The more-electric aircraft concept is a major trend in aircraft electrical power system engineering and results in an increase in electrical loads based on power electronic converters and motor drive systems. Unfortunately, power electronic driven loads often behave as constant power loads having the small-signal negative impedance that can significantly degrade the power system stability margin. Therefore, the stability issue of aircraft power systems is of great importance. The research of the thesis deals with the modelling and stability analysis of an aircraft power system. The aircraft power system architecture considered in the thesis is based on the More Open Electrical Technologies (MOET) aircraft power system with one generator as only a single generator can be connected to a system at any one time. The small-signal stability analysis is used with the system dynamic model derived from the dq modelling method under the assumption that the aircraft power system operating point does not change rapidly during normal operation mode. The linearization technique using the first order terms of a Taylor expansion is used so as to achieve a set of linear models around an equilibrium point for a small-signal stability study. The thesis presents the development of effective models capable of representing the electrical power system dynamic behaviour for stability studies. The proposed model can be used to predict the instability point for variations in operating points and/or system parameters. Agreement between the theoretical estimation, simulation, and experimental results for a simple system are achieved that ranges from acceptable to very good. Finally, the subsystem models described in the thesis can be interconnected in an algorithmic way that is representative of a more generalized aircraft power system model. The generalized model is also applied to a more complex and realistic aircraft power system with simulation validations for thorough investigations of aircraft power system stability. This model may be considered as a powerful and flexible stability analysis tool to analyse the complex multi-converter electrical power systems.

This dissertation describes a numerical modelling strategy for characterising the windage of a spiral bevel gear rotating within a static shroud. The techniques employed include the use of a parametric solid model, and flow field modelling using computational fluid dynamics (CFD) software. A number of hypothetical physical alterations are made to a control system consisting of a gear and a shroud, based on those found in a Rolls-Royce aero engine. Windage is a parasitic power loss that occurs when a gear does work on air and oil within a gas turbine internal gearbox. It leads to degradation of the oil, which wears turbo-machinery and bearing components, shortening their lives. Windage power losses also impact upon the fuel consumption of an engine, reducing its environmental credentials. The requirement of the oil is to cool and lubricate the meshing location of a pair of gears and for it to then be removed from the vicinity of the gear - preventing its re-ingestion and recirculation. The best solution to these issues of reducing windage and managing the oil is to shroud the gear effectively. Additional cooling of oil can mitigate the damage of too much heat generation, but this adds weight and expense to an engine. A parametric model of a shrouded spiral bevel gear is created, which allows for changes to be made to single or multiple dimensions of the gear and shroud. A control volume CFD approach is used, with a single tooth of a gear modelled to reduce computational time. Four gear size variables are tested: inner diameter, outer diameter, cone angle and module (number of teeth). Findings for air-only show that windage can be reduced by: increasing the cone angle; increasing the number of teeth; or decreasing the outer diameter. The effect of changing the inner diameter on windage was found to be complex due to the interaction of gear and shroud upon the system results, but far less significant than the outer diameter, as windage was seen to scale by this variable to the power of 4.3. Changes to the design of the shroud are made, with a comparison of five inlet and five outlet designs. It is found that a sudden restriction at the inlet to the shroud is the most effective way of reducing single phase windage, with additional shroud features that make the flow path more tortuous also helping. The outlet of the shroud is shown to increase windage as it is opened up and permitted to be less restrictive. A series of investigations using a Lagrangian discrete particle model (DPM) to simulate the presence of oil droplets within the system are also presented. It is shown that the destination of oil within the domain is predominantly dictated by the source location of the oil, with little sensitivity to initial velocity or size. Film modelling on the surface of the shroud, using the DPM-based film model, allows the motion of a thin layer of oil to be studied. In conjunction with the five shroud outlet designs, it is shown that a less restrictive, more open shroud outlet design will help prevent re-ingestion of oil that is present within the shrouded area of the gear.

