The interconnection of multiple oshore renewable energy sources to form a network and maximise their availability requires a method for controlling the transportation of bulk electrical energy. For the distances considered, and as a result of the capacitive nature of HVAC cables, HVDC is the most likely technology for meeting these bulk transport requirements. This research investigates the development of an MMC based Dual Active Bridge (DAB) for interfacing two different parts of a HVDC network. Computational tools are developed in order to design and evaluate such a power electronics structure as well as to support the design process of the transformer required for scaling and matching voltages between the two parts of the network. Linear control techniques are applied to control the converter to operate at the required average capacitor voltage level and power transmission. Simulation results, supported by experimental data from a low voltage MMC prototype are presented to validate the approaches.

The key motivation of this study is to investigate the potential of graphene/metal oxides nanocomposites as electrodes for electrochemical capacitor applications. It is envisioned that the positive synergistic effect between graphene and metal oxides (where novel graphene material acts as a highly conductive platform for ease of ion transfer kinetics and metal oxide acts as spacers to avoid the restacking of graphene sheets to make available more active surface areas) results in excellent electrode material for high performance electrochemical capacitor. In this thesis, a series of hybrid composites comprising of graphene and low cost transition metal oxides were synthesised and characterised for their potential as electrode for electrochemical capacitor applications. In order to achieve this, the graphene used in the preparation of the hybrid composites was successfully synthesised from highly pyrolytic graphene in a proper ratio of ethanol and water before the integration of the metal oxides via a solvothermal route. A parametric study was carried out in a step by step approach to validate the success of the composite synthesis before the electrochemical stage. X-ray Diffraction, Field emission and Transmission scanning electron microscopy, energy-dispersive X-ray and Raman spectroscopy, cyclic voltammetry and galvanostatic charge/discharge tests were used to verify the integrity of the as-produced graphene/metal oxide composites and their applicability to electrochemical capacitors. Upon the completion of the experimental work, the electrochemical tests demonstrated that the introduction of graphene to the metal oxide improved the electrochemical performance in-terms of capacitance, energy density, power density, equivalent series resistance and cycling stability. The results also indicated that the ratio of graphene to metal-oxide plays a significant role in the electrochemical performance of the composite. In comparison with the different graphene/Zinc oxide (ZnO) nanocomposites studied, the electrode material with a weight ratio of 1:8 (graphene: ZnO) displayed a specific capacitance of 236 F/g at a scan rate of 10 mV/s with energy and power densities of 11.80 Wh/kg and 42.48 kW/kg respectively. The specific capacitance of the graphene-Manganese oxide (MnO2) composite electrode material with a weight ratio of 1:16 (graphene: MnO2) demonstrated the best performance of 380 F/g at a scan rate of 5 mV/s among the four ratios studied. The G1Co4 composite electrode with a weight ratio of 1:8 (graphene: Co3O4) demonstrated a superior specific capacitance of 384 F/g at a current density of 0.3 A/g coupled with retention of 80% of its capacitance after 1000 cycles among the graphene-cobalt composites. The Graphene-Nickel cobaltite composite electrode with weight ratio of 1:8 (graphene: NiCo2O4) labelled G-8NC2 displayed a superior specific capacitance (698 F/g at a current density of 0.5 A/g) and good cycling stability (74% capacity retention after 5000 cycles at current density of 1 A/g). The 1:8 ratio exhibited well attached Nickel molybdate nanorods on the surface and edges of the graphene sheets with the highest specific capacitance of 670 F/g at 0.3 A/g, as compared to other tested composites. The significance of these findings details a synthesis route that provides an effective, simple and practical method of preparing graphene-metal oxide composite materials for electrochemical capacitor applications.

