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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 work presented here seeks to compare different means of providing scavenging systems for an automotive 2-stroke engine. It follows on from previous work solely investigating uniflow scavenging systems, and aims to provide context for the results discovered there as well as to assess the benefits of a new scavenging system: the reverse-uniflow sleeve-valve. For the study the general performance of the engine was taken to be suitable to power a medium-duty truck, and all of the concepts discussed here were compared in terms of indicated fuel consumption for the same cylinder swept volume using a one-dimensional engine simulation package. In order to investigate the sleeve-valve designs layout drawings and analysis of the Rolls-Royce Crecy-type sleeve had to be undertaken.

A comprehensive general purpose engine simulation model has been successfully developed. This paper reports on an investigation undertaken to compare the accuracy and computational efficiency of four alternative methods for modelling the gas flow and performance in internal combustion engines. The comparison is based on the filling-and-emptying method, the acoustic method, the Lax-Wendroff two-stage difference method and the Harten-Lax-Leer upstream method, using a unified treatment for the boundary conditions. The filling-and-emptying method is the quickest method among these four methods, giving performance predictions with reasonably good accuracy, and is suitable for simulating engines using not highly tuned gas exchange systems. Based on the linearized Euler equations, the acoustic method is capable of describing time-varying pressure distributions along a pipe.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Internal combustion engines are routinely developed using 1D engine simulation tools. A well-known limitation is the accuracy of the turbocharger compressor and turbine sub-models, which rely on hot gas bench-measured maps to characterize performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a preprocessing algorithm interpolates and extrapolates the data to generate a wider, more densely populated map. Methods used for compressor map interpolation vary. They may be mathematical or physical in nature, but there is no unified approach, except that they typically operate on input map data in SAE format. For decades it has been common practice for turbocharger suppliers to share performance data with engine OEMs in this form. This paper describes a compressor map interpolation technique based on the nondimensional compressor flow and loading coefficients, instead of SAE-format data.

A new hydraulic cam follower with variable valve timing (VVT) properties is described. Experimental results show that the point of closure of the valve may be delayed as a linear function of engine speed without external control. No other parameter of the valve event is modified by the device. An obvious application is the control of intake valve timing for engines with a wide speed range, where the point of valve closure could be scheduled with engine speed in order to maximise the trapped mass, hence improving the torque curve at low and high speeds. The device is considered for application to the Ford 2.5 litre DI diesel engine, where it may be used to retard inlet valve closure from close to bottom dead centre (BDC) at cranking speed to 50-60 deg after BDC at rated speed.

In both the marine and power industries there are now a choice of off-the-shelf condition monitoring systems available that utilise artificial intelligence techniques to analyse engine performance data. These systems are proving to be a valuable aid in optimising performance and reducing down-time by assisting with maintenance planning. These systems rely on careful monitoring of an engine's performance, for instance engine speed, fuelling, boost pressure, turbine inlet pressure, turbocharger speed, and exhaust temperature. With this data, they utilise a variety of interpolation and pattern recognition algorithms to compare it with previously recorded data stored in lookup tables. This paper describes how a neural network approach can be used as a cheap alternative for the analysis of this data, greatly reducing the need for such large lookup tables and complex pattern recognition programs.

Throttling loss of downsized gasoline engines is significantly smaller than that of naturally aspirated counterparts. However, even the extremely downsized gasoline engine can still suffer a relatively large throttling loss when operating under part load conditions. Various de-throttling concepts have been proposed recently, such as using a FGT or VGT turbine on the intake as a de-throttling mechanism or applying valve throttling to control the charge airflow. Although they all can adjust the mass air flow without a throttle in regular use, an extra component or complicated control strategies have to be adopted. This paper will, for the first time, propose a de-throttling concept in a twin-charged gasoline engine with minimum modification of the existing system. The research engine model which this paper is based on is a 60% downsized 2.0L four cylinder gasoline demonstrator engine with both a supercharger and turbocharger on the intake.

Engines equipped with pressure charging systems are more prone to knock partly due the increased intake temperature. Meanwhile, turbocharged engines when operating at high engine speeds and loads cannot fully utilize the exhaust energy as the wastegate is opened to prevent overboost. The turboexpansion concept thus is conceived to reduce the intake temperature by utilizing some otherwise unexploited exhaust energy. This concept can be applied to any turbocharged engines equipped with both a compressor and a turbine-like expander on the intake loop. The turbocharging system is designed to achieve maximum utilization of the exhaust energy, from which the intake charge is over-boosted. After the intercooler, the turbine-like expander expands the over-compressed intake charge to the required plenum pressure and reduces its temperature whilst recovering some energy through the connection to the crankshaft.

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.

A range extended electric vehicle (REEV) has the benefit of zero pipeline emission for most of the daily commute driving using the full electric mode while maintaining the capability for a long-range trip without the requirement of stop-and-charge. This capability is provided by the on-board auxiliary power unit (APU) which is used to maintain the battery state of charge at a minimum limit. Due to the limited APU package size, a small capacity engine with low-cylindercount is normally used which inherently exposes more severe torque pulsation, that arises from a low firing frequency. By using vector control, it is feasible to vary the generator in-cycle torque to counteract the engine torque oscillation dynamically. This allows for a smoother operation of the APU with the possibility of reducing the size of the engine flywheel. In this paper, a series of motor/generator control torque patterns were applied with the aim of cancelling the engine in-cycle torque pulses.

