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Low speed pre-ignition (LSPI) is a limiting phenomenon for several of the technologies being pursued as part of the low carbon agenda. To achieve maximum power density and efficiency engines are being downsized and turbocharged, while Direct- injection technologies are becoming ever more prominent. All changes that increase the propensity of LSPI. The low speed-high load operation envelope is limited due to LSPI. Hydrogen engines are also being explored, however, with such a low minimum enthalpy of ignition, LSPI is a major limitation to thermal efficiency. Several techniques are utilized in this study to investigate physical and physio-chemical aspects of lubricant initiated LSPI. Where possible attempts have been to validate methodologies or directional alignment with published data. The basis of the methodologies used is a validated 1D predictive combustion model of a single cylinder GTDI engine, that was used to provide simulation boundary conditions.

Low temperature combustion (LTC) of diesel fuel offers a path to low engine emissions of nitrogen oxides (NOx) and particulate matter (PM), especially at low loads. Borescopic optical imaging offers insight into key aspects of the combustion process without significantly disrupting the engine geometry. To assess LTC combustion, two-colour pyrometry can be used to quantify local temperatures and soot concentrations (KL factor). High sensitivity photo-multiplier tubes (PMTs) can resolve natural luminosity down to low temperatures with adequate signal-to-noise ratios. In this work the authors present the calibration and implementation of a borescope-based system for evaluating low luminosity LTC using spatially resolved visible flame imaging and high-sensitivity PMT data to quantify the luminous-area average temperature and soot concentration for temperatures from 1350-2600 K.

Injection pressure oscillations are proven to determine considerable deviations from the expected mass flow rate, leading to the jet velocities non-uniformity, which in turn implies the uneven spatial distribution of A/F ratio. Furthermore, once the injector is triggered, these oscillations might lead the rail pressure to experience a decreasing stage, to the detriment of spray penetration length, radial propagation and jet break-up timing. This has urged the research community to develop models predicting injection-induced pressure fluctuations within the rail. Additionally, several devices have been designed to minimize and eliminate such fluctuations. However, despite the wide literature dealing with the injection-induced pressure oscillations, many aspects remain still unclear. Moreover, the compulsory compliance with environmental regulations has shifted focus onto alternative fuels, which represent a promising pathway for sustainable vehicle mobility.

Gasoline Direct Injection (GDI) vehicles now make up the majority of European new car sales and a significant share of the existing car parc. Despite delivering measurable engine efficiency benefits, GDI fuel systems are not without issues. Fuel injectors are susceptible to the formation of deposits in and around the injector nozzles holes. It is widely reported that these deposits can affect engine performance and that different fuels can alleviate the buildup of those deposits. This project aims to understand the underlying mechanisms of how deposit formation ultimately leads to a reduction in vehicle performance. Ten GDI fuel injectors, with differing levels of coking were taken from engine testing and consumer vehicles and compared using a range of imaging and engine tests. At the time of writing, a new GDI engine test is being developed by the Co-ordinating European Council (CEC) to be used by the fuel and fuel additive industry.

Full hybrid electric vehicles are usually defined by their capability to drive in a fully electric mode, offering the advantage that they do not produce any emissions at the point of use. This is particularly important in built up areas, where localized emissions in the form of NOx and particulate matter may worsen health issues such as respiratory disease. However, high degrees of electrification also mean that waste heat from the internal combustion engine is often not available for heating the cabin and for maintaining the temperature of the powertrain and emissions control system. If not managed properly, this can result in increased fuel consumption, exhaust emissions, and reduced electric-only range at moderately high or low ambient temperatures negating many of the benefits of the electrification. This paper describes the development of a holistic, modular vehicle model designed for development of an integrated thermal energy management strategy.

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.

Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.

A significant amount of harmful emissions pass unreacted through catalytic after-treatment devices for IC engines before the light-off temperature is reached, despite the high conversion efficiency of these systems in fully warm conditions. Further tightening of fleet targets and worldwide emission regulations will make a faster catalyst light-off to meet legislated standards hence reduce the impact of road transport on air quality even more critical. This work investigates the effect of adding hydrogen (H2) at levels up to 2500 ppm into the exhaust gases produced by combustion of various oxygenated C2-, C4- and renewable fuel molecules blended at 20 % wt/wt with gasoline on the light-off performance of a commercially available three-way catalyst (TWC) (0.61 L, Pd/Rh/Pt - 19/5/1, 15g). The study was conducted on a modified naturally aspirated, 1.4 L, four-cylinder, direct-injected, spark-ignition engine.

The process of engine mapping in the automotive industry identifies steady-state engine responses by running an engine at a given operating point (speed and load) until its output has settled. While the time simulating this process with a computational model for one set of parameters is relatively short, the cumulative time to map all possible combinations becomes computationally inefficient. This work presents an alternative method for mapping out the steady-state response of an engine in simulation by applying bifurcation theory. The bifurcation approach used in this work allows the engine’s steady-state response to be traced through the model’s state-parameter space under the simultaneous variation of one or more model parameters. To demonstrate this approach, a bifurcation analysis of a simplified nonlinear engine model is presented.

Many modern I.C. engines rely on some form of active control of injection, timing and/or ignition timing to help combat tailpipe out emissions, increase the fuel economy and improve engine drivability. However, development of these strategies is often optimised to suit the average cycle at each condition; an assumption that can lead to sub-optimal performance, especially an increase in particulate (PN) emissions as I.C. engine operation, and in-particular its charge motion is subject to cycle-to-cycle variation (CCV). Literature shows that the locations of otherwise repeatable large-scale flow structures may vary by as much 25% of the bore dimension; this could have an impact on fuel break-up and distribution and therefore subsequent combustion performance and emissions.

