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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.

Electric machines in aerospace applications are subjected to extremely high operating temperatures. This increases coercivity or decreases saturation flux density of the electrical steel resulting in increased core loss. The need for high power density and increased operating speed favours the use of thin gauge Silicon Steel (Si-Fe) and Cobalt Iron (Co-Fe) laminations for aerospace applications. Therefore, the variation in iron loss is studied for three grades of Si-Fe laminations by subjecting them to controlled ageing in laboratory. The analysis is also provided over a range of flux density and frequency to generalize the phenomenon over the operating domain. The results of ageing the laminations are in turn used to predict the degradation in performance of a 1.15 MW, 16-pole 48-slot propulsion machine for aerospace application. The degradation is estimated in terms of variation in iron loss.

Electric machines offering a high power density are required for aerospace applications. Soft magnetic material with a high saturation flux density is one of the key component which is required to realize these power density targets. The need for a high saturation flux density necessitates the use of cobalt iron lamination over the conventional silicon steel. However, cobalt iron is very expensive i.e. order of 10 in comparison to silicon steel. Stator segmentation is identified as an appropriate method to reduce the wastage and cost associated with lamination. Consequently, in this paper, stator segmentation is analyzed on a 1.35 MW, 16-pole 48-slot propulsion machine. The impact of manufacturing is accounted by controlling the resulting airgap between the segmented structures. Electromagnetic performance for various segmented topologies are compared in terms of torque, torque ripple, and iron loss.

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.

Dynamical Energy Analysis (DEA) has recently been introduced as a mesh-based high frequency method modelling structure borne sound for complex built-up structures. Using DEA, the structure-borne sound of an assembled agricultural tractor was calculated and good agreement between measurement and DEA calculations has been shown. However, it is still difficult to model a solid structure as currently DEA is based on wave-transmission calculations through plates and plate-to-plate junctions. Additionally, it is often difficult to generate accurate FE meshes of assembled complex structures because of welds, bolts, and rubber brushes between components. In this paper, we propose a novel method to generate DEA elements based on measurement data in order to model solid parts of a complex structures. The method of Advanced Transfer Path Analysis (ATPA) is employed to extract energy-transmission characteristics of a structure.

Reconfigurable tooling frames consisting of steel box sections and bolted friction clamps offer an opportunity to replace traditional expensive welded steel tooling. This well publicized reconfigurable reusable jig tooling has been investigated for use in the assembly of a prototype compound helicopter wing. Due to the aircraft configuration, the wing design is pinned at both ends and therefore requires a higher degree of end to end accuracy, over the 4m length, than conventional wings. During the investigation some fundamental issues are approached, including: Potential cost savings and variables which effect the business case. Achievable Jig accuracy. Potential sources of instability that may affect accuracy over time. Repeatability of measurements with various features and methods. Typical jig stability over 24hrs including effects of small temperature fluctuations. Deflections that occur due to loading.

The Rapid And Cost Effective Rotorcraft (RACER) is being developed by Airbus Helicopters (AH) to demonstrate a new Vertical Take-Off and Landing configuration to fill the mobility gap between conventional helicopters and aeroplanes. RACER is a compound rotorcraft featuring wings and multiple rotors. The wing arrangement suggested by AH is defined as a staggered bi-plane joined configuration with an upper and a lower straight wing, either side of the fuselage, connected at their outboard extent to form a triangular structure. The ASTRAL consortium, consisting of the University of Nottingham and GE Aviation Systems, are responsible for the design, manufacture, assembly and testing of the wings. Producing an optimised strategy to assemble a joined-wing configuration for a passenger carrying rotorcraft is challenging and novel. The objective of this work concerns all aspects of assembling the joined-wing structure.

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.

Morphology plays an important role in determining behaviour and impact of soot nanoparticles, including effect on human health, atmospheric optical properties, contribution to engine wear, and role in marine ecology. However, its nanoscopic size has limited the ability to directly measure useful morphological parameters such as surface area and effective volume. Recently, 3D morphology characterization of soot nanoparticles via electron tomography has been the subject of several introductory studies. So-called ‘3D-TEM’ has been posited as an improvement over traditional 2D-TEM characterization due to the elimination of the error-inducing information gap that exists between 3-dimensional soot structures and 2-dimensional TEM projections. Little follow-up work has been performed due to difficulties with developing methodologies into robust high-throughput techniques.

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.