Traffic congestion is an important reason for driver frustration which in turn is the main cause of human errors and accidents. Statistics reports have shown that over 90% of accidents are caused by human errors. Therefore, it is vital to improve vehicle controls to ensure adequate safety measures in order to decrease the number of accidents or to reduce the impact of accidents. An application of mathematical control techniques to the longitudinal dynamics of a vehicle equipped with an adaptive cruise control (ACC) system is presented. This study is carried out for the detailed understanding of a complex ACC vehicle model under critical transitional manoeuvres (TMs) in order to establish safe inter-vehicle distance with zero range-rate (relative velocity) behind a preceding vehicle. TMs are performed under the influence of internal complexities from vehicle dynamics and within constrained operation boundaries. The constrained boundaries refer to the control input, states, and collision avoidance constraints. The ACC vehicle is based on a nonlinear longitudinal model that includes vehicle inertial and powertrain dynamics. The overall system modelling includes: complex vehicle models, engine maps construction, first-order vehicle modelling, controllers modelling (upper-level and lower-level controllers for ACC vehicles). The upper-level controller computes the desired acceleration commands for the lower-lever controller which then provides the throttle/brake commands for the complex vehicle model. An important aspect of this study is to compare four control strategies: proportional-integral-derivative; sliding mode; constant-time-gap; and, model predictive control for the upper-level controller analysis using a first-order ACC vehicle model. The first-order model represents the lags in the vehicle actuators and sensor signal processing and it does not consider the dynamic effects of the vehicle’s sub-models. Furthermore, parameter analyses on the complex ACC vehicle for controller and vehicle parameters have been conducted. The comparison analysis of the four control strategies shows that model predictive control (MPC) is the most appropriate control strategy for upper-level control because it solves the optimal control problem on-line, rather than off-line, for the current states of the system using the prediction model, at the same time being able to take into account operation constraints. The analysis shows that the complex ACC vehicle can successfully execute TMs, tracking closely the desired acceleration and obeying the constraints, whereas the constraints are only applied in the MPC controller formulation. It is found that a higher length of the prediction horizon should be used for a closed acceleration tracking. The effect of engine and transmission dynamics on the MPC controller and ACC vehicle performance during the gear shifting is studied. A sensitivity analysis for MPC controller and vehicle parameters indicates that a length of the control horizon that is too high can seriously disturb the vehicle behaviour, and this disturbance can be only removed if a higher value of control input cost weighting is used. Furthermore, the analysis indicates that a mass within the range of 1400-2000 kg is suitable for the considered ACC vehicle. It is recommended that a variable headway time should be used for the spacing control between the two vehicles. It is found that the vehicle response is highly sensitive to the control input cost weighting; a lower value (less than one) can lead to a highly unstable vehicle response. It is recommended that the lower-level controller must take into account the road gradient information because the complex ACC vehicle is unable to achieve the control objectives while following on a slope. Based on the results, it is concluded that a first-order ACC vehicle model can be used for the controller design, but it is not sufficient to capture the complex vehicle dynamic response. Therefore, a complex vehicle model should be of use for the detailed ACC vehicle analysis. In this research study the first-order ACC vehicle model is used for the complex vehicle validation, whereas the complex ACC vehicle model can be used for the experimental validation in future work.

Although hybrid electric vehicles (HEVs) generally improve fuel economy (FE) compared to conventional vehicles, evidence of higher FE variability in HEVs compared to conventional vehicles indicates that apart from the improvement in FE, the reduction of FE variability is also of significant importance for HEVs. Over the years research on how to optimise powertrain component sizes of HEVs has generally focused on improving FE over a given driving pattern; FE variability over a realistic range of driving patterns has generally been overlooked, and this can lead to FE benefits of HEVs not being fully realised in real-world usage. How to reduce the FE variability in HEVs due to variation in driving patterns through the optimisation of powertrain component sizes is considered as the research question. This research proposes a new methodology in which powertrain components are optimised over a range of driving patterns representing different traffic conditions and driving styles simultaneously. This improves upon the traditional methodology followed in the reviewed literature, where an optimisation is performed for each individual driving pattern. An analysis shows that the traditional methodology could produce around 20% FE variability due to variation in driving patterns. This study considers a computer simulation model of a series-parallel Toyota Prius HEV for the investigation. Four powertrain components, namely, internal combustion engine, generator, motor, and battery of the Toyota Prius are optimised for FE using a genetic algorithm. For both the proposed and traditional methodologies, the powertrain components are optimised based on 5 standard driving patterns representing different traffic conditions and driving styles. During the optimisation, the proposed methodology considers all the 5 driving patterns simultaneously, whereas the traditional methodology considers each driving pattern separately. The optimum designs of both the methodologies and the simulation model of the Toyota Prius which is the benchmark vehicle for this study are evaluated for FE over the aforementioned 5 standard driving patterns and also 10 real-world driving patterns of a predefined route consisting of urban and highway driving patterns. The proposed methodology provides a single optimum design over the 5 standard driving patterns, whereas the traditional methodology provides 5 different optimum designs, one for each driving pattern. The single optimum design produced by the proposed methodology is independent of the sequence of driving patterns. The proposed methodology reduces FE variability by 5.3% and up to 48.9% with comparable average FE compared to the Toyota Prius and traditional methodology, respectively over the 10 real-world driving patterns, whereas none of the optimum designs of the traditional methodology is able to reduce FE variability compared to the Toyota Prius. This research provides a promising direction to address customer concerns related to FE in the real-world and improves understanding of the effect of driving patterns on the design of powertrain components.

