Modeling and identification of power electronic converters

Nowadays, many industries are moving towards more electrical systems and components. This is done with the purpose of enhancing the efficiency of their systems while being environmentally friendlier and sustainable. Therefore, the development of power electronic systems is one of the most important points of this transition. Many manufacturers have improved their equipment and processes in order to satisfy the new necessities of the industries (aircraft, automotive, aerospace, telecommunication, etc.). For the particular case of the More Electric Aircraft (MEA), there are several power converters, inverters and filters that are usually acquired from different manufacturers. These are switched mode power converters that feed multiple loads, being a critical element in the transmission systems. In some cases, these manufacturers do not provide the sufficient information regarding the functionality of the devices such as DC/DC power converters, rectifiers, inverters or filters. Consequently, there is the need to model and identify the performance of these components to allow the aforementioned industries to develop models for the design stage, for predictive maintenance, for detecting possible failures modes, and to have a better control over the electrical system. Thus, the main objective of this thesis is to develop models that are able to describe the behavior of power electronic converters, whose parameters and/or topology are unknown. The algorithms must be replicable and they should work in other types of converters that are used in the power electronics field. The thesis is divided in two main cores, which are the parameter identification for white-box models and the black-box modeling of power electronics devices. The proposed approaches are based on optimization algorithms and deep learning techniques that use non-intrusive measurements to obtain a set of parameters or generate a model, respectively. In both cases, the algorithms are trained and tested using real data gathered from converters used in aircrafts and electric vehicles. This thesis also presents how the proposed methodologies can be applied to more complex power systems and for prognostics tasks. Concluding, this thesis aims to provide algorithms that allow industries to obtain realistic and accurate models of the components that they are using in their electrical systems.En la actualidad, el uso de sistemas y componentes eléctricos complejos se extiende a múltiples sectores industriales. Esto se hace con el propósito de mejorar su eficiencia y, en consecuencia, ser más sostenibles y amigables con el medio ambiente. Por tanto, el desarrollo de sistemas electrónicos de potencia es uno de los puntos más importantes de esta transición. Muchos fabricantes han mejorado sus equipos y procesos para satisfacer las nuevas necesidades de las industrias (aeronáutica, automotriz, aeroespacial, telecomunicaciones, etc.). Para el caso particular de los aviones más eléctricos (MEA, por sus siglas en inglés), existen varios convertidores de potencia, inversores y filtros que suelen adquirirse a diferentes fabricantes. Se trata de convertidores de potencia de modo conmutado que alimentan múltiples cargas, siendo un elemento crítico en los sistemas de transmisión. En algunos casos, estos fabricantes no proporcionan la información suficiente sobre la funcionalidad de los dispositivos como convertidores de potencia DC-DC, rectificadores, inversores o filtros. En consecuencia, existe la necesidad de modelar e identificar el desempeño de estos componentes para permitir que las industrias mencionadas desarrollan modelos para la etapa de diseño, para el mantenimiento predictivo, para la detección de posibles modos de fallas y para tener un mejor control del sistema eléctrico. Así, el principal objetivo de esta tesis es desarrollar modelos que sean capaces de describir el comportamiento de un convertidor de potencia, cuyos parámetros y/o topología se desconocen. Los algoritmos deben ser replicables y deben funcionar en otro tipo de convertidores que se utilizan en el campo de la electrónica de potencia. La tesis se divide en dos núcleos principales, que son la identificación de parámetros de los convertidores y el modelado de caja negra (black-box) de dispositivos electrónicos de potencia. Los enfoques propuestos se basan en algoritmos de optimización y técnicas de aprendizaje profundo que utilizan mediciones no intrusivas de las tensiones y corrientes de los convertidores para obtener un conjunto de parámetros o generar un modelo, respectivamente. En ambos casos, los algoritmos se entrenan y prueban utilizando datos reales recopilados de convertidores utilizados en aviones y vehículos eléctricos. Esta tesis también presenta cómo las metodologías propuestas se pueden aplicar a sistemas eléctricos más complejos y para tareas de diagnóstico. En conclusión, esta tesis tiene como objetivo proporcionar algoritmos que permitan a las industrias obtener modelos realistas y precisos de los componentes que están utilizando en sus sistemas eléctricos.Postprint (published version

Measurements, Models, Systems and Design

531 s.

