Design and analysis of a 2-DoF split-stator induction motor

A two degrees of freedom (2-DOF) actuator capable of producing linear translation, rotary motion, or helical motion would be a desirable asset to the fields of machine tools, robotics, and various apparatuses. In this paper, a novel 2-DOF split-stator induction motor was proposed and electromagnetic structure pa- rameters of the motor were designed and optimized. The feature of the direct-drive 2-DOF induction motor lies in its solid mover ar- rangement. In order to study the complex distribution of the eddy current field on the ferromagnetic cylinder mover and the motor’s operating characteristics, the mathematical model of the proposed motor was established, and characteristics of the motor were ana- lyzed by adopting the permeation depth method (PDM) and finite element method (FEM). The analytical and numerical results from motor simulation clearly show a correlation between the PDM and FEM models. This may be considered as a fair justification for the proposed machine and design tools.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Fe-doped and -mediated graphitic carbon nitride nanosheets for enhanced photocatalytic performance under natural sunlight

Herein, we demonstrate the synthesis of highly efficient Fe-doped graphitic carbon nitride (g-C3N4) nanosheets via a facile and cost effective method. The synthesized Fe-doped g-C3N4 nanosheets were well characterized by various analytical techniques. The results revealed that the Fe exists mainly in the +3 oxidation state in the Fe-doped g-C3N4 nanosheets. Fe doping of g-C3N4 nanosheets has a great influence on the electronic and optical properties. The diffuse reflectance spectra of Fe-doped g-C3N4 nanosheets exhibit red shift and increased absorption in the visible light range, which is highly beneficial for absorbing the visible light in the solar spectrum. More significantly, the Fe-doped g-C3N4 nanosheets exhibit greatly enhanced photocatalytic activity for the degradation of Rhodamine B under sunlight irradiation. The photocatalytic activity of 2 mol% Fe-doped g-C3N4 nanosheets is almost 7 times higher than that of bulk g-C3N4 and 4.5 times higher than that of pure g-C3N4 nanosheets. A proposed mechanism for the enhanced photocatalytic activity of Fe-doped g-C3N4 nanosheets was investigated by trapping experiments. The synthesized photocatalysts are highly stable even after five successive experimental runs. The enhanced photocatalytic performance of Fe-doped g-C3N4 nanosheets is due to high visible light response, large surface area, high charge separation and charge transfer. Therefore, the Fe-doped g-C3N4 photocatalyst is a promising candidate for energy conversion and environmental remediation.

New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance.

Switching patterns and steady-state analysis of grid-connected and stand-alone single-stage boost-inverters for PV applications

Renewable or sustainable energy (SE) sources have attracted the attention of many countries because the power generated is environmentally friendly, and the sources are not subject to the instability of price and availability. This dissertation presents new trends in the DC-AC converters (inverters) used in renewable energy sources, particularly for photovoltaic (PV) energy systems. A review of the existing technologies is performed for both single-phase and three-phase systems, and the pros and cons of the best candidates are investigated. In many modern energy conversion systems, a DC voltage, which is provided from a SE source or energy storage device, must be boosted and converted to an AC voltage with a fixed amplitude and frequency. A novel switching pattern based on the concept of the conventional space-vector pulse-width-modulated (SVPWM) technique is developed for single-stage, boost-inverters using the topology of current source inverters (CSI). The six main switching states, and two zeros, with three switches conducting at any given instant in conventional SVPWM techniques are modified herein into three charging states and six discharging states with only two switches conducting at any given instant. The charging states are necessary in order to boost the DC input voltage. It is demonstrated that the CSI topology in conjunction with the developed switching pattern is capable of providing the required residential AC voltage from a low DC voltage of one PV panel at its rated power for both linear and nonlinear loads. In a micro-grid, the active and reactive power control and consequently voltage regulation is one of the main requirements. Therefore, the capability of the single-stage boost-inverter in controlling the active power and providing the reactive power is investigated. It is demonstrated that the injected active and reactive power can be independently controlled through two modulation indices introduced in the proposed switching algorithm. The system is capable of injecting a desirable level of reactive power, while the maximum power point tracking (MPPT) dictates the desirable active power. The developed switching pattern is experimentally verified through a laboratory scaled three-phase 200W boost-inverter for both grid-connected and stand-alone cases and the results are presented.