The automotive industry is, perhaps, and that is left open to debate, one of the most important engineering fields, and one which is increasingly influential on our everyday lives. Automotive engineering brings together all aspects of engineering knowledge to produce the one product that so many people have become dependent upon. The industry itself is vast and many tangents can be drawn from it, hence here we must define the area of interest to which this work relates. The initial concept for the work carried out stems from the passenger car industry; however, the work has more farreaching benefits and implications. As passenger vehicles become increasingly popular and increasingly advanced, so the need increases to understand more of the operation of all aspects of the vehicle. This work stems from a need to gain understanding of the flow of breather and blowby gases within an internal combustion engine (ICE) with the long-term aim of fully understanding the processes involved to enable improved engine design and reduced pollutant production. The latter is a significant driving force as legislation becomes more strict on the level of pollutants emitted from vehicles and engines. This work therefore not only reflects on passenger vehicles, but any other industry or product that uses ICEs.

A significant number of electronic control units (ECUs) are nowadays networked in automotive vehicles to help achieve advanced vehicle control and eliminate bulky electrical wiring. This, however, inevitably leads to increased complexity in vehicle fault diagnostics. Traditional off-board fault diagnostics and repair at service centres, by using only diagnostic trouble codes logged by conventional onboard diagnostics, can become unwieldy especially when dealing with intermittent faults in complex networked electronic systems. This can result in inaccurate and time consuming diagnostics due to lack of real-time fault information of the interaction among ECUs in the network-wide perspective. This thesis proposes a new framework for on-board knowledge-based diagnostics focusing on network level faults, and presents an implementation of a real-time in-vehicle network diagnostic system, using case-based reasoning. A newly developed fault detection technique and the results from several practical experiments with the diagnostic system using a network simulation tool, a hardware- in-the- loop simulator, a disturbance simulator, simulated ECUs and real ECUs networked on a test rig are also presented. The results show that the new vehicle diagnostics scheme, based on the proposed new framework, can provide more real-time network level diagnostic data, and more detailed and self-explanatory diagnostic outcomes. This new system can provide increased diagnostic capability when compared with conventional diagnostic methods in terms of detecting message communication faults. In particular, the underlying incipient network problems that are ignored by the conventional on-board diagnostics are picked up for thorough fault diagnostics and prognostics which can be carried out by a whole-vehicle fault management system, contributing to the further development of intelligent and fault-tolerant vehicles.