Communication and energy delivery architectures for personal medical devices

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 219-232).Advances in sensor technologies and integrated electronics are revolutionizing how humans access and receive healthcare. However, many envisioned wearable or implantable systems are not deployable in practice due to high energy consumption and anatomically-limited size constraints, necessitating large form-factors for external devices, or eventual surgical re-implantation procedures for in-vivo applications. Since communication and energy-management sub-systems often dominate the power budgets of personal biomedical devices, this thesis explores alternative usecases, system architectures, and circuit solutions to reduce their energy burden. For wearable applications, a system-on-chip is designed that both communicates and delivers power over an eTextiles network. The transmitter and receiver front-ends are at least an order of magnitude more efficient than conventional body-area networks. For implantable applications, two separate systems are proposed that avoid reimplantation requirements. The first system extracts energy from the endocochlear potential, an electrochemical gradient found naturally within the inner-ear of mammals, in order to power a wireless sensor. Since extractable energy levels are limited, novel sensing, communication, and energy management solutions are proposed that leverage duty-cycling to achieve enabling power consumptions that are at least an order of magnitude lower than previous work. Clinical measurements show the first system demonstrated to sustain itself with a mammalian-generated electrochemical potential operating as the only source of energy into the system. The second system leverages the essentially unlimited number of re-charge cycles offered by ultracapacitors. To ease patient usability, a rapid wireless capacitor charging architecture is proposed that employs a multi-tapped secondary inductive coil to provide charging times that are significantly faster than conventional approaches.by Patrick Philip Mercier.Ph.D

Low Frequency Electric Field Imaging

abstract: Electric field imaging allows for a low cost, compact, non-invasive, non-ionizing alternative to other methods of imaging. It has many promising industrial applications including security, safely imaging power lines at construction sites, finding sources of electromagnetic interference, geo-prospecting, and medical imaging. The work presented in this dissertation concerns low frequency electric field imaging: the physics, hardware, and various methods of achieving it. Electric fields have historically been notoriously difficult to work with due to how intrinsically noisy the data is in electric field sensors. As a first contribution, an in-depth study demonstrates just how prevalent electric field noise is. In field tests, various cables were placed underneath power lines. Despite being shielded, the 60 Hz power line signal readily penetrated several types of cables. The challenges of high noise levels were largely addressed by connecting the output of an electric field sensor to a lock-in amplifier. Using the more accurate means of collecting electric field data, D-dot sensors were arrayed in a compact grid to resolve electric field images as a second contribution. This imager has successfully captured electric field images of live concealed wires and electromagnetic interference. An active method was developed as a third contribution. In this method, distortions created by objects when placed in a known electric field are read. This expands the domain of what can be imaged because the object does not need to be a time-varying electric field source. Images of dielectrics (e.g. bodies of water) and DC wires were captured using this new method. The final contribution uses a collection of one-dimensional electric field images, i.e. projections, to reconstruct a two-dimensional image. This was achieved using algorithms based in computed tomography such as filtered backprojection. An algebraic approach was also used to enforce sparsity regularization with the L1 norm, further improving the quality of some images.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Low-Power Energy Efficient Circuit Techniques for Small IoT Systems

Although the improvement in circuit speed has been limited in recent years, there has been increased focus on the internet of things (IoT) as technology scaling has decreased circuit size, power usage and cost. This trend has led to the development of many small sensor systems with affordable costs and diverse functions, offering people convenient connection with and control over their surroundings. This dissertation discusses the major challenges and their solutions in realizing small IoT systems, focusing on non-digital blocks, such as power converters and analog sensing blocks, which have difficulty in following the traditional scaling trends of digital circuits. To accommodate the limited energy storage and harvesting capacity of small IoT systems, this dissertation presents an energy harvester and voltage regulators with low quiescent power and good efficiency in ultra-low power ranges. Switched-capacitor-based converters with wide-range energy-efficient voltage-controlled oscillators assisted by power-efficient self-oscillating voltage doublers and new cascaded converter topologies for more conversion ratio configurability achieve efficient power conversion down to several nanowatts. To further improve the power efficiency of these systems, analog circuits essential to most wireless IoT systems are also discussed and improved. A capacitance-to-digital sensor interface and a clocked comparator design are improved by their digital-like implementation and operation in phase and frequency domain. Thanks to the removal of large passive elements and complex analog blocks, both designs achieve excellent area reduction while maintaining state-of-art energy efficiencies. Finally, a technique for removing dynamic voltage and temperature variations is presented as smaller circuits in advanced technologies are more vulnerable to these variations. A 2-D simultaneous feedback control using an on-chip oven control locks the supply voltage and temperature of a small on-chip domain and protects circuits in this locked domain from external voltage and temperature changes, demonstrating 0.0066 V/V and 0.013 °C/°C sensitivities to external changes. Simple digital implementation of the sensors and most parts of the control loops allows robust operation within wide voltage and temperature ranges.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138743/1/wanyeong_1.pd

