Multiphase electronically commutated dc machine is a new non-conventional machine and converter topology aimed at dc power generation and delivery systems. This thesis presents a detailed analysis of two multiphase electronically commutated dc machine topologies, firstly, the two level topology then the multilevel topology. Electronic current commutation processes in these topologies are analysed and electrical machine parameters that influence current commutation and the design of the electronic commutator are exposed. The behaviour of the power electronic commutator circuit is shown to be tightly coupled to that of the electrical machine connected to it and to be inductively dominated during current commutation. Performance, efficiency, footprint and cost are all affected by design considerations arising from the interaction of electronic commutator switching devices and electrical machine. Thus there is an incentive to ensure that the designs of power electronic commutator circuits and electrical machines are matched, allowing the requirements of the system as a whole to be satisfied. Since these machine and converter topologies depart from the conventional machine and converter topologies, an alternative modelling approach that lends itself well to modelling of the machine and its associated power electronics is presented. The models are used to evaluate the operational attributes of the machine and its associated electronic commutator power electronic circuit and the proposed control schemes. Results from two prototype laboratory drives built to practically access the viability and fully characterise the operational behavior of these topologies together with the simulation results are presented. Conclusions are drawn concerning the proposed topologies and their associated control strategies.

The demand for high-performance electrochemical energy storage devices is ever-growing as they are critical components for portable electronics, electric vehicles, and efficient storage media for energy from renewable sources. Electrochemical capacitors (also called supercapacitors) are emerging as one of the most promising candidates due to their rapid charge rate, high power density, good rate capability and excellent lifespan. However, their usage is significantly limited by the disadvantages of low energy density. The main aim of this work is to develop advanced electrode materials for supercapacitors with improved energy density while maintaining high power density and long cycle life. In this thesis, we have developed four novel electrode materials based on the transition metals of Ni and Cu for supercapacitor applications, including the metal oxides (Li2Ni2(MoO4)3 and Cu2O/CuMoO4) and metal sulfides (NiMoS4-A and Ni-Cu-S). These materials were prepared via different techniques, such as combustion, chemical co-precipitation and hydrothermal. Their physical properties were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscopy (TEM) etc. Their electrochemical behaviours were evaluated by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and cycling stability etc. To further measure the performance in practical energy storage devices, the materials were tested with a two-electrode configuration. All the four materials were used as positive electrodes, which were paired with proper activated carbon (AC) or nitrogen-doped graphene (NG) negative electrodes to assemble asymmetric supercapacitors (ASCs). At a current density of 1 A g-1, the Cu2O/CuMoO4 electrode exhibits a high specific capacitance of 4264 F g-1, superior to the1137 F g-1 of the Li2Ni2(MoO4)3, 706.5 F g-1 of the NiMoS4-A, and 938.6 F g-1 of the Ni-Cu-S. In terms of the ASCs, the Cu2O/CuMoO4//AC ASC could expand the operation voltage to 1.7 V, at which the energy density can reach 75.1 Wh kg-1 with a power density of 420 W kg-1. The NiMoS4-A//AC ASC displays a high energy density of 35 Wh kg-1 at an average power density of 400 W kg-1. Meanwhile, it exhibits excellent cycle stability, maintaining 82% of the initial capacitance after 10000 charge-discharge cycles at 5 A g-1. These good results suggest that the developed materials are promising for high-performance supercapacitor applications.

As future grids are becoming more decentralised, I study a stand-alone grid where the penetration of wind energy is high, and exploit a joint planning of energy storage and renewable energy source, as this can potentially result in a more economical and efficient energy system. More specifically, I consider an energy system that consists of a gas-fired plant and a small wind farm with a capacity for energy storage. I assume that the gas-fired plant has a maximum generation that is no more than the electricity consumption. I first propose an optimisation model with known wind speed and electricity demand. Then I gradually extend this deterministic model to study the stochastic nature of the wind speed and electricity demand forecasting. Numerical applications in two chosen locations with different characteristics have been provided for demonstration. In the model extension, I compare battery storage with the other storage technologies by modifying the part of the cost functional, charging/discharging capacity and efficiency rate corresponding to the storage. The optimal solution has changed due to different efficiencies, costs and charging/discharging capacities. Compressed air energy storage and pumped hydroelectric storage may have the advantage in cost, but if a big surplus of energy is needed to get charged within a short time period, batteries might be a better choice as flywheels are very expensive. Furthermore, I include carbon emission modelling from the gas-fired plant by applying a carbon tax and a carbon emission cap. In my system, for a carbon tax to have a similar effect in reducing emissions in comparison to a carbon emission cap, it would need to be very high. Finally, I consider the possibility of connecting my system to the National Grid where I import from, or export to, when my system has an electricity shortage or surplus in meeting the demand. The results provide helpful insights in planning a joint deployment of generation capacity and energy storage and show that the system operates more efficiently and economically when it is connected to the National Grid.