In this document, research into the modelling and analysis of current and concept vehicles for the purpose of enhancing vehicle handling is summarised. This work is recounted in detail in a portfolio of reports that has been submitted for the degree of Doctor of Engineering. The portfolio includes fifteen submissions, eleven of which are concerned with the analysis and simulation of drivers' steering behaviour. Two relate to a novel suspension concept. One addresses a current problem caused by suspension variability and one introduces a process for selecting between new suspension concepts. Each of these fifteen submissions is summarised in this document. In addition, the order in which it is recommended that these submissions be read is listed. In section 4, a project summary of the research into the analysis and simulation of drivers' steering behaviour is presented. Existing models of drivers' steering behaviour are reviewed. Vehicle tests that illustrate the different steering styles used by different drivers are recounted. A driver model that simulates the steering behaviour exhibited in these tests is formulated . Then, this driver model is used to develop a switching strategy for variable dampers. It is demonstrated that the switching strategy enhances vehicle handling and reduces the roll experienced by drivers during a handling manoeuvre. Finally, it is verified that this research complies with the requirement of the degree of Doctor of Engineering to demonstrate innovation in the application of knowledge to the engineering business environment. This is achieved by specifying eight examples of where new ideas and methods have been applied to address current issues within the automotive industry.

The energy management system (EMS) of hybrid electric vehicle controls the operation of two power plants; electric machine/battery and typically engine. Hence the fuel economy and emissions of hybrid vehicles strongly depend on the EMS. It is known that considering the future trip demand in devising an EMS control strategy enhance the vehicle and component performances. However existing such acausal EMS cannot be used in real time and would require prior knowledge of the trip vehicle speed profile (trip demand). Therefore rule based EMS which considers instantaneous trip demand in devising a control strategy are used. Such causal EMS are real time capable and simple in design. However rule based EMS are tuned for a set of driving cycles and hence their performance is vulnerable in real world driving. The research question is “How to design a real time capable acausal EMS for a plug in hybrid electric vehicle (PHEV) that can adapt to the uncertainties of real world driving”. In the research, the design and evaluation of a proposed EMS to deal and demonstrate in scenarios expected in real world driving respectively were considered. The proposed rule based acausal EMS is formulated over the estimated vehicle trip energy and driving information. Vehicle trip energy is the electric (battery) energy required to meet the trip demand estimated using known driving information. Driving information that can be considered are driver style, route distance and road types like urban and extra urban, with traffic as a sub function. Unlike vehicle speed, vehicle trip energy is shown to be relatively less dynamic in real world driving. For the proposed EMS evaluation, a commonly used parallel PHEV model was simulated. For driving information EMS was not integrated to a navigation system but manually defined. Evaluation studies were done for a driver, and traffic was not considered for simplicity. In the thesis, vehicle performance and credentials for real world applicability (real time capability and adaptability) of the proposed acausal EMS are demonstrated for various scenarios in real world driving; varied initial SOC, sequence of road types, trip distance and trip energy estimation. Over the New European Driving Cycle (NEDC) the proposed EMS vehicle performance is compared to a conventional rule based EMS. The proposed EMS fuel economy improvement is up to 11% with 5 times fewer number of engine stop-starts. Similarly in the validation study, with no prior knowledge of trip vehicle speed profile, the fuel economy improvement is up to 29% with 7 times fewer number of engine stop-starts. The simulation duration of the proposed EMS is as good as conventional rule based EMS. Hence the proposed EMS is potentially real time capable. The proposed EMS can adapt to a wide variation in trip energy (±15%) estimation and still perform better than the conventional rule based EMS. The proposed EMS can tolerate variation in trip demand estimation and no prior knowledge of trip vehicle speed profile is required, unlike other acausal EMS studies in the literature. A new PHEV EMS has been formulated. Through simulation it has been seen to deliver benefit in vehicle performance and real world applicability for varied scenarios as expected in real world driving. The key new step was to use vehicle trip energy in the formulation, which enabled rule based EMS to be acausal and potentially real time capable.