In-cylinder temperatures and their cyclic variations strongly influence many aspects of internal combustion engine operation, from chemical reaction rates determining the production of NOx and particulate matter to the tendency for auto-ignition leading to knock in spark ignition engines. Spatially resolved measurements of temperature can provide insights into such processes and enable validation of Computational Fluid Dynamics simulations used to model engine performance and guide engine design. This work uses a combination of Two-Colour Planar Laser Induced Fluorescence (TC-PLIF) and Laser Induced Grating Spectroscopy (LIGS) to measure the in-cylinder temperature distributions of a firing optically accessible spark ignition engine. TC-PLIF performs 2-D temperature measurements using fluorescence emission in two different wavelength bands but requires calibration under conditions of known temperature, pressure and composition.

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and non-minimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited.

The demand for more efficient and clean engines have prompted the research and development of new engine technologies. Automotive engines expected to run with leaner mixtures and higher compression ratios. Lean burn is effective to increase fuel economy whilst reducing emissions but unreliable ignition of the lean mixtures by the conventional spark plug is one of the problems which causes concerns to the engine designers. Laser ignition is a promising technology and holds many benefits over the spark ignition because it can extend the ignitability of lean mixtures with flexibility of the ignition location and absence of electrode degradation for improved engine performance with lean burn. In this study, high-speed photography is used to investigate the flame kernel growth and propagation in an optical direct injection engine using laser ignition by an Nd:YAG laser.

The conversion of lignocellulosic biomass to liquid fuels presents an alternative to the current production of renewable fuels for IC engines from food crops. However, realising the potential for reductions in net CO2 emissions through the utilisation of, for example, waste biomass for sustainable fuel production requires that energy and resource inputs into such processes be minimised. This work therefore investigates the combustion and emission characteristics of five intermediate platform molecules potentially derived from lignocellulosic biomass: gamma-valerolactone (GVL), methyl valerate, furfuryl alcohol, furfural and 2-methyltetrahydrofuran (MTHF). The study was conducted on a naturally aspirated, water cooled, single cylinder spark-ignition engine. Each of the platform molecules were blended with reference fossil gasoline at 20 % wt/wt.

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.

The deactivation of one or more cylinders in internal combustion engines has long been established in literature as a means of reducing engine pumping losses and thereby improving brake specific fuel consumption. As down-sizing and down-speeding of modern engines becomes more extreme, drivability issues associated with mode transition become more acute and need to be managed within a suitable calibration framework. This paper presents methodology by which a calibration may be deduced for optimal mode-transitioning in respect of minimising the torque disturbance as cylinders are deactivated and re-activated. At the outset of this study a physics based engine model is used to investigate the key parameters that influence the transition. Having understood these, experiments are designed to establish the level of mode transition disturbance using quantitative statistical indicators such that the cost function may be defined and an optimisation undertaken.

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as the promising solution in engine downsizing. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The electrified turbocharger consists of a variable geometry turbocharger (VGT) and an electric motor (EM) within the turbocharger bearing housing, where the EM is capable in bi-directional power transfer. The VGT, EM, and exhaust gas recirculation (EGR) valve all impact the dynamics of air path. In this paper, the dynamics in an electrified turbocharged diesel engine (ETDE), especially the couplings between different loops in the air path is analyzed. Furthermore, an explicit principle in selecting control variables is proposed. Based on the analysis, a model-based multi-input multi-output (MIMO) decoupling controller is designed to regulate the air path dynamics.

With increasingly stringent requirements and regulations related to particulate matter(PM) emissions, manufacturers are paying more and more attention to emissions from gasoline direct injection(GDI) engines. The present paper proposes an improved two-step soot model. The model is applied in the Kiva-Chemkin program to simulate the processes of spray impinging, fuel mixture preparation, combustion and soot formation in a typical turbocharged downsized GDI engine. The simulation results show that soot formation in the GDI engine is attributed to non-uniform distribution of the air-fuel mixture and pool fire of wall film in the cylinder. Under homogeneous mode, increasing the injection advance angle can optimize fuel atomization and improve air-fuel mixing, thus reducing soot formation. However, an excessive injection advance angle may cause spray to impinge on the cylinder wall and this will sharply increase the soot emission.

Particle Number (PN) have already been a big issue for developing high efficiency internal combustion engines (ICEs). In this study, controlled spark-assisted stratified compression ignition (SSCI) with moderate end-gas auto-ignition was used for reducing PN in a high compression ratio gasoline direct injection (GDI) engine. Under wide open throttle (WOT) and Maximum Brake Torque timing (MBT) condition, high external cooled exhaust gas recirculation (EGR) was filled in the cylinder, while two-stage direct injection was used to form desired stoichiometric but stratified mixture. SSCI combustion mode exhibits two-stage heat release, where the first stage is associated with flame propagation induced by spark ignition and the second stage is the result of moderate end-gas auto-ignition without pressure oscillation at the middle or late stage of the combustion process.

Two identical commercial Thermo-Electric Modules (TEMs) were assembled on a plate type heat exchanger to form a Thermoelectric Generator (TEG) unit in this study. This unit was tested on the Exhaust Gas Recirculation (EGR) flow path of a test engine. The data collected from the test was used to develop and validate a steady state, zero dimensional numerical model of the TEG. Using this model and the EGR path flow conditions from a 30% torque Non-Road Transient Cycle (NRTC) engine test, an optimization of the number of TEM units in this TEG device was conducted. The reduction in fuel consumption during the transient test cycle was estimated based on the engine instantaneous Brake Specific Fuel Consumption (BSFC). The perfect conversion of TEG recovered electrical energy to engine shaft mechanical energy was assumed. Simulations were performed for a single TEG unit (i.e. 2 TEMs) to up to 50 TEG units (i.e. 100 TEMs).