This thesis shows both the use of acoustic metamaterials and coded waveforms for Non-Destructive Testing (NDT) applications. The exotic features of the acoustic metamaterials have been exploited for imaging a sub-wavelength object at frequencies into the middle audible – low ultrasonic range, thus beating the so-called diffraction limit. This has been investigated by means of both Finite Element Modelling and a series of experiments. These demonstrate that acoustic metamaterials fabricated using additive manufacturing with a polymer substrate can be used successfully for imaging a subwavelength object within a frequency range that was not previously explored. The experimental setup made use of coded waveform excitation for characterising the performance of these metamaterials in the frequency domain. Such broadband excitations waveforms can be exploited together with advanced signal processing techniques such as Pulse Compression (PuC) to enhance the Signal-to-Noise Ratio (SNR). Hence, a first step toward the realization of an acoustic metamaterial device that can be used with coded waveforms and PuC has been investigated. Parallel research on the optimal use of coded signals with PuC techniques has been carried out. The main characteristics of several widely-used coded waveforms and advanced algorithms have been reported. Their features have been investigated numerically so as to provide a benchmark for choosing an optimal coded waveform and pulse compression algorithm for a given NDT application. In addition, the improvement in inspection capabilities given by these advanced signal processing techniques has been tested using real industrial NDT applications in highly scattering and attenuating samples. This has been done by programming a tailored post-processing/imaging algorithm for each specific application. Furthermore, a portable instrumentation system is described, which is capable of providing a performance comparable to standard bench-top PuC instruments. Finally, an innovative strategy for using coded signals and PuC in active thermography inspection has been investigated. This results in an enhanced defect discrimination in challenging materials with respect to the standard PuC thermography procedure.

The proliferation of the national-wide deployment of surveillance cameras and identity management systems has promoted the development of biometric systems. Gait as a behavioural biometric trait can be measured unobtrusively at a moderate distance, thus it is predominant in remote human tracking and identification tasks. The past two decades have witnessed a considerable development of gait recognition systems. Yet there are challenges that confine the practical application of gait analysis. The motivation of our work is to identify the problems and find corresponding solutions to explore the potentials of gait recognition and promote its applicability in open-world scenarios. Gait recognition systems use human profile as features, while the appearance of human profile, also known as silhouette, can be affected in various manners. For example, clothing changes the shape of torso (coat) or legs (skirt); carrying bag attaches extra region to the silhouette; walking surface or speed variation changes the appearance of legs. On the other hand, camera viewpoint variation changes the shape of both the upper and lower body, while segmentation errors may cause massive corruption of the gait features. We summarise them into two categories: partial interference and holistic deformation. The former has been well addressed by existing literatures. The holistic deformation on gait silhouette results in large intra-class variation, and we notice that the performance of conventional approaches decreases under such circumstance. Thus our work focus mostly on the latter challenge. Accordingly, we propose ViFS, an automatic feature selection approach that seeks for the optimal representation features from gallery set, and evaluate its performance under various conditions. We find that ViFS minimises the intra-class variation between gallery and probe data, and by introducing proper feature enhancers, we can further reduce the number of holistic deformation modalities required in the gallery set. We test the proposed method on public dataset that contains viewpoint variations, and the matching accuracy has achieved 99.1% on CASIA Dataset B and 97.7% on OU-ISIR Large Population Dataset. The formulation and discussion are presented in Chapter 3. The success of Convolutional Neural Network (CNN) based methods in image classification field has drawn attention from researchers. Recently a large number of literatures have covered the application of CNN in computer vision tasks, including face and gait recognition in the biometrics field. CNN has much greater discriminant learning ability in the highly non-linear space. Thus we merge CNN feature maps with the proposed ViFS approach, which achieves the state-of-the-art performance on view-invariant gait recognition problem. The methodology and results are presented in Chapter 4. Among the holistic deformation challenge, the silhouette quality issue is seldom addressed, while no published dataset concerns with the influence of segmentation quality on gait recognition algorithms. We create a dataset that contains silhouettes with six different segmentation qualities in both gallery and probe set, and evaluated the conventional methods as well as the proposed ViFS approach on this dataset. It is proved that ViFS based framework and its extension outperforms the conventional methods by 8%-10%, which further indicates the effectiveness of ViFS based framework on gait holistic deformation challenge. This work is presented in Chapter 5. This thesis aims at tackling the gait silhouette holistic deformation challenge, and ViFS based frameworks are proposed to achieve robust recognition performance. We evaluate the effect of different feature enhancers for ViFS, and find out that the discriminant power of CNN feature maps is much more powerful than subspace learning methods (3% higher accuracy under same conditions), thus it requires less gallery data to achieve deformation-invariant recognition.

