Resonant power conversion topologies for inductive charging of electrical vehicle batteries

This thesis is concerned with inductive charging of electric vehicle batteries. Rectified power form the 50/60 Hz utility feeds a dc-ac converter which delivers high-frequency ac power to the electric vehicle inductive coupling inlet. The inlet configuration has been defined by the Society of Automotive Engineers in Recommended Practice J-1773. This thesis studies converter topologies related to the series resonant converter. When coupled to the vehicle inlet, the frequency-controlled series-resonant converter results in a capacitively-filtered series-parallel LCLC (SP-LCLC) resonant converter topology with zero voltage switching and many other desirable features. A novel time-domain transformation analysis, termed Modal Analysis, is developed, using a state variable transformation, to analyze and characterize this multi-resonant fourth-orderconverter. Next, Fundamental Mode Approximation (FMA) Analysis, based on a voltage-source model of the load, and its novel extension, Rectifier-Compensated FMA (RCFMA) Analysis, are developed and applied to the SP-LCLC converter. The RCFMA Analysis is a simpler and more intuitive analysis than the Modal Analysis, and provides a relatively accurate closed-form solution for the converter behavior. Phase control of the SP-LCLC converter is investigated as a control option. FMA and RCFMA Analyses are used for detailed characterization. The analyses identify areas of operation, which are also validated experimentally, where it is advantageous to phase control the converter. A novel hybrid control scheme is proposed which integrates frequency and phase control and achieves reduced operating frequency range and improved partial-load efficiency. The phase-controlled SP-LCLC converter can also be configured with a parallel load and is an excellent option for the application. The resulting topology implements soft-switching over the entire load range and has high full-load and partial-load efficiencies. RCFMA Analysis is used to analyze and characterize the new converter topology, and good correlation is shown with experimental results. Finally, a novel single-stage power-factor-corrected ac-dc converter is introduced, which uses the current-source characteristic of the SP-LCLC topology to provide power factor correction over a wide output power range from zero to full load. This converter exhibits all the advantageous characteristics of its dc-dc counterpart, with a reduced parts count and cost. Simulation and experimental results verify the operation of the new converter.

Grid integration of wave energy & generic modelling of ocean devices for power system studies

The work presented in this thesis covers four major topics of research related to the grid integration of wave energy. More specifically, the grid impact of a wave farm on the power quality of its local network is investigated. Two estimation methods were developed regarding the flicker level Pst generated by a wave farm in relation to its rated power as well as in relation to the impedance angle ψk of the node in the grid to which it is connected. The electrical design of a typical wave farm design is also studied in terms of minimum rating for three types of costly pieces of equipment, namely the VAr compensator, the submarine cables and the overhead line. The power losses dissipated within the farm's electrical network are also evaluated. The feasibility of transforming a test site into a commercial site of greater rated power is investigated from the perspective of power quality and of cables and overhead line thermal loading. Finally, the generic modelling of ocean devices, referring here to both wave and tidal current devices, is investigated.

Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

Wireless sensor node design for heterogeneous networks

Two complementary wireless sensor nodes for building two-tiered heterogeneous networks are presented. A larger node with a 25 mm by 25 mm size acts as the backbone of the network, and can handle complex data processing. A smaller, cheaper node with a 10 mm by 10 mm size can perform simpler sensor-interfacing tasks. The 25mm node is based on previous work that has been done in the Tyndall National Institute that created a modular wireless sensor node. In this work, a new 25mm module is developed operating in the 433/868 MHz frequency bands, with a range of 3.8 km. The 10mm node is highly miniaturised, while retaining a high level of modularity. It has been designed to support very energy efficient operation for applications with low duty cycles, with a sleep current of 3.3 μA. Both nodes use commercially available components and have low manufacturing costs to allow the construction of large networks. In addition, interface boards for communicating with nodes have been developed for both the 25mm and 10mm nodes. These interface boards provide a USB connection, and support recharging of a Li-ion battery from the USB power supply. This paper discusses the design goals, the design methods, and the resulting implementation.

