THE CONCEPT FOR THE “SMART HOME” CONTROLLED BY A SMARTWATCH

In this paper a “Smart Home“ solution is proposed in which power plugs in a remote room can be controlled by a smartwatch, an Android mobile device or a PHP web app. Communication between these devices takes place in real time via server using Node.js technology. An electrical circuit for determining current and voltage on the plugs via Arduino Wi-Fi module sends the measured values to the server, based on which the electrical energy consumption in each time interval can be determined. All the measured values are stored in MySQL database and used for creation of appropriate reports. Smartwatch app enables remote plugging and unplugging. In addition, the setting of limits for electrical energy consumption on each plug is enabled, as well as the power of the consumption device that can be plugged. Exceeding of the allowed values leads to the automatic unplugging

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

Realization of a Self-Reconfigurable Modular Robot

This project realized a self-reconfigurable modular robot for search & rescue applications. The module was designed to move independently and connect with other modules. A single module was roughly 3x3x6” and weighed 2lbs. The module had three degrees of freedom, giving it individual mobility and high system configurability. The small module size and untethered operation necessitated an innovative design and strategic placement of the microcontroller, wireless communication, motors & control systems, sensors, and battery. An external magnetic connection mechanism using electrically switchable permanent magnets was designed, allowing the modules to connect and disconnect repeatedly

APPLICATION OF PYTHON PROGRAMMING LANGUAGE IN MEASUREMENTS

Application of Python programming language in automation of measurement systems and creating virtual instruments is discussed in this paper. Requirements imposed to the software in order to perform these tasks are listed, and Python modules that support them are presented. Application of proposed techniques are illustrated in seven examples in different application areas. Analysis of software evolution, as well as the evolution of professional education yields conclusion that application of Python in automating measurement systems is promising

Wind energy harvester interface for sensor nodes

The research topic is developping a power converting interface for the novel FLEHAP wind energy harvester allowing the produced energy to be used for powering small wireless nodes. The harvester\u2019s electrical characteristics were studied and a strategy was developped to control and mainting a maximum power transfer. The electronic power converter interface was designed, containing an AC/DC Buck-Boost converter and controlled with a low power microcontroller. Different prototypes were developped that evolved by reducing the sources of power loss and rendering the system more efficient. The validation of the system was done through simulations in the COSMIC/DITEN lab using generated signals, and then follow-up experiments were conducted with a controllable wind tunnel in the DIFI department University of Genoa. The experiment results proved the functionality of the control algorithm as well as the efficiency that was ramped up by the hardware solutions that were implemented, and generally met the requirement to provide a power source for low-power sensor nodes

Power Electronics Applications in Renewable Energy Systems

The renewable generation system is currently experiencing rapid growth in various power grids. The stability and dynamic response issues of power grids are receiving attention due to the increase in power electronics-based renewable energy. The main focus of this Special Issue is to provide solutions for power system planning and operation. Power electronics-based devices can offer new ancillary services to several industrial sectors. In order to fully include the capability of power conversion systems in the network integration of renewable generators, several studies should be carried out, including detailed studies of switching circuits, and comprehensive operating strategies for numerous devices, consisting of large-scale renewable generation clusters

Circuits and Systems for Energy Harvesting and Internet of Things Applications

The Internet of Things (IoT) continues its growing trend, while new “smart” objects are con-stantly being developed and commercialized in the market. Under this paradigm, every common object will be soon connected to the Internet: mobile and wearable devices, electric appliances, home electronics and even cars will have Internet connectivity. Not only that, but a variety of wireless sensors are being proposed for different consumer and industrial applications. With the possibility of having hundreds of billions of IoT objects deployed all around us in the coming years, the social implications and the economic impact of IoT technology needs to be seriously considered. There are still many challenges, however, awaiting a solution in order to realize this future vision of a connected world. A very important bottleneck is the limited lifetime of battery powered wireless devices. Fully depleted batteries need to be replaced, which in perspective would generate costly maintenance requirements and environmental pollution. However, a very plausible solution to this dilemma can be found in harvesting energy from the ambient. This dissertation focuses in the design of circuits and system for energy harvesting and Internet of Things applications. The first part of this dissertation introduces the research motivation and fundamentals of energy harvesting and power management units (PMUs). The architecture of IoT sensor nodes and PMUs is examined to observe the limitations of modern energy harvesting systems. Moreover, several architectures for multisource harvesting are reviewed, providing a background for the research presented here. Then, a new fully integrated system architecture for multisource energy harvesting is presented. The design methodology, implementation, trade-offs and measurement results of the proposed system are described. The second part of this dissertation focus on the design and implementation of low-power wireless sensor nodes for precision agriculture. First, a sensor node incorporating solar energy harvesting and a dynamic power management strategy is presented. The operation of a wireless sensor network for soil parameter estimation, consisting of four nodes is demonstrated. After that, a solar thermoelectric generator (STEG) prototype for powering a wireless sensor node is proposed. The implemented solar thermoelectric generator demonstrates to be an alternative way to harvest ambient energy, opening the possibility for its use in agricultural and environmental applications. The open problems in energy harvesting for IoT devices are discussed at the end, to delineate the possible future work to improve the performance of EH systems. For all the presented works, proof-of-concept prototypes were fabricated and tested. The measured results are used to verify their correct operation and performance