Air pollution has become a growing concern around the world. Human exposure to hazardous air pollutants is associated with a range of health problems and increased mortality. An estimated 40,000 early deaths per year are caused by the exposure to air pollutants in the UK alone, which cost over £20 billion annually to individuals and health services1. In this work, novel solidly mounted resonator (SMR) devices were developed for integration in a low-cost, portable air quality monitor for the real-time monitoring of particulate matter and volatile organic compounds (VOCs). Finite element models of the SMRs were developed to aid their design and simulate the response of the sensors to particles and exposure to VOCs. For particle sensing, a SMR based unit was developed, working in a dual mode configuration. The unit was characterised inside an environmental chamber, together with commercial reference instruments, to particles of known size and composition. A detection limit of 20 μg/m3 was found (below the safe exposure limit). To target fine particles (< 2.5 μm), a virtual impactor was incorporated into the system. For VOC detection, the SMR devices were functionalised with polymer coatings to detect acetone and toluene vapours (most common VOCs in air). A polymer drop-coating system was developed to complete this aim (polymer film thicknesses < 100nm). An automated VOC test station was developed to characterise the SMR based sensors to low ppm concentrations of the target vapours (< 200 ppm). The SMR devices demonstrated a limit of detection of 5 ppm to toluene and 50 ppm of acetone (well below the safe exposure limits). A novel CMOS based SMR device, suitable for volume production and monolithic integration, was designed with an integrated microheater and CMOS acoustic mirror. The heater was included to vary the temperature of the sensing area (to enhance the sensitivity of the SMR to a particular VOC through temperature modulation or to clear particles off the surface). The fabricated device (1.9 GHz) exhibited good performance.

Major changes are under way in our power grids. Until very recently, a few hundred, very large, dependable fossil-fuelled power stations were supplying power to consumers whose only role was to use energy whenever they wanted. Today we have wind farms, solar farms, solar panels on millions of roofs, smart metering. Electric vehicles are on the rise and storage technologies are developing rapidly. Achieving a low-carbon, affordable, and secure electricity system, the so-called `energy trilemma,' presents many challenges and opportunities. As energy becomes more dependent on volatile resources such as the wind and sun, flexibility will become increasingly important for maintaining system security at palatable costs. One new source of flexibility could come from domestic appliances. Thermostatically-controlled loads (TCLs), such as fridges, freezers, air-conditioners and hot-water tanks are effectively energy stores that can be adapted to meet the needs of the grid with negligible impact on consumers. By allowing their operating set points to vary (a little) according to the electricity frequency, they could provide a valuable resource to the grid. However, a thorough understanding of their potential to exhibit synchronisation will be needed to understand and mitigate against the potential risks of a decentralised response provider. In this thesis I outline the operation of the electricity grid in Great Britain and describe the existing research into using TCLs for demand-side response. I present a new continuum model for a population of deterministic frequency-sensitive TCLs that is sufficiently tractable to allow for our stability analysis. I also solve for the long-term behaviour of a fully synchronised group of TCLs and analyse its stability to splitting into two groups, and hypothesise about the stability of N groups. Using system data from National Grid, the operation of the GB electricity system is simulated over ten-day periods with, and without, a population of fridges providing frequency response to determine their impact. I find that synchronisation issues should always be expected when the fridge population is identical, but with even very low levels of parameter diversity, such issues are eradicated in our simulations. Given the inherent diversity in a population of TCLs, this research shows that decentralised, deterministic control schemes are a viable option for using TCLs for frequency response, and that such a scheme could provide a valuable resource.