Addressing non-linear hardware limitations and extending network coverage area for power aware wireless sensor networks

Science Foundation Ireland (07/CE/11147); Irish Research Council for Science Engineering and Technology (Embark Initiative)

Fabrication and characterization of doped and porous silicon nanowires as anodes for lithium ion batteries

By using Si(100) with different dopant type (n++-type (As) or p-type (B)), it is shown how metal-assisted chemically (MAC) etched silicon nanowires (Si NWs) can form with rough outer surfaces around a solid NW core for p-type NWs, and a unique, defined mesoporous structure for highly doped n-type NWs. High resolution electron microscopy techniques were used to define the characteristic roughening and mesoporous structure within the NWs and how such structures can form due to a judicious choice of carrier concentration and dopant type. Control of roughness and internal mesoporosity is demonstrated during the formation of Si NWs from highly doped n-type Si(100) during electroless etching through a systematic investigation of etching parameters (etching time, AgNO3 concentration, %HF and temperature). Raman scattering measurements of the transverse optical phonon confirm quantum size effects and phonon scattering in mesoporous wires associated with the etching condition, including quantum confinement effects for the nanocrystallites of Si comprising the internal structure of the mesoporous NWs. Laser power heating of NWs confirms phonon confinement and scattering from internal mesoporosity causing reduced thermal conductivity. The Li+ insertion and extraction characteristics at n-type and p-type Si(100) electrodes with different carrier density and doping type are investigated by cyclic voltammetry and constant current measurements. The insertion and extraction potentials are demonstrated to vary with cycling and the occurrence of an activation effect is shown in n-type electrodes where the charge capacity and voltammetric currents are found to be much higher than p-type electrodes. X-ray photo-electron spectroscopy (XPS) and Raman scattering demonstrate that highly doped n-type Si(100) retains Li as a silicide and converts to an amorphous phase as a two-step phase conversion process. The findings show the succinct dependence of Li insertion and extraction processes for uniformly doped Si(100) single crystals and how the doping type and its effect on the semiconductor-solution interface dominate Li insertion and extraction, composition, crystallinity changes and charge capacity. The effect of dopant, doping density and porosity of MAC etched Si NWs are investigated. The CV response is shown to change in area (current density) with increasing NW length and in profile shape with a changing porosity of the Si NWs. The CV response also changes with scan rate indicative of a transition from intercalation or alloying reactions, to pseudocapactive charge storage at higher scan rates and for p-type NWs. SEM and TEM show a change in structure of the NWs after Li insertion and extraction due to expansion and contraction of the Si NWs. Galvanostatic measurements show the cycling behavior and the Coulombic efficiency of the Si NWs in comparison to their bulk counterparts.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Electropermanent magnetic anchoring for surgery and endoscopy

The use of magnets for anchoring of instrumentation in minimally invasive surgery and endoscopy has become of increased interest in recent years. Permanent magnets have significant advantages over electromagnets for these applications; larger anchoring and retraction force for comparable size and volume without the need for any external power supply. However, permanent magnets represent a potential hazard in the operating field where inadvertent attraction to surgical instrumentation is often undesirable. The current work proposes an interesting hybrid approach which marries the high forces of permanent magnets with the control of electromagnetic technology including the ability to turn the magnet OFF when necessary. This is achieved through the use of an electropermanent magnet, which is designed for surgical retraction across the abdominal and gastric walls. Our electropermanent magnet, which is hand-held and does not require continuous power, is designed with a center lumen which may be used for trocar or needle insertion. The device in this application has been demonstrated successfully in the porcine model where coupling between an intraluminal ring magnet and our electropermanent magnet facilitated guided insertion of an 18 Fr Tuohy needle for guidewire placement. Subsequent investigations have demonstrated the ability to control the coupling distance of the system alleviating shortcomings with current methods of magnetic coupling due to variation in transabdominal wall thicknesses. With further refinement, the magnet may find application in the anchoring of endoscopic and surgical instrumentation for minimally invasive interventions in the gastrointestinal tract.

Survey on demand side sensitivity to power quality in Ireland

Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

Location dependence of a MEMS electromagnetic transducer with respect to an AC power source

A MEMS, silicon based device with a cantilever oscillationsand an integrated magnet is presented for magnetic to electrical transduction. The cantilever structure can be configured either as an energy harvester to harvest power from an AC power line or as an AC current sensor. The positioning of the transducer with respect to the AC conductor is critical in both scenarios. For the energy scavenger, correct positioning is required to optimize the harvested power. For the current sensor, it is necessary to optimise the sensitivity of the sensor. This paper considers the effect of the relative position of the transducer with respect to the wire on the resulting electromagnetic forces and torques driving the device. It is shown here that the magnetic torque acting on a cantilever beam with an integrated magnet and in the vicinity of an alternating electromagnetic field is a very significant driver of the cantilever oscillations.