Over the last decade, advancement of microelectronics has triggered a growing interest in ambient energy harvesting. Ambient energy can be found in various forms such as: thermoelectric, acoustic, solar, and mechanical vibrations. Most of the stated ambient energy sources have been thoroughly investigated. One of the relatively unexplored ambient energy sources is raindrop impact energy. Raindrop impact energy harvesting is achieved by converting the strain induced by an impinging raindrop on a piezoelectric beam into usable electrical energy. Most of the conducted research from the literature only considered single droplet impact on a piezoelectric beam. More interestingly, actual field test has yet to be conducted. These are the areas that the research will cover. A commercial piezoelectric beam (Mide-v25w) is utilised for this research. In this work, the piezoelectric beam is modelled as a distributed parameter system. To describe the post impact behaviours and water layer formed on the piezoelectric beam, impact coefficient and added mass coefficient are introduced for respective cases. Excitation models for single droplet, multiple droplet, artificial rain, and actual rain are developed. The models presented here were validated via experimental results. A hybrid bridge rectifier is designed and tested under actual rain. Experiment results showed that the half bridge rectifier is able to produce 95.12 % more energy than the full bridge rectifier during low voltage operation. From the actual rain experiment, the raindrop impact energy harvester was able to produce 1564 µJ energy over a rain period of 3539 s. The maximum instantaneous power generated by the piezoelectric was found to be 3.75 mW. This is higher compared the highest instantaneous power recorded in the literatures, which was 23 µW.

Current Non Destructing Testing (NDT) techniques for oil and gas pipeline inspection are accurate and reliable but there are limited numbers of continuous monitoring technique available that can automatically make real-time decisions on the status of the pipeline. Furthermore, most of the NDT methods are deployed at predetermined interval which can last for several months. Sudden onsets of defects are undetected and lead to pipeline failure and unscheduled shutdown. A reliable inspection method is required whereby the pipelines are monitored continuously and are able to provide the operators sufficient time to plan and organize shutdowns. In order to implement this, a continuous monitoring technique is needed which can detect defects automatically with minimal human intervention. Support Vector Machine (SVM) is a powerful machine learning technique for classification, however, the training phase requires batch data to find a model and this is not feasible for a continuous NDT system. This thesis proposes a novel method where the SVM training phase is able to find a model from the incremental dataset acquired from Long Range Ultrasonic Testing (LRUT) system. Results show that this method has comparable accuracy compared to the batch data method. Traditionally, SVM training data is labeled by an expert, however in a continuous monitoring NDT, it is not practical to assign an expert to label the continuously acquired data. Therefore, a novel unsupervised training technique is proposed. The technique is able to cluster the acquired data into a few clusters accurately. The performance of the proposed technique is compared to Self Organizing Map (SOM) method and shows better results. This thesis also proposes a novel method to implement a Genetic Algorithm (GA) as the Quadratic Programming (QP) solver in the SVM efficiently. Conventional SVM implement Sequential Minimal Optimization (SMO) which requires that the data be sparse for optimal operation. The performance of the method is evaluated and shows comparable result to traditional methods. As such, this thesis provides the framework to perform unsupervised continuous monitoring for oil and gas pipelines using LRUT in real time.

Over the last few years, significant advancements in the SiC power MOSFET fabrication technology has led to their wide commercial availability from various manufacturers. As a result, they have now transitioned from being a research activity to becoming an industrial reality. SiC power MOSFET technology offers great benefits in the electrical energy conversion domain which have been widely discussed and partially demonstrated. Superior material properties of SiC and the consequent advantages are both later discussed here. For any new device technology to be widely implemented in power electronics applications, it’s crucial to thoroughly investigate and then validate for robustness, reliability and electrical parameter stability requirements set by the industry. This thesis focuses on device characterisation of state-of-the-art SiC power MOSFETs from different manufacturers during short circuit and avalanche breakdown operation modes under a wide range of operating conditions. The functional characterisation of packaged DUTs was thoroughly performed outside of the safe operating area up until failure test conditions to obtain absolute device limitations. For structural characterisation, Infrared thermography on bare die DUTs was also performed with an aim to observe hotspots and/or degradation of the structural features of the device. The experimental results are also complemented by 2D TCAD simulation results in order to get a further insight into the underlying physical mechanisms behind failure during such operation regimes. Moreover, the DUTs were also tested for body diode characterisation with an aim to observe degradation and instability of electrical device parameters which may adversely affect the performance of the overall system. Such investigations are really important and act as a feedback to device manufacturers for further technological improvements in order to overcome the highlighted issues with an aim to bring about advancements in device design to meet the ever-increasing demands of power electronics.

