and torque performance are two major challenges for highly downsized turbocharged engines. However, the inherent characteristics of the turbocharged SI engine such as negative PMEP, knock sensitivity and poor transient performance significantly limit its maximum potential. Conventional ways of improving the problems above normally concentrate solely on the engine side or turbocharger side leaving the exhaust manifold in between ignored. This paper investigates this neglected area by highlighting a novel means of gas exchange process. Divided Exhaust Period (DEP) is an alternative way of accomplishing the gas exchange process in turbocharged engines. The DEP concept engine features two exhaust valves but with separated function. The blow-down valve acts like a traditional turbocharged exhaust valve to evacuate the first portion of the exhaust gas to the turbine.

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.

The present work investigates a means of controlling engine hydrocarbon startup and shutdown emissions in a Wankel engine which uses a novel rotor cooling method. Mechanically the engine employs a self-pressurizing air-cooled rotor system (SPARCS) configured to provide improved cooling versus a simple air-cooled rotor arrangement. The novelty of the SPARCS system is that it uses the fact that blowby past the sealing grid is inevitable in a Wankel engine as a means of increasing the density of the medium used for cooling the rotor. Unfortunately, the design also means that when the engine is shutdown, due to the overpressure within the engine core and the fact that fuel vapour and lubricating oil are to be found within it, unburned hydrocarbons can leak into the combustion chambers, and thence to the atmosphere via either or both of the intake and exhaust ports.

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.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

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.

Precise, repeatable and representative testing is a key tool for developing and demonstrating automotive fuel and lubricant products. This paper reports on the first findings of a project that aims to determine the requirements for highly repeatable test methods to measure very small differences in fuel economy and powertrain performance. This will be underpinned by identifying and quantifying the variations inherent to this specific test vehicle, both on-road and on Chassis Dynamometer (CD), that create a barrier to improved testing methods. In this initial work, a comparison was made between on-road driving, the New European Drive Cycle (NEDC) and World harmonized Light-duty Test Cycle (WLTC) cycles to understand the behavior of various vehicle systems along with the discrepancies that can arise owing to the particular conditions of the standard test cycles.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

The octane appetite of an engine is frequently characterised by the so-called K value. It is usually assumed that K is dependent only on the thermodynamic conditions in the engine when knock occurs. In this work we test this hypothesis: further analysis was conducted on experimental results from SAE 2019-01-0035 in which a matrix of fuels was tested in a single cylinder engine. The fuels consisted of a relatively small number of components, thereby simplifying the analysis of the chemical kinetic proprieties. Through dividing the original fuel matrix into subsets, it was possible to explore the variation of K value with fuel properties. It was found that K value tends to increase slightly with RON. The explanation for this finding is that higher RON leads to advanced ignition timing (i.e. closer to MBT conditions) and advanced ignition timing results in faster combustion because of the higher pressures and temperatures reached in the thermodynamic trajectory.

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.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

To meet LEV and EU Stage III emission requirements, it is necessary for new catalytic converters to be designed which exceed light-off temperature as quickly as possible. The technical solutions are secondary air injection, active heating systems such as the electrically heated catalytic converter, and the close coupled catalytic converter. Engine control functions are extensively used to heat the converter and will to play a significant role in the future. The concept of relocating the converter to a position close to the engine in an existing vehicle involves new conflicts. Examples include the space requirements, the thermal resistance of the catalytic coating and high temperature loads in the engine compartment.

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.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

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.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.