Modelagem e análise dinâmica de um sistema de conversão de energia eólica dotado de gerador síncrono de imã permanente utilizando a plataforma ATP

Human development requires a broad balance between ecological, social and economic factors in order to ensure its own sustainability. In this sense, the search for new sources of energy generation, with low deployment and operation costs, which cause the least possible impact to the environment, has been the focus of attention of all society segments. To do so, the reduction in exploration of fossil fuels and the encouragement of using renewable energy resources for distributed generation have proved interesting alternatives to the expansion of the energy matrix of various countries in the world. In this sense, the wind energy has acquired an increasingly significant role, presenting increasing rates of power grid penetration and highlighting technological innovations such as the use of permanent magnet synchronous generators (PMSG). In Brazil, this fact has also been noted and, as a result, the impact of the inclusion of this source in the distribution and sub-transmission power grid has been a major concern of utilities and agents connected to Brazilian electrical sector. Thus, it is relevant the development of appropriate computational tools that allow detailed predictive studies about the dynamic behavior of wind farms, either operating with isolated load, either connected to the main grid, taking also into account the implementation of control strategies for active/reactive power generation and the keeping of adequate levels of voltage and frequency. This work fits in this context since it comprises mathematical and computational developments of a complete wind energy conversion system (WECS) endowed with PMSG using time domain techniques of Alternative Transients Program (ATP), which prides itself a recognized reputation by scientific and academic communities as well as by electricity professionals in Brazil and elsewhere. The modeling procedures performed allowed the elaboration of blocks representing each of the elements of a real WECS, comprising the primary source (the wind), the wind turbine, the PMSG, the frequency converter, the step up transformer, the load composition and the power grid equivalent. Special attention is also given to the implementation of wind turbine control techniques, mainly the pitch control responsible for keeping the generator under the maximum power operation point, and the vector theory that aims at adjusting the active/reactive power flow between the wind turbine and the power grid. Several simulations are performed to investigate the dynamic behavior of the wind farm when subjected to different operating conditions and/or on the occurrence of wind intensity variations. The results have shown the effectiveness of both mathematical and computational modeling developed for the wind turbine and the associated controls.

A New Method for Modeling Free Surface Flows and Fluid-structure Interaction with Ocean Applications

The computational modeling of ocean waves and ocean-faring devices poses numerous challenges. Among these are the need to stably and accurately represent both the fluid-fluid interface between water and air as well as the fluid-structure interfaces arising between solid devices and one or more fluids. As techniques are developed to stably and accurately balance the interactions between fluid and structural solvers at these boundaries, a similarly pressing challenge is the development of algorithms that are massively scalable and capable of performing large-scale three-dimensional simulations on reasonable time scales. This dissertation introduces two separate methods for approaching this problem, with the first focusing on the development of sophisticated fluid-fluid interface representations and the second focusing primarily on scalability and extensibility to higher-order methods.

We begin by introducing the narrow-band gradient-augmented level set method (GALSM) for incompressible multiphase Navier-Stokes flow. This is the first use of the high-order GALSM for a fluid flow application, and its reliability and accuracy in modeling ocean environments is tested extensively. The method demonstrates numerous advantages over the traditional level set method, among these a heightened conservation of fluid volume and the representation of subgrid structures.

Next, we present a finite-volume algorithm for solving the incompressible Euler equations in two and three dimensions in the presence of a flow-driven free surface and a dynamic rigid body. In this development, the chief concerns are efficiency, scalability, and extensibility (to higher-order and truly conservative methods). These priorities informed a number of important choices: The air phase is substituted by a pressure boundary condition in order to greatly reduce the size of the computational domain, a cut-cell finite-volume approach is chosen in order to minimize fluid volume loss and open the door to higher-order methods, and adaptive mesh refinement (AMR) is employed to focus computational effort and make large-scale 3D simulations possible. This algorithm is shown to produce robust and accurate results that are well-suited for the study of ocean waves and the development of wave energy conversion (WEC) devices.