Power electronics is an enabler for the low-carbon economy, delivering flexible and efficient control and conversion of electrical energy in support of renewable energy technologies, transport electrification and smart grids. Reduced costs, increased efficiency and high power densities are the main drivers for future power electronic systems, demanding innovation in materials, component technologies, converter architectures and control. Power electronic systems utilise semiconductor switches and energy storage devices, such as capacitors and inductors to realise their primary function of energy conversion. Presently, roughly 50% of the volume of a typical power electronic converter is taken up by the energy storage components, so reducing their weight and volume can help to reduce overall costs and increase power densities. In addition, the energy storage densities of inductors are typically much lower than those of capacitors, providing a compelling incentive to investigate techniques for improvement. The main goal of this research was to improve the design of an inductor in order to achieve higher energy densities by combining significantly increased current densities in the inductor windings with the ability to limit the temperature increase of the inductor through a highly effective cooling system. Through careful optimisation of the magnetic, electrical and thermal design a current density of 46 A/mm2 was shown to be sustainable, yielding an energy storage density of 0.537 J/ kg. A principal target for this enhanced inductor technology was to achieve a high enough energy density to enable it to be readily integrated within a power module and so take a step towards a fully-integrated “converter in package” concept. The research included the influence of the operating dc current, current ripple, airgap location and operating frequency on the inductor design and its resulting characteristics. High frequency analysis was performed using an improved equivalent circuit, allowing the physical structure of the inductor to be directly related to the circuit parameters. These studies were validated by detailed small-signal ac measurements. The large signal characteristics of the inductor were determined under conditions of triangular, high-frequency current as a function of frequency, current (flux) ripple amplitude and dc bias current (flux) and a model developed allowing the inductor losses to be predicted under typical power electronic operating conditions.

The growing demands for electrical capacity on future more electric aircraft (MEA) has led the engine-based generators to increase in size. Many manufacturers and researchers have a strong interest in developing fuel cells for aerospace applications due to their advantage of high efficiency and their use as a medium for clean energy resources. A particular interest is in using fuel cells within the Auxiliary Power Unit (APU) - a function that is currently provided by an additional gas turbine in most aircraft. Their integration into aircraft systems is not straightforward. A particular challenge, which this thesis addresses, is the provision of a suitable power conversion system which is able to interface the fuel cell to the aircraft electrical system – taking account of the complex electrical characteristics of the fuel cell and the demanding requirements of the aircraft electrical network. The interleaved boost converter with coupled inductors (IBCI) is one of the many converters that is promising for fuel cell applications because it has low input current ripple and a high step-up voltage gain. It comprises a current doubler circuit, voltage doubler rectifier, coupled inductor and active clamp. The proposed converter is an extended version of the single phase to multiphase IBCI converter using interleaving techniques. The input stage of the converter is a coupled inductor which connected to a half-bridge configuration and an active clamp. The output side is a voltage doubler rectifier. A detailed analysis of the converter and associated modelling are presented. The design and construction of a prototype converter is presented with a particular focus on ensuring operability of the converter over the entire fuel cell characteristic range as well as achieving high efficiency at nominal load. A laboratory-scale (1/10) prototype of a nominal full-scale converter was built to verify the feasibility of the proposed converter topology. Good agreement between the experimental results and the simulation results has been demonstrated, which validates the converter design, modelling, and effectiveness of the efficiency evaluation approximations.