Developing Energy Harvest Efficient Strategies with Microbial Fuel Cells

Nowadays, thinking of energetic efficiency is to determine how to decrease consumption and to reuse resources. This is a major concern when addressing hydric resources. The consumption of drinking water is seeing an unaffordable growth and, although most of it is replenished to the environment, the water quality is affected by pollutants and impurities. As such, using wastewater, a by-product of our routine and way of life, as resource is an asset. Even more when thinking about the heightened energy costs of a wastewater treatment station. The hypotheses of this work show how to achieve this goal by using microbial fuel cells. The organic composition of this water increases its energy production potential, where the bacterial metabolism can be used to, simultaneously, produce energy and help to clean the water. This document is divided in 5 chapters. The strategic positioning of the theme happens in chapter 1. Chapter 2 explains how the main elements of microbial fuel cell technology can work and determine its operation. In chapter 3, the power management systems used with microbial fuel cells are presented and discussed, with the identification of optimization strategies. The second-to-last chapter corresponds to the experimental results discussion and validation, while focusing improved energy production efficiencies. The outputs of this chapter pilot the future work analysis on chapter 5, together with the main conclusions and research trends. The validity and usefulness of this work is cleared with an application example.Pensar em economia energética é, hoje, considerar soluções para a redução de consumo e reutilização de recursos. Esta preocupação é importante ao examinar a utilização dos recursos hídricos. O consumo de água potável está a crescer insustentavelmente e, apesar de grande parte desse consumo ser restituído ao meio ambiente, a qualidade da água é afetada por poluentes ou impurezas. A utilização de água residual, um produto da nossa rotina e qualidade de vida, como um recurso é, por isso, uma mais valia. É ainda mais evidente ao considerar os elevados consumos energéticos de uma estação de tratamento de água residual. As hipóteses abordadas neste trabalho mostram como é possível atingir este objetivo usando células microbianas de combustível. A composição orgânica desta água faz com que o seu potencial energético possa ser explorado, usando o metabolismo bacteriano para produzir energia e, simultaneamente, auxiliar na limpeza da água. Este documento está dividido em 5 capítulos. O posicionamento do tema ocorre no capítulo 1. O capítulo 2 observa os principais elementos da tecnologia das células microbianas de combustível, permitindo compreender o seu funcionamento e conhecer que variáveis afetam o seu funcionamento. No capítulo 3 são apresentadas as tipologias de abordagem à gestão energética para esta pilha bacteriológica, discutindo-se as vantagens e otimizações de cada sistema. O penúltimo capítulo corresponde à exploração de resultados experimentais e à validação de hipóteses, orientadas para a maior eficiência energética. Surgem assim recomendações que servirão para guiar os trabalhos futuros, discutidos no capítulo final. Este, o capítulo 5, conta ainda com a apresentação das principais conclusões e das tendências de pesquisa. O trabalho termina com um exemplo de aplicação que solidifica a validade e utilidade da aplicação desta tecnologia

Energy Harvesting Techniques for Small Scale Environmentally-Powered Electronic Systems

The continuous advances in integrated circuit fabrication technologies, circuit design, and networking techniques enable the integration of an in-creasing number of functionalities in ever smaller devices. This trend de-termines the multiplication of possible application scenarios for tiny em-bedded systems such as wireless sensors, whose utilization has grown more and more pervasive. However, the operating life time of such sys-tems, when placed in locations not allowing a wired connection to a de-pendable power supply infrastructure, is still heavily limited by the finite capacity of currently available accumulators, whose technology has not improved at the same pace of the electronic systems they supply. Energy harvesting techniques constitute a real solution to power un-tethered computing platforms in this kind of spatially-distributed applica-tions. By converting part of the energy freely available in the surrounding environment to electrical energy, the operating life of the system can be extended considerably, potentially for an unlimited time. In recent years an increasing number of researchers have investigated this possibility. In this dissertation we discuss our results about the study and design of systems capable of harvesting energy from various regenerative sources. We start with the design of an airflow energy harvester, focusing on the optimization of its power generation and efficiency performances, and obtaining superior results with respect to similar works in literature. Then we deal with the improvement of this architecture to implement a fully autonomous vibrational harvester, featuring uncommon in-the-field configuration capabilities. Afterwards we investigate the applicability of self-powered wireless sensor nodes to heavy duty and agricultural machinery, finding attractive vibration sources capable of providing enough power to sustain remarkable data transmission rates. To address remote monitoring applications with stringent needs in terms of power supply availability, we present a truly flexible multi-source energy harvester, along with a simulation framework expressly developed to anticipate the harvester performance when placed in a specific operating environment. Furthermore, the design strategies allowing energy harvesters to fully exploit the locally generated power can be profitably applied in the field of distributed electricity generation from renewable energy sources, to enhance the self-consumption capabilities of microgeneration systems. Based on this motivation, we finally propose a grid-assisted photovoltaic power supply to improve the self-sustainability of ground-source heat pumps, and analyze original data on the consumption profiles of these systems to assess the effectiveness of the design. Energy harvesting techniques have the potential to enable many cut-ting-edge applications, especially in remote sensing and pervasive computing areas, which can bring innovations in several fields of human activity. In this thesis we contribute tackling some of the numerous open research challenges still hampering the widespread adoption of this technology