Vehicle-to-grid uses vehicles with on-board electricity storage as an energy storage system for the electricity grid. Vehicles not only take power from the grid when charging, but can supply power back to the grid. This storage mechanism can then be used in various applications, for example, providing balancing services and helping the introduction of renewable energy sources. Research into vehicle-to-grid suggests that it is feasible in certain applications. Indeed, the component technology required for vehicle-to-grid has been successfully demonstrated. Gaps in the analysis of vehicle-to-grid feasibility remain. Notably, the behaviour of individuals in a vehicle-to-home context is not well understood. A vehicle-to-home simulation tool was developed to address these gaps. The tool incorporates a use case methodology and a Matlab Simulink model. Application of the use case methodology identifies the inputs and constraints determined by users in a vehicle-to-home system. Feeding these inputs into the model facilitates the sensitivity analysis of vehicle-to-home operation to these user dependent variables. The use of the simulation tool is demonstrated in two case studies: Using an electric vehicle as back-up power supply; and using an electric vehicle to support small-scale distributed generation. The operation of a vehicle-to-home system in these case studies is presented, along with the sensitivity of operation to input parameters including: battery storage capacity, vehicle usage and vehicle charging. Both case studies demonstrated that, given the correct conditions|notably cooperation of the vehicle user|vehicle-to-home can operate successfully in storage applications. It was shown that an electric vehicle could provide back-up storage to households for a useful amount of time|between 20 hours and several days. It was shown that an electric vehicle can be used to store energy from a small-scale wind turbine such that the generation is better utilised than if no storage is available. The developed simulation tool enables analysis of novel vehicle-to-home applications not possible with previous models of vehicle-to-grid. The use of the tool highlighted the importance of including individual variation in behaviour when studying vehicle-to-home systems.

Club motorsport, a low cost, amateur form of motorsport, forms a significant part of the motorsport industry in the United Kingdom. If efforts are not made to move towards more environmentally friendly technologies, then this form of motorsport is at risk of becoming irrelevant. One approach taken by other motorsport sectors has been to implement hybrid electric vehicle technology, which can result in improved vehicle performance on the race track. However, the companies that operate in the club motorsport sector do not typically have the resources and experience necessary to develop these technologies. An innovative process was used to guide the design of a new hybrid electric vehicle drivetrain for use in club motorsport. This process made use of the ability for vehicle manufacturers to set the vehicle specifications in club motorsport. A conjoint analysis of customer requirements was carried out, a first for the industry, and led to the development of a market simulation tool. A vehicle simulation tool was then developed to assist in the evaluation of the hybrid electric drivetrain design options. The result of following this process was a new and innovative hybrid electric drivetrain installed in a Westfield Sportscars Sport Turbo, reducing 0-60mph acceleration time from 5.4 seconds to 3.8 seconds. An innovative type of system control was implemented, by where the driver is given a finite amount of boost energy for use throughout the race. The drivetrain can also be easily transferred to other vehicle platforms, as the first shelf engineered hybrid drivetrain for motorsport, allowing its use by multiple manufacturers across the club motorsport and niche vehicle sectors. This project has shown that it is possible to implement environmentally friendly technologies, such as hybrid electric vehicle technology, into club motorsport and be able to meet customer, technical and cost requirements. The process that has been developed enables innovation in hybrid electric race car design. This has been shown in the development of a hybrid electric vehicle suitable for use, and sale, in the club motorsport industry.