Experimental and Theoretical Models to Probe Mechanisms of Biological Charge Flow

Nature is challenged to move charge efficiently over many length scales. From sub-nm to μm distances, electron-transfer proteins orchestrate energy conversion, storage, and release both inside and outside the cell. Uncovering the detailed mechanisms of biological electron-transfer reactions, which are often coupled to bond-breaking and bond-making events, is essential to designing durable, artificial energy conversion systems that mimic the specificity and efficiency of their natural counterparts. Here, we use theoretical modeling of long-distance charge hopping (Chapter 3), synthetic donor-bridge-acceptor molecules (Chapters 4, 5, and 6), and de novo protein design (Chapters 5 and 6) to investigate general principles that govern light-driven and electrochemically driven electron-transfer reactions in biology. We show that fast, μm-distance charge hopping along bacterial nanowires requires closely packed charge carriers with low reorganization energies (Chapter 3); singlet excited-state electronic polarization of supermolecular electron donors can attenuate intersystem crossing yields to lower-energy, oppositely polarized, donor triplet states (Chapter 4); the effective static dielectric constant of a small (~100 residue) de novo designed 4-helical protein bundle can change upon phototriggering an electron transfer event in the protein interior, providing a means to slow the charge-recombination reaction (Chapter 5); and a tightly-packed de novo designed 4-helix protein bundle can drastically alter charge-transfer driving forces of photo-induced amino acid radical formation in the bundle interior, effectively turning off a light-driven oxidation reaction that occurs in organic solvent (Chapter 6). This work leverages unique insights gleaned from proteins designed from scratch that bind synthetic donor-bridge-acceptor molecules that can also be studied in organic solvents, opening new avenues of exploration into the factors critical for protein control of charge flow in biology.

Développement et caractérisation de dérivés dipyrrométhène pour des applications dans le domaine du photovoltaïque

Ce projet de recherche mené en collaboration industrielle avec St-Jean Photochimie Inc. / PCAS Canada vise le développement et la caractérisation de dérivés dipyrrométhène pour des applications dans le domaine du photovoltaïque. La quête du récoltage des photons se situant dans le proche-infrarouge a été au centre des modifications structurales explorées afin d’augmenter l’efficacité de conversion des cellules solaires de type organique et à pigments photosensibles. Trois familles de composés intégrant le motif dipyrrométhène ont été synthétisées et caractérisées du point de vue spectroscopique, électrochimique, structural ainsi que par modélisation moléculaire afin d’établir des relations structures-propriétés. La première famille comporte six azadipyrrométhènes au potentiel de coordination tétradentate sur des centres métalliques. Le développement d’une nouvelle voie synthétique asymétrique combinée à l’utilisation d’une voie symétrique classique ont permis d’obtenir l’ensemble des combinaisons de substituants possibles sur les aryles proximaux incluant les noyaux 2-hydroxyphényle, 2-méthoxyphényle et 2- pyridyle. La modulation du maximum d’absorption dans le rouge a pu être faite entre 598 et 619 nm. De même, la présence de groupements méthoxyle ou hydroxyle augmente l’absorption dans le violet (~410 nm) tel que démontré par modélisation. La caractérisation électrochimique a montré que les dérivés tétradentates étaient en général moins stables aux processus redox que leur contre-parti bidentate. La deuxième famille comporte dix dérivés BODIPY fusionnés de façon asymétrique en position [b]. L’aryle proximal a été modifié de façon systématique afin de mieux comprendre l’impact des substituents riches en électron et de la fusion de cycles aromatiques. De plus, ces dérivés ont été mis en relation avec une vaste série de composés analogues. Les résultats empiriques ont montré que les propriétés optoélectroniques de la plateforme sont régies par le degré de communication électronique entre l’aryle proximal, le pyrrole sur lequel il est attaché et le noyau indolique adjacent à ce dernier. Les maximums d’absorption dans le rouge sont modulables entre 547 et 628 nm et la fluorescence des composés se situe dans le proche- infrarouge. L’un des composé s’est révélé souhaitable pour une utilisation en photovoltaïque ainsi qu’à titre de sonde à pH. La troisième famille comporte cinq complexes neutres de RuII basés sur des polypyridines et portant un ligand azadipyrrométhène cyclométalé. Les composés ont montré une forte absorption de photons dans la région de 600 à 800 nm (rouge à proche- infrarouge) et qui a pu être étendue au-delà de 1100 nm dans le cas des dérivés portant un ligand terpyridine. L’analyse des propriétés optoélectroniques de façon empirique et théorique a montré un impact significatif de la cyclométalation et ouvert la voie pour leur étude en tant que photosensibilisateurs en OPV et en DSSC. La capacité d’un des complexes à photo-injecter un électron dans la bande de conduction du semi-conducteur TiO2 a été démontré en collaboration avec le groupe du Pr Gerald J. Meyer à University of North Carolina at Chapel Hill, premier pas vers une utilisation dans les cellules solaires à pigments photosensibles. La stabilité des complexes en solution s’est toutefois avérée problématique et des pistes de solutions sont suggérées basées sur les connaissances acquises dans le cadre de cette thèse.