This dissertation reports the research work that was conducted to propose a non-volatile architecture for FPGA using resistive switching devices. This is achieved by designing a Configurable Memristive Logic Block (CMLB). The CMLB comprises of memristive logic cells (MLC) interconnected to each other using memristive switch matrices. In the MLC, novel memristive D flip-flop (MDFF), 6-bit non-volatile look-up table (NVLUT), and CMOS-based multiplexers are used. Other than the MDFF, a non-volatile D-latch (NVDL) was also designed. The MDFF and the NVDL are proposed to replace CMOS-based D flip-flops and D-latches to improve energy consumption. The CMLB shows a reduction of 8.6% of device area and 1.094 times lesser critical path delay against the SRAM-based FPGA architecture. Against similar CMOS-based circuits, the MDFF provides switching speed of 1.08 times faster; the NVLUT reduces power consumption by 6.25nW and improves device area by 128 transistors; while the memristive logic cells reduce overall device area by 60.416μm2. The NVLUT is constructed using novel 2TG1M memory cells, which has the fastest switching times of 12.14ns, compared to other similar memristive memory cells. This is due to the usage of transmission gates which improves voltage transfer from input to the memristor. The novel 2TG1M memory cell also has lower energy consumption than the CMOS-based 6T SRAM cell. The memristive-based switch matrices that interconnects the MLCs together comprises of novel 7T1M SRAM cells, which has the lowest energy-delay-area-product value of 1.61 among other memristive SRAM cells. Two memristive logic gates (MLG) were also designed (OR and AND), that introduces non-volatility into conventional logic gates. All the above circuits and design simulations were performed on an enhanced SPICE memristor model, which was improved from a previously published memristor model. The previously published memristor model was fault to not be in good agreement with memristor theory and the physical model of memristors. Therefore, the enhanced SPICE memristor model provides a memristor model which is in good agreement with the memristor theory and the physical model of memristors, which is used throughout this research work.

The rise and consolidation of Additive Manufacturing (AM) as a technology has made possible the fabrication of highly customised and complex products in almost every industry. This not only allows the creation of objects that were impossible just a few decades ago but also facilitates the production of small runs of products at a reasonable cost, which reduces the design-prototyping cycles and boosts product innovation. However, to produce truly functional parts it is desirable for these systems to be able to deposit multiple complex materials in a single process to locally embed controllable properties such as electrical conductivity or sensing capabilities into the produced geometries. Consequently, a review of current AM technologies capable of depositing conductive materials is performed in this PhD and discussed to find the most suitable approaches. Similarly, existing multi-material set-ups are studied to find limitations and common practices to create a system that is capable of fulfilling the objectives of this work. Piezo-activated inkjet printing (PIJ) is identified as an appropriate technology for multi-material applications due to its non-contact nature, high spatial resolution, capability of mixing and digitally grading materials and simple scale-up of the process. Furthermore, in the last decade it has been shown that jetting can be used for the accurate deposition of a wide range of functional materials. However, upon detailed review of this method, the limitations that it imposes on the compositions of the inks are identified as its main drawback. Specifically, the solid content and molecular weight of the fluids that can be jetted are restricted by the viscosity of the final ink, typically under 40 mPa·s. This is problematic in the case of jetting conductive materials, since it forces the solid content to be very low, therefore yielding very thin and often inhomogeneous layers. Additionally, all the organic components on the inks added to facilitate its ejection need to be removed, which typically means longer and more aggressive post-processes before rendering the printed tracks conductive. For this reason, drop-on-demand micro-dispensing valves were chosen as a high viscosity jetting (HVJ) approach in this work, with the intention of assessing their capability as a suitable tool for multi-material AM of functional inks. However, since their resolution and speed are lower than conventional inkjet, a hybrid approach is presented including micro-dispensing valves and inkjet printheads capable of depositing a wide range of viscosities in a single process. A comprehensive description of the hybrid set-up is given, discussing its main elements including the printing heads, the custom design printer assembly, the ultraviolet (UV) and infrared (IR) lamps installed for in-situ processing, the monitoring system and the set-up to measure the evolution of the electrical resistance in printed tracks in real time during post-processing. Additionally, the printing strategy and process flow is discussed. The investigated set-up was used to study the printability and performance of several functional materials ranging from UV-curable polymers to conductive formulations such as carbon paint, a silver nanoparticle-based paste and a dispersion of PEDOT:PSS. Each material was thoroughly characterised prior to printing with a special focus on viscosity. Their drop formation and deposition processes were studied at different printing settings using high speed imaging and footprint analysis of the deposited drops. These tests were used to obtain sets of working parameters that allow reliable printing and were used to produce 2D patterns with different resolutions to find the drop spacing that results in flat homogeneous films. Later, these films were post-treated according to the requirements of each material and multilayer structures were produced and analysed with an optical profilometer. The cross-section of these 3D tracks was used together with the measured resistance to obtain the electric conductivity of the materials under the printing conditions used. Finally, the accumulated information during the previous stages of printing was used to produce 3D multi-material demonstrators with incorporated conductive tracks, electric components and electroluminescent elements. These proof-of-concept samples were used to discuss limitations of the approach and showcase future possibilities of the system.