Slotted aerofoils have been suggested by numerous researchers as an effective means of controlling boundary layer flow separation, and improving aerodynamic performance. Numerous slot designs have been studied at high Reynolds number, but there is scarcity of study of such slots effect on aerofoil performance in low Reynolds number scenarios. In the present work, wind tunnel and numerical investigation of the effect of a unique slot configuration and its geometric parameters on the aerodynamic performance of a NACA0018 aerofoil at low Reynolds number was executed. The aim of this work is to ascertain if the unique slot configuration on the NACA0018 can improve the aerodynamic performance compared to a plain NACA0018, and if the slotted NACA0018 could be applied as rotors on a Darrieus-style vertical axis micro wind turbine for small scale energy conversion at low wind speeds. Four aerofoils were initially fabricated for the wind tunnel tests, each conforming to the NACA0018 profile; a plain aerofoil and three other slotted aerofoils, each with a span–length slot positioned at X=15%, X=45% and X=70% from the leading edge. The, chord length (c), span, slot slope (ψ) and slot width of the slotted aerofoils were 0.25m, 0.3m, 55° and 0.02c respectively. A 2D wind tunnel set up was used in testing the four aerofoils at Reynolds numbers of 92x103 138x103, 184x103 and 230x103, within 0° to 20° range of incidence. Comparing the slotted and plain aerofoils, the aerodynamic force data shows that the presence of the slots was detrimental to aerodynamic performance especially when the slot location is closer to the leading edge. Therefore, a 2D numerical parametric study of slot width and slope was carried out using ANSYS FLUENT 16.0 with the intention of improving the lift–to–drag (L/D) ratio of the span–length slotted aerofoils. Furthermore, a final slot configuration consisting of segmented slot pattern which incorporated the results of the parametric study was fabricated and tested in a wind tunnel. The aerodynamic force analysis shows a 50% increase in L/D ratio of the slotted aerofoil with slot position at X=70%, but its aerodynamic performance was still less than the Plain NACA0018. Thus this work proves that the suggested slot layout did not improve the aerodynamic performance of the NACA0018 aerofoil and as a result, it cannot be recommended to be used as a vertical axis wind turbine rotor. Finally, in order to improve the NACA0018 aerofoil performance, it was suggested that a new slot layout with slot slope on the pressure side inclined towards the leading edge should be designed and studied.

An autogyro or Autogiro is a unique type of rotary-wing aircraft that was successfully flown in the 1920s, many years before the first helicopter came to service. As far as the rotorcraft technology is concerned, the technical issues addressed by autogyros were eventually rectified and paved the way for the success of helicopter development. When helicopter became more popular and accepted in the civil aviation industry in the 1940s, autogyros were nearly forgotten and the popularity slowly diminished. The re-emergence of autogyros in the last two decades in hobby and sports flight activities, however, coincides with bad safety records due to stability issues. At the time of this writing, there are no specific flying qualities standards to be em- ployed as guidelines to design a light autogyro with good stability attributes. The only requirements available are addressed in the BCAR Section T airworthiness standard for light autogyros which only prescribes some basic dynamic stability requirements for the vehicle. For existing conventional light autogyros which mostly of 'home-built' type, complying with the airworthiness standards would be an issue as most of them were built beforehand. From these concerns, this Thesis aims to improve the flying qualities performance of existing light autogyros through automatic flight control methods, as one of the ways to practically achieve the required performance. Consequently, specific flying qualities requirements for light autogyros must first be proposed as preliminary guidelines for design and flying qualities improvement. A generic mathematical model of light autogyros named ARDiS is developed based on the 'multiblade' simulation ap- proach which is computationally cost-effective. This model was successfully validated against real autogyro flight data and later implemented in the control enhancement of the vehicle. The control enhancement was developed using classical approaches with limitation in size and simplicity of the vehicle as a light aircraft. Proper actuation control hard- ware was separately modelled and deployed into the autogyro to demonstrate a higher dynamics in the control mechanism so that a more realistic attitude behaviour of the vehicle is presented. This control enhancement was successfully evaluated with both, linear and nonlinear simulations according to the proposed autogyro flying qualities attributes. All presented results signify a higher possibility of improving the flying qualities of currently used and future built light autogyros through control enhance- ment.

