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The work examined the practicality of converting a modern production 6 cylinder 7.7 litre heavy-duty diesel engine for flex dual-fuel operation with ammonia as the main fuel. A small amount of diesel fuel (pilot) was used as an ignition source. Ammonia was injected into the intake ports during the intake stroke, while the original direct fuel injection equipment was retained and used for pilot diesel injection. A bespoke engine control unit was used to control the injection of both fuels and all other engine parameters. The aim was to provide a cost-effective retrofitting technology for existing heavy-duty engines, to enable eco-friendly operation with minimal carbon emissions. The tests were carried out at a baseline speed of 600 rpm for the load range of the engine (10-90%), with minimum pilot diesel quantity and as high as 90% substitution ratio of ammonia for diesel fuel.

Ammonia (NH3) is emerging as a potential fuel for longer range decarbonised heavy transport, predominantly due to favourable characteristics as an effective hydrogen carrier. This is despite generally unfavourable combustion and toxicity attributes, restricting end use to applications where robust health and safety protocols can always be upheld. In the currently reported work, a spark ignited thermodynamic single cylinder research engine was upgraded to include gaseous ammonia and hydrogen port injection fueling, with the aim of understanding maximum viable ammonia substitution ratios across the speed-load operating map. The work was conducted under stoichiometric conditions with the spark timing re-optimised for maximum brake torque at all stable logged sites. The experiments included industry standard measurements of combustion, performance and engine-out emissions.

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.

This paper presents a method for analysing the characteristics of nano-scale particles emitted from a 1.6 Litre, 4-stroke, gasoline direct injection (GDI) and turbocharged spark ignition engine fitted with a three-way catalytic converter. Ensemble Empirical Mode Decomposition (EEMD) is employed in this work to decompose the nano-scale particle size spectrums obtained using a differential mobility spectrometer (DMS) into Intrinsic Mode Functions (IMF). Fast Fourier Transform (FFT) is then applied to each IMF to compute its frequency content. The results show a strong correlation between the IMFs of specific particle ranges and the IMFs of the total particle count at various speed and load operating conditions. Hence, it is possible to characterise the influence of specific nano-scale particle ranges on the total particulate matter signal by analysing the frequency components of its IMFs using the EEMD-FFT method.

Formula (1) vehicles have transitioned from E5 to E10 fuel for the 2022 season to reduce carbon emissions and by 2026 the vehicles are required to use 100% sustainable fuels. The aim of this paper is to identify the operating envelope of the F1 power unit for E10-E100 fuel and the resulting emission levels for these fuel compositions using numerical simulations. To achieve this aim an F1 engine model has been developed in GT-Suite with reference to the FIA 2022 Technical Regulations. The combustion model has been validated using data obtained from literature relating to laminar and turbulent flame speed, friction and heat transfer characteristics within the combustion chamber. One of the main challenges of using ethanol-based fuels is the increased levels of formaldehyde in the tailpipe.

Internal combustion (IC) engines are the most common power unit technology found in road vehicles. The process of combustion within IC engines is linked to the output torque and overall powertrain performance. This work presents a method of analysing the parameters of cylinder pressure and crankshaft instantaneous speed signals obtained from a turbocharged, 4-stroke, 4-cylinder, 1.6 Litre, spark ignition, gasoline direct injection engine at various speed and load operating conditions. Whereas cepstrum analysis is used in the present work to extract critical features characterising the combustion process. Cepstrum analysis showed that the location of maximum heat release can be directly obtained from the quefrency of the instantaneous crank speed. This paper presents a systematic scheme for applying cepstrum for obtaining combustion features from the instantaneous crank speed signal.

With ever stricter legislative requirements for CO2 and other exhaust emissions, significant efforts by OEMs have launched a number of different technological strategies to meet these challenges such as Battery Electric Vehicles (BEVs). However, a multiple technology approach is needed to deliver a broad portfolio of products as battery costs and supply constraints are considerable concerns hindering mass uptake of BEVs. Therefore, further investment in Internal Combustion (IC) engine technologies to meet these targets are being considered, such as lean burn gasoline technologies alongside other high efficiency concepts such as dedicated hybrid engines. Hence, it becomes of sound reason to further embrace diversity and develop complementary technologies to assist in the transition to the next generation hybrid powertrain. One such approach is to provide increased valvetrain flexibility to afford new degrees of freedom in engine operating strategies.