Molecular Communications (MC) is an increasingly attractive technique to enable the communication and networking of devices in environments where traditional communication techniques may not be suitable. MC has been used to convey information in both human society and in animal populations and been studied on both the microscale and the macroscale. On the basis of these studies, this thesis focuses on characterising MC channel models under different environments and examining the impact these models have on the communication performance. The thesis begins by reviewing the latest developments in MC including communication paradigm, channel models, modulation schemes and forward error correction codes. It then provides the comprehensive research methods used during the PhD, including the construction of complex propagation environments and molecular communication equipments, and explains the procedures of the experimentation. The thesis then goes on to analyse the channel model for static environment. A novel capture probability expression of a finite sized receiver and the performance metrics of bit error rate, throughput and round-trip-time are derived. Experimentally, the additive noise in the channel response was found to conform to a Nakagami distribution. Afterwards, the thesis characterises two dynamic channel models, namely, the fading distribution due to temperature fluctuations, which is validated by numerical simulations, and the mobile channel where both transmitter and receiver are in mobility and in order to combat transposition errors, positional-distance codes are applied. Furthermore, the energy model of the bacteria based mobile relay channel is proposed to demonstrate a superior energy efficiency. Finally, the thesis goes on to propose a potential application of MC to locate a hidden entity with an unknown location in a vast underwater search space. Two molecular messaging methods for location discovery are proposed: a chemical encoding messaging method, and a Rosenbrock gradient ascent algorithm. The two chemical methods are found to offer attractive performance trade-offs in complexity and robustness. To conclude, the potential future work on MC channel modelling is identified in complex geometric environments.

Lithium-ion cells are the most commonly used method of energy storage for portable electronics. However, the capacity and power reduces with time and is dependent on usage conditions. This is a challenge for electric vehicle battery packs that are expected to last for up to eight years. Vehicle manufacturers need to understand the causes of this phenomena to accurately predict the vehicles achievable range over its entire lifetime. For automotive manufacturers to tackle this challenge they must know what operating conditions impact cell capacity and power. And, once this has been established, how these operating conditions impact cell capacity and power. Answers to these questions would provide critical information for manufactures; allowing them to mitigate or plan for their impact. In this work, electrical testing was performed across seven cell conditions for between six and thirty months to determine changes in capacity and resistance. Due to the different facility requirements at least one of the following cell chemistries were used for each test, Nickel manganese cobalt (NMC), Nickel Cobalt Aluminium (NCA) and lithium cobalt dioxide (LiCoO2) / all with graphite negative electrodes. State of charge, temperature, current rate during charge, the quantity of the state of charge window utilised and vibration all impacted electrical performance. Cell orientation and external pressure had no effect on cell lifetime. Cell capacity and resistance change over its lifetime is a function of the parasitic chemical reactions occurring within the cell. Understanding how these operating conditions impact cell performance requires a study of the fundamental materials that are at fault. Therefore, materials characterisation of the negative electrode surface film (identified as the primary source of changes to cell capacity and resistance) was performed. Consistency of analytical methods to study this surface film is dependent on the processes of preparation. Those used within literature to open cells, and process the internal cell electrodes led to erroneous results through modification of the surface films chemical properties. A new method is introduced of opening 18650-type cells that is simpler, costs less and stops surface film damage and contamination. In addition, washing electrode surfaces with solvents, which is routinely done within literature, was found to affect the surface film. This work shows that washing can remove surface film and selectively solvate parts of it. It is therefore recommended that washing is not performed. After cell opening, samples were then analysed to determine material changes. A method is introduced to determine the relative surface film thickness (which relates to cell resistance) with x-ray photoelectron spectroscopy that is an improvement on the current method within literature. A wet chemistry method is also shown to selectively remove LiPF6 salt. This makes it possible to use high performance liquid chromatography to study the polymeric species without it reacting with hydrofluoric acid. Using these methods, a relationship is identified between current rate during charge and surface film thickness at the negative electrode up to rates of 4-C. At rates of 6-C and greater the surface film altered chemically. Cell vibration was found to cause the selectively formed film to be replaced with electrolyte reduction products, increasing cell resistance. Subjecting cells to different temperatures and states of charge (SoC) caused different films to form at each temperature. Coupled with electrical performance data, this could be reduced to two. One at 10o C and one at 45o C. SoC was also found to accelerate film formation but not chemically alter it at these two temperatures. Problems with the USABC test for a percentage change in state of charge for lithium-ion cells was identified, but these problems stopped surface film analysis. This work identifies what conditions impact cell performance and their effect on the negative electrode surface film. Changes in the surface film have significant implications on the users of electric-vehicles, most especially the range of the vehicle battery and how that reduces over its lifetime. Such information may directly impact the vehicle warranty, battery size and type of accelerated testing performed to predict cell lifetime. All of these factors represent considerable costs to manufacturers of electric vehicles. Accuracy is therefore of critical importance.