Mesoscale ocean eddy dataset in the Lofoten Basin from Satellite Altimetry

The Lofoten Basin is the most eddy rich region in the Norwegian Sea. In this paper, the characteristics of these eddies are investigated from a comprehensive database of nearly two decades of satellite altimeter data (1995-2013) together with Argo profiling floats and surface drifter data. An automated method identified 1695/1666 individual anticyclonic/cyclonic eddies in the Lofoten Basin from more than 10,000 altimeter-based eddy observations. The eddies are found to be predominantly generated and residing locally. The spatial distributions of lifetime, occurrence, generation sites, size, intensity, and drift of the eddies are studied in detail. The anticyclonic eddies in the Lofoten Basin are the most long-lived eddies (>60 days), especially in the western part of the basin. We reveal two hotspots of eddy occurrence on either side of the Lofoten Basin. Furthermore, we infer a cyclonic drift of eddies in the western Lofoten Basin. Barotropic energy conversion rates reveals energy transfer from the slope current to the eddies during winter. An automated colocation of surface drifters trapped inside the altimeter-based eddies are used to corroborate the orbital speed of the anticyclonic and cyclonic eddies. Moreover, the vertical structure of the altimeter-based eddies is examined using colocated Argo profiling float profiles. Combination of altimetry, Argo floats, and surface drifter data is therefore considered to be a promising observation-based approach for further studies of the role of eddies in transport of heat and biomass from the slope current to the Lofoten Basin.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Development of functionalised multiwalled carbon nanotube/polyaniline composites for electrical applications

Combining intrinsically conducting polymers with carbon nanotubes (CNT) helps in creating composites with superior electrical and thermal characteristics. These composites are capable of replacing metals and semiconductors as they possess unique combination of electrical conductivity, flexibility, stretchability, softness and bio-compatibility. Their potential for use in various organic devices such as super capacitors, printable conductors, optoelectronic devices, sensors, actuators, electrochemical devices, electromagnetic interference shielding, field effect transistors, LEDs, thermoelectrics etc. makes them excellent substitutes for present day semiconductors.However, many of these potential applications have not been fully exploited because of various open–ended challenges. Composites meant for use in organic devices require highly stable conductivity for the longevity of the devices. CNT when incorporated at specific proportions, and with special methods contributes quite positively to this end.The increasing demand for energy and depleting fossil fuel reserves has broadened the scope for research into alternative energy sources. A unique and efficient method for harnessing energy is thermoelectric energy conversion method. Here, heat is converted directly into electricity using a class of materials known as thermoelectric materials. Though polymers have low electrical conductivity and thermo power, their low thermal conductivity favours use as a thermoelectric material. The thermally disconnected, but electrically connected carrier pathways in CNT/Polymer composites can satisfy the so-called “phonon-glass/electron-crystal” property required for thermoelectric materials. Strain sensing is commonly used for monitoring in engineering, medicine, space or ocean research. Polymeric composites are ideal candidates for the manufacture of strain sensors. Conducting elastomeric composites containing CNT are widely used for this application. These CNT/Polymer composites offer resistance change over a large strain range due to the low Young‟s modulus and higher elasticity. They are also capable of covering surfaces with arbitrary curvatures.Due to the high operating frequency and bandwidth of electronic equipments electromagnetic interference (EMI) has attained the tag of an „environmental pollutant‟, affecting other electronic devices as well as living organisms. Among the EMI shielding materials, polymer composites based on carbon nanotubes show great promise. High strength and stiffness, extremely high aspect ratio, and good electrical conductivity of CNT make it a filler of choice for shielding applications. A method for better dispersion, orientation and connectivity of the CNT in polymer matrix is required to enhance conductivity and EMI shielding. This thesis presents a detailed study on the synthesis of functionalised multiwalled carbon nanotube/polyaniline composites and their application in electronic devices. The major areas focused include DC conductivity retention at high temperature, thermoelectric, strain sensing and electromagnetic interference shielding properties, thermogravimetric, dynamic mechanical and tensile analysis in addition to structural and morphological studies.