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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.

The increased severity and prevalence of insoluble deposits formed on fuel injectors in gasoline direct injection (GDI) engines precipitates negative environmental, economic and healthcare impacts. A necessary step in mitigating deposits is to unravel the molecular compositions of these complex layered materials. But very little molecular data has been acquired. Mass spectrometry shows promise but most techniques require the use of solvents, making them unsuited for analyzing insoluble deposits. Here, we apply the high mass-resolving power and in-situ analysis capabilities of 3D OrbitrapTM secondary ion mass spectrometry (3D OrbiSIMS) to characterize deposits formed on the external tip and internal needle from a GDI injector. This is the first application of the technique to study internal GDI deposits. Polycyclic aromatic hydrocarbons (PAHs) are present up to higher maximum masses in the external deposit.

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.

Engine research has increasingly focused on emission of sub 23 nm particulates in recent years. Likewise, current legislative efforts are being made for particulate number (PN) emission limits to include this previously omitted size range. In Europe, PN measurement equipment and procedures for regulatory purposes are defined by the particle measurement programme (PMP). Latest regulation drafts for sub 23 nm measurements specify counting efficiencies with a 65% cut-off size at 10 nm (d65) and a minimum of 90% above 15 nm (d90). Even though alternative instruments, such as differential mobility spectrometers (DMS), are widely used in laboratory environments, the interpretation of their sub 23 nm measurements has not yet been widely discussed. For this study, particulate emissions of a 1.0L gasoline direct injection (GDI) engine have been measured with a DMS system for low to medium speeds with two load steps.

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 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.

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.

The gradual push towards electric vehicles (EV) as a primary mode of transport has resulted in an increased focus on electric and hybrid powertrain research. One answer to the consumers’ concern over EV range is the implementation of small combustion engines as generators to supplement the energy stored in the vehicle battery. Since these range extender generators have the opportunity to run in a small operating window, some engine types that have historically struggled in an automotive setting have the potential to be competitive. The relative merits of two different engine options for range extended electric vehicles are simulated in vehicle across the WLTP drive cycle. The baseline electric vehicle chosen was the BMW i3 owing to its availability as an EV with and without a range extender gasoline engine.

Wankel rotary engines are becoming an increasingly popular area of research with regard to their use as a range extender in the next generation of Hybrid Electric Vehicle (HEV). Due to their simple design, lightness, compactness and very favourable power-to-weight ratio, they represent one of the best alternative solutions to classic reciprocating piston engines. On the other hand, current Wankel engines still need improvements in terms of specific fuel consumption and emissions. This paper describes an innovative approach for the assessment of the performance of a modern rotary engine. All the experimental activities will be carried out within the Innovate UK funded ADAPT Intelligent Powertrain project led by Westfield Sportscars Limited.

The solid state power controller (SSPC) is one of the most important power electronic components of the aircraft electrical power distribution (EPS) systems. This paper presents an architecture of the DC SSPC and provides the mitigation techniques for transient voltage overshoot during its turn-off. The high source side inductance carries breaking current (9xnominal current) just before turnoff and induces large voltage transient across the semiconductor devices. Therefore, the stored inductive energy needs to be dissipated in order to prevent semiconductor switches from over-voltage/thermal breakdown. Three different transient voltage suppression (TVS) devices to reduce voltage stress across switches are included in the paper for detail study. The comprehensive comparison of the TVS devices is presented. In addition, the thermal impact of the TVS devices on the semiconductor switches is also analyzed.

Fuel economy and emission challenges are pushing automotive OEMs to develop alternative hybrid-electric, and full-electric powertrains. This increases variation in potential powertrain architectures, exacerbating the already complex control software used to coordinate various propulsion devices within the vehicle. Safety of this control software must be ensured through high-integrity software monitoring functions that detect faults and ensure safe mitigating action is taken. With the complexity of the control software, this monitoring functionality has itself become complex, requiring extensive modification for each new powertrain architecture. Significant effort is required to develop, calibrate, and verify to ensure safety (as defined by ISO 26262). But this must also be robust against false fault-detection, thereby maximising vehicle availability to the customer.

The size and morphology of soot particles and agglomerates extracted from lubricating oil drawn from the sump of a diesel engine have been investigated and compared using Transmission Electron Microscopy (TEM) and Nanoparticle Tracking Analysis (NTA). Samples were prepared for electron microscopy imaging by both centrifugation and solvent extraction to investigate the impact of these procedures on the morphological characteristics, such as skeleton length and width and circularity, of the obtained soot. It was shown that centrifugation increases the extent of agglomeration within the sample, with 15% of the agglomerates above 200 nm compared to only 11% in the solvent extracted soot. It was also observed that the width of centrifugation extracted soot was typically 10 nm to 20 nm larger than that of solvent extracted soot, suggesting that centrifugation forces the individual agglomerate chains together.