Structural health monitoring requires precise techniques with high accuracy, due to the relatively small deformations that can be found in many structures. It has been proved that GPS is capable of detecting the characteristics of the response of flexible structures. Although GPS can be applied for displacement monitoring, some existing constraints may limit the accuracy of the monitoring application. Some sources of these limitations are the multipath error, random noise, cycle slips and the geometry of the satellite constellation. Studies have been conducted to overcome these limitations using a combination of the GPS and other sensors: geodetic (e.g. Robotic Total Stations) or non-geodetic (e.g. accelerometer). Although these studies succeeded generally to reduce the effects of these limitations, they are still restricted on specific cases of monitoring, due to difficulties of using the accelerometer for monitoring static or quasi-static displacements and RTS due its limited range. The introduction of the Global Navigation Satellite Systems (GNSSs), apart from GPS, such as GLONASS, BeiDou, and Galileo provides an alternative solution by combined GPS data with additional observations from other GNSS constellations to overcome GPS-only limitations. Therefore, the current study aims to develop a multi-GNSS method for structural health monitoring. The integration of different constellations contributes to improving the accuracy and availability of the solution, which allows the structural response and its characteristics effectively. The positioning performance in this study is investigated and achieved in three conducted stages: Firstly, a series of GNSS zero baseline measurements are conducted simultaneously for 12 consecutive days in the UK and China sites to investigate the noise level of different GNSS solutions. The main aim is to investigate the correlation between the geometry of satellite constellation and the performance of the GPS-only and multi-GNSS solution. It is proved that for periods of a poor GPS-only solution, due to the satellite constellation or problematic satellites, the multi-GNSS solution leads to more accurate and of higher availability solution. Secondly, short baselines of GNSS measurements of static (1 Hz) and kinematic (10 Hz and 20 Hz) observations are collected to evaluate the precision and accuracy of different GNSS solutions. Following the same analysis approach and using the 3D best fitting of non-linear least squares adjustment models, it is proved that the multi-GNSS solution is significantly improved in comparison with the GPS-only solution for periods of weak geometry or problematic satellites. This can be attributed to the geometry improvement of the combined solution, which can reach 30% for GDOP values. Finally, the GNSS measurements are investigated at the Severn Bridge and the Forth Road Bridge in the UK for real structural monitoring of long-span suspension bridges. The analysis was based on an assessment of workflow methodology applied in this study. The noise level of GNSS data was assessed by zero baseline at the base station of the Severn Bridge. It was approved that the combined GPS/GLONASS solution reduced the noise level and led to more accurate results with less discontinuous time intervals. Regarding the spectral analysis, the GPS-only solution led to a higher noise level of the spectrum and less easy to be detected peaks for some intervals relatively to the spectra of the multi-GNSS solution. It was inferred from the results presented in the current study that the noise errors and discontinuity problems, as well as other limitations of the GPS-only solution, were significantly reduced and improved by combined GNSS solution. These findings are promising for many real structural monitoring applications.

The field of Prognostics and Health Management is becoming ever more important in the modern maintenance era, with advanced techniques of automation and mechanisation becoming increasingly prevalent. Prognostic technology has promising abilities to forecast remaining useful life and likely future circumstances of complex systems. However, the evolution of data processing and its critical impact on remaining useful life predictions continually demand increasing development so as to meet higher performance levels. There is often a gap between the adequacy of prognostic pre-processing and the prediction methods. One way to reduce this gap would be to design an adaptive data processing method that can filter multidimensional condition monitoring data by incorporating useful information from multiple data sources. Due to the incomplete understanding on the multi-dimensional failure mechanisms and the collaboration between data sources, current prognostic methods lack the ability to deal effectively with complicated interdependency, multidimensional condition monitoring information and noisy data. Further conventional methods are unable to deal with these efficiently. The methodology proposed in this research handles these deficiencies by introducing a prognostic framework that allows the effective use of monitoring data from different resources to predict the lifetime of systems. The methodology presents a feed-forward neural network filtering approach for trajectory similarity based remaining useful life predictions. The extraction of health indicators is applied as a type of dynamic filtering, in which the time series having full operational conditions are used to train a neural network mapping between raw training inputs and a health indicator output. This trained network function is evaluated by repeating condition monitoring information from multiple data subsets. After the network filtering, the training trajectories are used as baselines to predict the future behaviours of test trajectories. The similarity between these data subsets compares the relationship between the historical performance deterioration of a system's prior operating period with a similar system's degradation behaviour. The proposed prognostic technique, together with dynamic data filtering and remaining useful estimation, holds the promise of increased prediction performance levels. The presented methodology was tested using the PHM08 data challenge provided by the Prognostics Centre of Excellence at NASA Ames Research Centre, and it achieved the overall leading score in the published literature.

Automotive companies are searching for new, innovative materials that attempt to redefine what is traditionally associated as a ‘luxury material’. Market research shows that future customers will demand tangible sustainability in vehicle interiors through the use of eco-friendly materials. However, research has also identified customer scepticism towards the quality of green products sold by luxury brands. The perception of quality is typically determined by peripheral and sensorial product properties such as styling, shape and touch. The uncertainty of new materials compounded by the need to balance sustainability, sensory and emotional appeal mean it is no longer possible to rely on the designers’ intuition and experience to evaluate materials. Rigorous, robust methods which include both objective material assessments and the quantification of subjective, sensory and experiential attributes will maximize the chance of successful adoption by customers. They can also offer further insight, such as demonstrating that the Perceived Quality (PQ) of a cheaper material can be improved just by making the material softer using a foam backing, as was found in this research. To address this, a new process has been developed to measure the perceived haptic quality of soft automotive interior materials. Studies were conducted in the UK and Hong Kong to generate user-defined metrics. Of these metrics, roughness and hardness had the largest impact on PQ, so mechanical testing was conducted to obtain objective measurements of both. The subjective and objective measurements were found to correlate strongly, implying that objective measurements alone could indicate a customer’s opinion of these materials. The final stage of the process introduces a statistical model which uses the objective data to predict PQ scores. This is based around an Artificial Neural Network validated as accurate to within 4.5%. A graphical user interface was designed so practitioners can use the model to predict how customers may respond to a new material or a change in the surface characteristics of an existing material, without needing to conduct the initial customer research. The process has been integrated in part within the sponsor company and has influenced future research and business strategy in this area.