Internal combustion (IC) engines are the current dominant power source used in the automotive industry for hybrid vehicles. The combustion process of IC engines involves various parameters, which are linked to the overall performance of the driveline. Therefore, finding the frequency coupling between the manifold pressure, in-cylinder pressure and output crankshaft speed will provide an insight into the reasons for torque fluctuations and its effect on driveline performance. The present work introduces a methodology to analyze cylinder pressure, manifold pressure and instantaneous crank speed signals measured from a 4 cylinder, 1.6 Litre, Gasoline Direct Injection Engine at different speed conditions to identify the frequency coupling between these signals. This work uses Ensemble Empirical Mode Decomposition (EEMD) as a de-noising method and Bispectral analysis for examining the presence of a frequency coupling from the signals.

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.

A novel surrogate model is presented, which predicts the engine-out Particle Number (PN) emissions of a light-duty, spray-guided, turbo-charged, GDI engine. The model is developed through extensive CFD analysis, carried out using the Siemens Simcenter STAR-CD, and considers a range of part-load operating conditions and single-variable sweeps where control parameters such as start of injection and injection pressure are varied in isolation. The work is attached to the Ford-led APC6 DYNAMO project, which aims to improve efficiency and reduce harmful emissions from the next generation of gasoline engines. The CFD work focused on the air exchange, fuel spray and mixture preparation stages of the engine cycle. A combined Rosin-Rammler and Reitz-Diwakar model, calibrated over a wide range of injection pressure, is used to model fuel atomization and secondary droplets break-up.

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.

Through improving the 48V hybrid vehicle archetype, governmental emission targets could be more easily met without incurring the high costs associated with increasing levels of electrification. The braking energy recovery function of hybrid vehicles is recognised as an effective solution to reduce emissions and fuel consumption in the short to medium term. The aim of this study was to evaluate methods to maximise the braking energy recovery capability of the 48V hybrid electric vehicle over pre-selected drive cycles using appropriately sized electrified components. The strategy adopted was based upon optimising the battery chemistry type via specific power capability, so that overall brake power is equal to the maximum battery charging power in a typical medium-sized passenger car under typical driving. This will maximise the regenerative braking energy whilst providing a larger torque assistance for a lower battery capacity.

The aim of the present work is to propose a control strategy for maximizing the performance of a Formula One (F1) car through numerical simulation for 2021 regulations taking 2019 regulations as a benchmark. This study has developed an engine-powertrain model of an F1 car with real world driver data for estimating the vehicle’s full throttle performance. The maximum possible energy recovered, stored and deployed by the Energy Recovery System (ERS) was estimated for the first 10 circuits in the 2019 FIA Formula One World Championship® Race Calendar. A 1.6L V6 Internal Combustion Engine (ICE), as well as, a full vehicle was modelled according to the 2019 Federation Internationale de l'Automobile (FIA) Formula One technical regulations using GT-Suite software. The model was validated against the experimental data. The data for validation was extracted from On- Board videos using Optical Character Recognition (OCR) and FIA regulations.

Reducing emissions from light duty vehicles is critical to meet current and future air quality targets. With more focus on real world emissions from light-duty vehicles, the interactions between engine and exhaust gas aftertreatment are critical. For modern engines, most emissions are generated during the warm-up phase following a cold start. For Diesel engines this is exaggerated due to colder exhaust temperatures and larger aftertreatment systems. The De-NOx aftertreatment can be particularly problematic. Engine manufacturers are required to take measures to address these temperature issues which often result in higher fuel consumption (retarding combustion, increasing engine load or reducing the Diesel air-fuel ratio). In this paper we consider an inner-insulated turbocharger as an alternative, passive technology which aims to reduce the exhaust heat losses between the engine and the aftertreatment. Firstly, the concept and design of the inner-insulated turbocharger is presented.