The octane appetite of an SI engine can be expressed in terms of an Octane Index: OI = (1−K) RON + K MON where K is a constant for a given operating condition and depends only on the pressure and temperature variation in the engine (it is not a property of the fuel). Experimental measurements of K values can be costly and time consuming. This paper reports the development of a new K-value simulation method that can be applied to any spark ignition engine given basic engine data. Good agreement between simulation and experimental results suggests the method is reliable and can be applied to a wide range of engines.

Turbocharging has become the favored approach for downsizing internal combustion engines to reduce fuel consumption and CO2 emissions, without sacrificing performance. Matching a turbocharger to an engine requires a balance of various design variables in order to meet the desired performance. Once an initial selection of potential compressor and turbine options is made, corresponding performance maps are evaluated in 1D engine cycle simulations to down-select the best combination. This is the conventional matching procedure used in industry and is ‘passive’ since it relies on measured maps, thus only existing designs may be evaluated. In other words, turbine characteristics cannot be changed during matching so as to explore the effect of design adjustments. Instead, this paper presents an ‘adaptive’ matching methodology for the turbocharger turbine.

The present work investigates the effect of low levels CO2 addition on the combustion characteristics inside a single cylinder optical engine operated under low load conditions. The effects of dilution levels (up to 7.5% mass flow rate CO2 addition), the number of pilot injections (single or double pilot injections) and injection pressure (25 or 40 MPa), are evaluated towards the direction of achieving a partially premixed combustion (PPC) operation mode. The findings are discussed based on optical measurements and via pressure trace and apparent rate of heat release analyses in a Ricardo Hydra optical light duty diesel engine. The engine was operated under low IMEP levels of the order of 1.6 bar at 1200 rpm and with a CO2 diluent-enhanced atmosphere resembling an environment of simulated low exhaust gas recirculation (EGR) rates. Flame propagation is captured by means of high speed imaging and OH, CH and C2 line-of-sight chemiluminescence respectively.

The paper presents results from a study into the potential of a complex cycle gas turbine engine, originally investigated by the Ford Motor Company for truck applications in the 1960s, and updated to gauge the possible improvements by raising the efficiencies of its constituent components from the values used in period to more modern levels. To perform this investigation, firstly a spreadsheet model was constructed and the data that Ford made available in the open literature were used to validate it. The methodology used in the model was to balance the power consumed by the compressors (and the auxiliaries where applicable) with that produced by their driving turbines, and to match the thermal power in the heat exchangers with the data provided. Using the quoted lower heating value of the diesel fuel originally used, this approach led to an accuracy in the match of brake specific fuel consumption (in terms of g/kWh) to three places of decimals.

In recent years, there has been an impetus in the automotive industry to develop newer diesel injection systems with a view to reducing fuel consumption and emissions. This development has led to hardware capable of higher pressures, typically up to 2500 bar. An increase in pressure will result in a corresponding increase in fuel temperature after compression with studies showing changes in fuel temperatures of up to 150 °C in 1000-2500 bar injection systems. Until recently, the addition of Fatty Acid Methyl Esters, FAME, to diesel had been blamed for a number of fuel system durability issues such as injector deposits and fuel filter blocking. Despite a growing acceptance within the automotive and petrochemical industries that FAME is not solely to blame for diesel instability, there is a lack of published literature in the area, with many studies still focusing on FAME oxidation to explain deposit formation and hardware durability.

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.

Vehicle start-stop systems are becoming increasingly prevalent on internal combustion engine (ICE) because of the capability to reduce emissions and fuel consumption in a cost effective manner. Thus, the ICE undergoes far more starting events, therefore, the behaviour of ICE during start-up becomes critical. In order to simulate and optimise the engine start, Model in the Loop (MiL) simulation approach was selected. A proceduralised cranking test has been carried out on a 2.0-liter turbocharged, gasoline direct injection (GDI) engine to collect data. The engine behaviour in the first 15 seconds was split into eight different phases and studied. The engine controller and the combustion system were highly transient and interactive. Thus, a controller model that can set accurate boundary conditions is needed. The relevant control functions of throttle opening and spark timing have been implemented in Matlab/Simulink to simulate the behaviours of the controller.

This study measures, during various transients of speed and load, in-cylinder-, intake-/exhaust- (manifold) pressures and engine torque. The tests were conducted on a typical high power-density, passenger car powertrain (common-rail diesel engine, of in-line 4-cylinder configuration equipped with a Variable Geometry Turbocharger). The objective was to quantify the deterioration (relative to a steady-steady condition) in transient Specific Fuel Consumption (SFC) that may occur during lagged-boost closed-loop control and thus propose an engine control strategy that minimises the transient SFC deterioration. The results, from transient characterisation and the analysis method applied in this study, indicate that transient SFC can deteriorate up to 30% (function of load transient) and is primarily caused by excessive engine pumping-loss.

Recent legislation banning the sale of new petrol and diesel vehicles in Europe from 2035 has shifted the focus of internal combustion engine research towards alternative fuels with net zero tailpipe emissions such as hydrogen. Research regarding hydrogen as a fuel is particularly pertinent to the so-called ‘hard-to-electrify’ propulsion applications, requiring a combination of large range, fast refuelling times or high-load duty cycles. The virtual design, development, and optimisation of hydrogen internal combustion engines has resulted in the necessity for accurate predictive modelling of the hydrogen combustion and autoignition processes. Typically, the models for these processes rely respectively on laminar flame speed datasets to calculate the rate of fuel burn as well as ignition delay time datasets to estimate autoignition timing. These datasets are generated using chemical kinetic mechanisms available in the literature.