This thesis describes research undertaken to improve computational modelling capability for the internal gearbox (IGB) of an aeroengine. Using the commercial computational fluid dynamics (CFD) software ANSYS FLUENT modelling methodologies for regions within the IGB have been developed, applied and refined. The IGB is a bearing chamber that houses the bearings that support the low pressure, intermediate pressure and high pressure shafts and in addition the spiral bevel gear pair that enable power to be taken from the high pressure shaft to power aircraft auxiliary systems. Within civil aeroengines parasitic power loss is a significant issue and as oil is used to lubricate and cool throughout the engine, this power loss largely manifests as increased heat-to-oil (HTO). A significant contributor to HTO is the IGB. The IGB contains complex geometry and a highly rotating two-phase flow consisting of films, droplets, ligaments and mist. Central to the IGB is the spiral bevel gear pair. Previous modelling research has shown that detailed modelling of flow behaviour is too computationally expensive for domains larger than a few teeth. Modelling the meshing gears with full flow fidelity is not yet feasible. In this thesis a significantly less computationally expensive approach is explored. The complex gear-shroud geometry is replaced by a smooth cone with momentum sources used to generate the required fluid motion. In the single phase model these momentum sources were tuned/calibrated against a full tooth model spanning four teeth. The model was capable of generating flow behaviour to within 5% of the full tooth model. Oil was added as a discrete phase with a film model but was less successful as oil motion is strongly affected by geometrical detail. A second approach to whole chamber modelling was proposed where the chamber is split into three zones and coupled via boundary conditions. Single phase investigation showed that the amount of swirl in the front chamber affects computed windage power loss with the maximum occurring at an inlet swirl number of around 0.5. The amount of swirl at gear entry does not however affect the amount of swirl at shroud exit and this shows that decoupling of the front chamber is viable. The investigations into the zonal coupling of the IGB highlighted the importance of the geometry of the rear chamber (between gear and bearing) on the flow through the gear. A study to investigate how best to model the two-phase flow in this rear chamber was conducted. Transient models showed the volume of fluid approach (VOF) to be inadequate whereas a full two-phase Eulerian model converged, yielding viable results consistent with limited qualitative experimental data. The computational model predicts significant accumulation of oil towards the bearing side of the chamber, with this oil stripping periodically through shroud exit slots to the front chamber. In the final part of the research a parametric study on several geometric features in the rear chamber was conducted using the developed two-phase modelling methodology. The chamber size, rear wall geometry, shroud exit slot location and size were investigated. The work in this thesis improves IGB modelling capability through - Establishing the capabilities and limitations of momentum source approach for full two-phase modelling of a shrouded gear - Establishing that to some extent a bearing chamber can be productively modelled as separate but linked zones - Identifying a successful modelling methodology for the high volume fraction two phase flow in the rear chamber In addition the work in this thesis shows that - For single phase flow the amount of swirl at gear inlet affects the windage power loss - The behaviour of oil in the rear chamber, including the amount trapped and the exit condition, are strongly affected by chamber geometry Guidelines for rear chamber design are also suggested.

Bearing Chambers in Aero-Engines are located near the rolling-element type of bearings which support the shafts and accomodate the resulting thrust loads. One of the main task of the bearing chambers is, beside an efficient scavenging of the lubricating oil, the cooling of the hot compartments. A very complex two-phase air-oil flow takes usually place in these bearing chambers consisting of oil droplet-laden air flows and shear-driven liquid wall films. The interaction of the droplets with the wall films is significantly influencing the wall heat transfer and the cooling performance of these systems. For this reason, a detailed characterization and modelling of the mass and momentum exchange between droplets and wall films for the unique impingement parameter range in bearing chambers is inevitable. This scientific report investigates the oil droplet impact dynamics for typical impingement regimes relevant to aero-engine bearing chambers. The application of a Direct Numerical Simulation (DNS) technique based on the Volume-of-Fluid (VOF) method and coupled with a gradient-based adaptive mesh refinement (AMR) technique allowed to characterize the drop impact dynamics during various single micro- and millimeter drop impacts onto thin and thick films. With the help of a special numerical treatment, a self-perturbing mechanism is installed that leads to the correct resolution of the crown disintegration process. The numerical methodology was thoroughly validated using the experimental results of millimeter sized drop impacts onto deep liquid pools. These results were developed with an enhanced back-illuminated high-speed imaging and Particle Tracking Velocimetry (PTV) technique. New insights into the cavity penetration, the crown’s breakup dynamics and the secondary droplet characteristics following a single drop impact have been developed with the help of the isolated variation of different parameters of influence. Particularly the influence of the Froude number, the impingement angle, and the cavity-wall interaction delivered results to date not reported in scientific literature. Beside the advances in fundamental physics describing the drop impact dynamics with the help of the numerical and experimental results, a set of correlations could also be derived. From these correlations, a drop-film interaction model was formulated that is suitable for the parameter range found in bearing chambers.