Characterization of soot nanoparticle morphology can be used to develop understanding of nanoparticle interaction with engine lubricant oil and its additives. It can be used to help direct modelling of soot-induced thickening, and in a more general sense for combatting reductions in engine efficiency that occur with soot-laden oils. Traditional 2D transmission electron microscopy (TEM) characterization possesses several important shortcomings related to accuracy that have prompted development of an alternative 3D characterization technique utilizing electron tomography, known as 3D-TEM. This work details progress made towards facilitating semi-automated image acquisition and processing for location of structures of interest on the TEM grid. Samples were taken from a four cylinder 1.4 L gasoline turbocharged direct injection (GTDI) engine operated in typically extra-urban driving conditions for 20,284 km, with automatic cylinder deactivation enabled.

Formation of soot is a known phenomenon for diesel engines, however, only recently emerged for gasoline engines with the introduction of direct injection systems. Soot-in-oil samples from a three-cylinder turbocharged gasoline direct injection (GDI) engine have been analysed. The samples were collected from the oil sump after periods of use in predominantly urban driving conditions with start-stop mode activated. Thermogravimetric analysis (TGA) was performed to measure the soot content in the drained oils. Soot deposition rates were similar to previously reported rates for diesel engines, i.e. 1 wt% per 15,000 km, thus indicating a similar importance. Morphology was assessed by transmission electron microscopy (TEM). Images showed fractal agglomerates comprising multiple primary particles with characteristic core-shell nanostructure. Furthermore, large amorphous structures were observed. Primary particle sizes ranged from 12 to 55 nm, with a mean diameter of 30 nm and mode at 31 nm.

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.

Demonstrating the cost/benefits of technologies in the automotive sector is becoming very challenging because the benefits from technologies are sometimes of similar magnitude to testing precision. This paper aims to understand vehicle-borne imprecision and the effect of this on the quality of chassis dynamometer (CD) testing. Fuel consumption and NOx emissions precision is analyzed for two diesel vehicles with particulate filter and SCR systems. The two vehicles were tested on a high precision CD facility over the NEDC (New European Drive Cycle) and WLTC (World harmonized Light-duty Test Cycle) cycles. The CD base precision of testing was characterized between 0.6-3% depending on the cycle phase. A novel application of multi-variate statistical analysis was used to identify the factors that affected testing precision, allowing isolation of small differences that were not obvious when conducting cycle-averaged or cycle-phase-averaged analysis.

The thermal management of a Formula 1 car is a challenging task as it involves multiple components, systems and multiple sources of thermal energy. The present work attempts to model a representative F1 car following 2018 F1 regulations directly linked to the cooling systems requirements and performance. The main purpose of this work is to simulate the steady and transient behaviour of the cooling system when the vehicle is in a qualifying lap, and during the entire race, including the wait in the starting grid and the pit stops. This model includes the sub-models representing internal combustion engine, hybrid powertrain, vehicle, driver and an appropriate cooling system composed of radiators, pumps and expansion tanks. This work validates the cooling system of a representative 2018 F1 car for the Silverstone Circuit. This model is capable of simulating the overall thermal performance of the F1 car for sizing the cooling system for most of the F1 circuits.

A physics based, lumped thermal capacity model of a 1litre, 3 cylinder, turbocharged, directly injected spark ignition engine has been developed to investigate the effects of cylinder deactivation on the thermal behaviour and fuel economy of small capacity, 3 cylinder engines. When one is deactivated, the output of the two firing cylinders is increased by 50%. The largest temperature differences resulting from this are between exhaust ports and between the upper parts of liners of the deactivated cylinder and the adjacent firing cylinder. These differences increase with load. The deactivated cylinder liner cools to near-coolant temperature. Temperatures in the lower engine structure show little response to deactivation. Temperature response times following deactivation or reactivation events are similar. Motoring work for the deactivated cylinder is a minor loss; the net benefit of deactivation diminishes with increasing load.