Although flutter analysis is a relatively old problem in aviation, it is still challenging, particularly with the advent of composite materials and requirements for high-speed light airframes. The main challenge for this problem is at the transonic flow region. The transonic flow, being non-linear, poses a great challenge over traditional linear theories which fail to predict the aerodynamic properties accurately. Aerospace has been one of the primary areas of applications to take advantage of composite materials with the aim to reduce the total mass and improve control effectiveness. This work takes advantage of CFD methods advancement as the main flow solver for non-linear governing equations. In order to investigate the dynamic behaviour of composite aircraft wings, the dynamic stiffness method (DSM) for bending-torsion composite beam is used to compute the free vibration natural modes. The main objective of this work is coupling the dynamic stiffness method (DSM) with high fidelity computational fluid dynamics models in order to predict the transonic flutter of composite aircraft wings accurately and efficiently. In addressing the main aim of this study, Euler fluid flow solvers of an open source CFD code called OpenFOAM has been coupled with elastic composite wing, represented by the free vibration modes computed by DSM. The first part of this study is devoted to investigating the free vibration characteristics of two types of aircraft, namely sailplane type and transport airliner type. Two models of each type have been analysed and contrasted, which revealed the significance of the natural modes of aircraft wings and how these modes inherently capture the essential characteristics of the system. Then to validate the CFD code, two pitching and self-sustained two degrees of freedom airfoils under different flow condition have been modelled. The results have been compared against experimental measurements and numerical data from the literature which showed good agreement for the predicted force coefficients. Finally, the model has been extended to study a complete aircraft wing. Both metallic and composite Goland wings have been investigated under a wide range of flow conditions. The composite wing has been investigated using different material coupling values to show their effect on its aeroelastic behaviour. The results showed the significant influence of the material coupling on the aeroelastic characteristics of composite wings.

Motivated by the enlarged design space and additional flexibility offered by the latest advances in manufacturing techniques, especially Additive Manufacturing (AM), this thesis investigates a novel turbine end-wall aerothermal management method with the engineered surface structures, through closely coupled experi-mental and numerical studies. A 90-degree turning duct and a linear turbine cascade test section were employed for the experimental research in a low-speed wind tunnel. Duct and turbine end-wall heat transfer and cooling effectiveness were measured by transient Infrared Thermography. PIV measurement was conducted to obtain the exit flow field. Computational fluid dynamics (CFD) simulations were performed using ANSYS FLUENT to compliment the experimental findings. The flow solver uses the finite volume method to solve the three-dimensional Reynolds-Averaged Navier-Stokes (RANS) equations. The k-ω shear stress transport (SST) turbulence model was validated and chosen for all the numerical studies. The secondary flow control principle of the engineered surface structure in the simplified duct is revealed through a detailed investigation of the flow produced by multiple small surface structures. The CFD and PIV measurement results consistently show that addition of the engineered surface structure on end-wall can effectively reduce the magnitude of streamwise vorticity associated with the secondary flow and alleviate its lift-off motion. For turbine cascade applications, it can be observed that the strength of the passage vortex is effectively reduced, and the passage vortex loss core moves closer to the end-wall with the addition of the engineered surface structure. The purge air cooling enhancement by the engineered surface structure is then studied. The purge air cooling flow becomes more attached to the end-wall and covers a larger wall surface area with the added end-wall rib structures. Both experimental and numerical results reveal a consistent trend on improving film cooling effectiveness and net heat flux reduction (NHFR). This novel concept was success-fully demonstrated in a more realistic turbine cascade case. Enhanced cooling effectiveness and net heat flux reduction were obtained from both experimental data and CFD analysis. The additional surface features were proved to be effective in reducing the passage vortex and providing more coolant coverage without introducing additional aerodynamic loss. The overall Net Heat Load Reduction for the 90-degree turning duct and the turbine cascade is increased by 11% and 2% respectively.