Attaching micro-channel heat sinks operating under flow boiling conditions on heat sources of electronic components is an efficient cooling technique which still requires further improvements of designs. When developing this system, the efficient heat transfer performance is essential, however, this development often entangles with difficulties. The difficulties arise as existing prediction approaches are underdeveloped and inadequate to perform the accurate prediction in wide ranges of operating conditions. This inadequacy persists due to incomplete discoveries of involved mechanisms that involve fluid and dynamics for the heat transfer during the flow boiling. Also, the mechanisms involved in the flow boiling process are complicated, hindering the development of more reliable approaches. By addressing this issue, this study explores and investigates the relating mechanisms. The mechanisms of fluids during the flow boiling of subcooled liquids in micro-channel heat sinks immediately before and during the nucleation of first bubbles were explored in this study. This study then addressed the mechanisms of heat transfer enhancement of flow boiling. Later, this study repeated with different substrate materials of micro-channel heat sinks and working fluids. This study serves the purpose to better understand the involved mechanisms during the flow boiling of subcooled liquids in micro-channel heat sinks for the development of more reliable approaches to predict the heat transfer. This study regarding the mechanisms during the flow boiling in micro-channel heat sinks implemented the numerical model associated with the Volume of Fluid (VOF) in which corresponding governing equations were solved using a computational fluid dynamics (CFD). In this model, computational domains of micro-channel heat sinks in three dimensions that include the sub-domains of solids and fluid were created to consider the conjugate heat transfer for better estimation of data. The data collected in this study were from operating parameters of heat flux, mass flux, and inlet temperature of the micro-channel at 500-3197 kW/m2, 115-389 kg/m2 s, and 23-53°C, respectively. The micro-channel heat sinks operated at the atmospheric pressure, and the corresponding substrate materials chosen were steel, silicon, aluminium and copper, and working fluids selected were water and ethanol. The numerical results agree well with the experimental data from the previous study. The results show that although the bubble nucleation is absent, the heat transfer mechanisms in micro-channels possesses the nucleate boiling characteristic involving the transient conduction with the existence of the phase change process. The heat transfer mechanisms from the phase change process with the incomplete evaporation induce the ascending and descending flows and liquid-vapour mixture on the heating surfaces. From the results, four different modes of heat transfer mechanisms from the phase change process associated with ascending and descending flows and liquid vapour mixture become apparent. The ascending and descending flows on the heating surfaces appear with local increases of pressure gradients near to the heating surfaces facilitating the heat transfer enhancement due to phase change. On the other hand, the liquid-vapour mixture produced from the phase change process impeding the heat transfer. In overall, the heat transfer enhancement due to the phase change at the side surfaces in the micro-channel is more extensive as compared to the bottom surface for each condition tested in this study. Meanwhile, the amount of the liquid-vapour mixture accumulating on the bottom surface is more massive as compared to the side surfaces, leading to the impedance of the heat transfer. These heat transfer mechanisms also persist during flow boiling in micro-channels. The heat transfer enhancement due to phase change from the side and bottom surfaces also varies when employing different operating conditions before and during flow boiling. This study provides better insights for researchers and designers in industries regarding the local mechanisms for the heat transfer during the flow boiling in micro-channel heat sinks. These understandings assist the researchers to develop the more reliable prediction methods to design new and better heat transfer performance of micro-channel heat sinks and avoid repeating experiments which are costly and tedious in procedures.