This thesis presents results on the effects of low-temperature gettering processes on minority carrier lifetime in multicrystalline silicon. Wafers are sourced from different height positions of a commercially-grown ingot. The distribution of different key material properties including bulk lifetime, interstitial iron concentration, and dislocation density are characterised and are found to vary widely with ingot height position. Lifetimes are measured by using temporary liquid iodine-ethanol passivation at room temperature or silicon nitride films deposited by plasma-enhanced chemical vapour deposition. Lifetimes are lower in samples from the extrema of ingot than the centre parts. Interstitial iron concentrations are found to be highest in the bottom samples and lowest at the centre of the ingot. Dislocation density is lowest at the bottom of the ingot and increases with ingot height position. In as-grown wafers, low-temperature gettering can improve lifetime substantially in relatively poor samples from the extrema of the ingot. Iodine-ethanol passivation is used to separate thermal effects of annealing from any bulk passivation which may occur during surface passivation from lifetime measurement. The largest relative lifetime improvement (from 5.5 μs to 38.7 μs) is achieved in material from the bottom of the ingot with annealing at 400°C for 35 h. The benefit of low-temperature annealing is marginal for middle samples. Bulk interstitial iron concentrations decrease by up to 2.1 order of magnitude in the bottom samples. The reduction in interstitial iron concentration is not found to be systematically dependent on annealing temperature. For bottom samples a good correlation between the changes in lifetime and interstitial iron concentration is found. The effects of different passivation schemes on low-temperature gettering is also investigated. The results show that starting lifetime and interstitial iron concentration strongly depends on the choice of passivation scheme. The effect of different surface passivation schemes is more pronounced in relatively high lifetime samples. In samples from the bottom of the middle of the wafer, lifetime improves from 113 μs to 171 μs with silicon nitride passivation upon annealing at 400 °C for 25 h. Supporting results from secondary ion mass spectrometry show that substantial concentrations of iron exist in the silicon nitride film after low-temperature annealing. This suggests silicon nitride layer might be an additional gettering centre for interstitial iron. This thesis also studies the effects of low-temperature annealing combined with a standard phosphorus diffusion process to form an emitter. Lifetime in samples from the top and bottom of the ingot can be improved by annealing at 300°C and 400°C even after the phosphorus diffusion process. The largest improvement is from 54 μs to 78 μs upon post-diffusion annealing of bottom samples at 300°C, and the results suggest gettering of impurities other than interstitial iron is likely. The phosphorus diffused emitter layers do not act as effective additional gettering sites for interstitial iron upon low-temperature annealing. The lifetime improvement upon pre-diffusion annealing is retained after the diffusion process. In summary, low-temperature annealing has the potential to improve the lifetime in as-grown multicrystalline silicon and after a phosphorus diffusion gettering under some conditions. Low-temperature annealing thus provides a potential low cost route to improve multicrystalline solar cell efficiencies.