As projected manufacturing rates for commercial aircraft increase to levels of multiple ship sets per day from individual manufacturing facilities, GE Aviation have expressed the need for a shift in composites secondary structure manufacturing philosophy. Traditional manufacturing processes tend to be touch labour intensive and hence costly. The manual placement of large numbers of individual ply profiles, lengthy debulking operations and complex cure cycles, result in excessive component lead times and manufacturing costs. As a result, direct labour cost is a major factor in the total economies of production processes. The implementation of industrial robotics has proved highly successful in automotive manufacturing, and various methods for automating individual aspects of the composites manufacturing process have been suggested. Technical cost modelling has been used to anticipate the production costs of a prototype secondary structure component, as supplied by GE Aviation, through direct simulation of the existing manufacturing process. This work has clearly highlighted the potential for cost and cycle time reductions if process automation can be successfully introduced. Observation of the existing manufacturing process has allowed three alternative manufacturing scenarios to be considered with respect to cost-effectiveness and feasibility, whilst highlighting long term cost benefits. Investigations have been undertaken to identify and evaluate alternative material and processing methodologies ranging from resin infused woven dry fabrics to UD prepreg tape and tow. In addition, candidate processing routes have been systematically evaluated using design of experiments techniques, which focussed on assessing the feasibility and technology readiness of robotic deposition and consolidation methodologies, including pick and place and debulking. Process automation in these areas has the potential for total component cost and cycle time reductions in the order of 2.8 to 21.6 and 0.6 to 63.4 per cent respectively. The quasi-static mechanical testing of a range of face sheet materials has provided a performance assessment based on tensile, compressive and shear properties and laminate Vf. Findings suggest that materials offering increased suitability for automation typically have reduced mechanical performance when compared to candidate prepregs; tensile modulus and strength reductions of 5 and 34 per cent were reported when comparing a 6k woven 2X2 twill fabric and equivalent prepreg respectively. Furthermore, 26 and 4 per cent reductions in tensile modulus and 38 and 40 per cent reductions in tensile strength were observed for 179 and 318gsm UD NCF, when compared with a candidate UD prepreg. Data has also been presented on the effect of varying the traditional consolidation frequency and methodology. While earlier findings suggest that debulking has little effect on the laminate tensile modulus; ply compaction level varies considerably. Furthermore, it has been shown that on-the-fly consolidation, using a robotically mounted, roller-based end effector has the advantages of mechanical performance retention, cycle time reduction and repeatable laminate post cure thickness. In addition, when compared with candidate woven and UD prepreg laminates manufactured using the traditional vacuum bagging approach; equivalent tensile modulus, strength and fibre volume fraction have been observed and with less variability. Handling characteristics inherent to vacuum and needle grippers, including pickup performance, defined as the pickup or holding force required to overcome fabric weight, shear force performance; the maximum force that can be exerted on the fabric before the onset of slip, and the accuracy with which non-rigid-materials (NRMs) can be handled, have also been considered. The achievable positional accuracy of robotically pick and placed prepreg plies greatly exceeds that of dry fabrics in all cases and with less variability, irrespective of the gripping mechanism used. Vacuum grippers exhibit more uniform positional error and increased positional accuracy when handling dry fabrics, whilst needle grippers outperformed the vacuum alternative when handling prepregs, irrespective of form. Robotic pick and place solutions offer low variability in ply positional error with a guaranteed placement accuracy of ±0.8mm and ±2.3mm for prepregs and dry fabrics respectively. Characterisation of the gap type defect and butt and overlapping joining methodologies has provided a performance trend based on ply positional error. Quasi-static mechanical testing has revealed that laminates with equivalent tensile modulus to an un-spliced control could be achieved. However, significant reductions in the tensile strength and an increase in overall laminate thickness and thickness variation highlighted the negative effect of ply splicing on laminate performance. However, it has been shown that a robotic placement accuracy of ±0.8mm gives rise to acceptable tensile strength reductions in candidate prepreg laminates. The up-scaling of laminate level robotic manipulators has been discussed and addressed in conjunction with the commissioning of a flexible robotic manufacturing cell, facilitating the manufacture of full-scale secondary structure aerospace components. Comparisons have been made between a benchmark prepreg panel, manufactured using traditional manual methods and alternative dry fabric and prepreg panels manufactured using increased levels of process automation. In each case, manufacturing feasibility, mechanical performance and component geometric accuracy have been assessed. It has been shown that there are significant advantages to be gained from the implementation of robotic automation within the traditional manufacturing process. Component cost and cycle time reductions, coupled with the processing and performance advantages and increased suitability to automation of woven dry fibre materials are clear. Findings which support a key driver of this project, which seeks to justify alternative dry fabrics as a viable alternative to traditional prepreg broadgoods for the manufacture of secondary structure aerospace components.