Studies of diesel system deposits continue to be the subject of interest and publications worldwide. The introduction of high pressure common rail systems resulting in high fuel temperatures in the system with the concomitant use of fuels of varying solubilizing ability (e.g. ULSD and FAME blends) have seen deposits formed at the tip of the injector and on various internal injector components. Though deposit control additives (DCAs) have been successfully deployed to mitigate the deposit formation, work is still required to understand the nature and composition of these deposits. The study of both tip and internal diesel injector deposits (IDID) has seen the development of a number of bench techniques in an attempt to mimic field injector deposits in the laboratory. One of the most used of these is the Jet Fuel Thermal Oxidation Tester or JFTOT (ASTM D3241).

High power density for aerospace motor drives is a key factor in the successful realization of the More Electric Aircraft (MEA) concept. An integrated system design approach offers optimization opportunities, which could lead to further improvements in power density. However this requires multi-disciplinary modelling and the handling of a complex optimization problem that is discrete and nonlinear in nature. This paper proposes a multi-level approach towards applying random heuristic optimization to the integrated motor design problem. Integrated optimizations are performed independently and sequentially at different levels assigned according to the 4-level modelling paradigm for electric systems. This paper also details a motor drive sizing procedure, which poses as the optimization problem to solve here. Finally, results comparing the proposed multi-level approach with a more traditional single-level approach is presented for a 2.5 kW actuator motor drive design.

This work was concerned with study of the in-cylinder flow field and flame development in a spark ignition research engine equipped with Bowditch piston optical access. High-speed natural light (chemiluminescence) imaging and simultaneous in-cylinder pressure data measurement and analysis were used to understand the fundamentals of flame propagation for a variety of ethanol fuels blended with either gasoline or iso-octane. PIV was undertaken on the same engine in a motoring operation at a horizontal imaging plane close to TDC (10 mm below the fire face) throughout the compression stroke (30°,40°,90° and 180°bTDC) for a low load engine operating condition at 1500rpm/0.5 bar inlet plenum pressure. Up to 1500 cycles were considered to determine the ensemble average flow-field and turbulent kinetic energy. Finally, comparisons were made between the flame and flow experiments to understand the apparent interactions.

The paper will deal with the problem of establishing a desirable power sharing in multi-feed electric power system for future more-electric aircraft (MEA) platforms. The MEA is one of the major trends in modern aerospace engineering aiming for reduction of the overall aircraft weight, operation cost and environmental impact. Electrical systems are employed to replace existing hydraulic, pneumatic and mechanical loads. Hence the onboard installed electrical power increases significantly and this results in challenges in the design of electrical power systems (EPS). One of the key paradigms for future MEA EPS architectures assumes high-voltage dc distribution with multiple sources, possibly of different physical nature, feeding the same bus(es). In our study we investigate control approaches to guarantee that the total electric load is shared between the sources in a desirable manner. A novel communication channel based secondary control method is proposed in this paper.

The future aircraft electrical power system is expected to be more efficient, safer, simpler in servicing and easier in maintenance. As a result, many existing hydraulic and pneumatic power driven systems are being replaced by their electrical counterparts. This trend is known as a move towards the More-Electric Aircraft (MEA). As a result, a large number of new electrical loads have been introduced in order to power many primary functions including actuation, de-icing, cabin air-conditioning, and engine start. Therefore electric power generation systems have a key role in supporting this technological trend. Advances in modern power electronics allow the concept of starter/generator (S/G) which enables electrical engine start and power generation using the same electrical machine. This results in substantial improvements in power density and reduced overall weight.

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.

Car floor structures typically contain a number of smaller-scale features which make them challenging for vibro-acoustic modelling beyond the low frequency regime. The floor structure considered here consists of a thin shell floor panel connected to a number of rails through spot welds leading to an interesting multi-scale modelling problem. Structures of this type are arguably best modelled using hybrid methods, where a Statistical Energy Analysis (SEA) description of the larger thin shell regions is combined with a finite element model (FEM) for the stiffer rails. In this way the modal peaks from the stiff regions are included in the overall prediction, which a pure SEA treatment would not capture. However, in the SEA regions, spot welds, geometrically dependent features and directivity of the wave field are all omitted. In this work we present an SEA/FEM hybrid model of a car floor and discuss an alternative model for the SEA subsystem using Discrete Flow Mapping (DFM).

Range Extended Electric Vehicles (REEVs) are gaining popularity due to their simplicity, reduced emissions and fuel consumption when compared to parallel or series/parallel hybrid vehicles. The range extender internal combustion engine (ICE) can be optimised to a number of steady state points which offers significant improvement in overall exhaust emissions. One of the key challenges in such vehicles is to reduce the overall powertrain costs, and OEMs providing REEVs such as the BMW i3 have included the range extender as an optional extra due to increasing costs on the overall vehicle price. This paper discusses the development of a low cost Auxiliary Power Unit (APU) of c.25 kW for a range extender application utilising a 624 cc two cylinder automotive gasoline engine. Changes to the base engine are limited to those required for range extender development purposes and include prototype control system, electronic throttle, redesigned manifolds and calibration on European grade fuel.