Energy Harvesting Systems for the Internet of Things with Applications to Smart Agriculture

The Internet of Things is the interconnection of everyday objects to the web, with the purpose of exchanging information to enable smarter actions and potentially make a process more efficient. However, how power is provided and stored in remote sensing applications is still one of the main modern electronics challenges of such technology and can become one of the main constraints to prevent its mass adoption. Energy Harvesting is an emerging technology that can transform energy in the environment into usable energy, among such environmental energy are electromagnetic waves, thermal, solar, kinesthetic transducers, fuel cells, to name a few. Because this technology makes use of the available ambient energy, it has the potential to increase the power readiness for battery-operated electronics and more importantly, it can become the technology that fully powers the next generation of internet-enabled agricultural solutions. This dissertation centers around the design and development of high-efficient power management systems for AC and DC energy harvesting sources. The proposed architectures not only consider circuits, systems and algorithms that make a more efficient power extraction but also focuses on providing inherent sensing functionalities at no extra system complexity, which in turn not only achieves the goal of extending the battery life of proposed smart sensor applications but also proposes new charge extraction methods to permanently power an electronic device. The work presented in this dissertation demonstrates that energy harvesting, and internet of things devices can be implemented in multiple smart agriculture scenarios by proposing algorithms, circuits and systems capable of performing energy harvesting operations while providing reliable data to the end user. The analysis of the design of such proof-of-concept prototypes are provided in this dissertation along with its implementation and testing. The first part of this dissertation proposes novel algorithms for maximum power extraction and new power measurement techniques. The second part focuses on front-end circuits for AC energy harvesting sources and circuits that can provide sensing capabilities along with energy harvesting operations

Modulaarinen kehitysalusta langattomille lääketieteellisille anturi-implanteille

Implanting medical sensor devices under skin improves the quality of the acquired measurement results, and can greatly increase the comfort for the patient in prolonged measurement. Design of such complex devices and related systems benefits from using a dedicated development platform that represents the functionalities and associated challenges. This work presents the design, implementation and verified performance of a modular platform that can be used in demonstration, development and testing of various functionalities of wireless medical sensor implants. The system is constructed using discrete components and consists of five inter connectable modules, each representing a specific function of the sensor implant system: bio potential measurement front-end module, wireless communication front-end module, clock and power management module, control logic module and external reader module. The implemented system has measurement front-end with an ENOB of 9 bits and configurable structure for the needs of various bio potentials. Wireless data transfer operates at 840-960 MHz with supported data rate up to 640 kbps. The system demonstrates dual carrier operation for separating the power and data transfers. Power can be harvested and clock extracted from 6.75 MHz or 865 MHz radio signals, both radio signals can be generated by the external reader. Control logic is provided with a high-end FPGA evaluation board. The completed platform can be used for developing and testing aspects for novel implanted devices, such as different radio communication schemes, radio antenna options, or controls and algorithms in digital logic.Lääketieteellisten anturien asettaminen ihon alle parantaa biopotentiaalimittauksien tulosten laatua ja pitkäaikaisten mittauksien mukavuutta potilaalle. Näiden monimutkaisten laitteiden suunnittelua voidaan tehostaa käyttämällä apuna sovelluskohtaista kehitysalustaa. Tässä työssä suunnitellaan ja toteutetaan modulaarinen, korkean suorituskyvyn kehitysalusta biopotentiaalia mittaavien langattomien anturi-implanttijärjestelmien eri toiminnallisuuksien esittelyyn, kehitykseen ja testaukseen. Diskreeteillä komponenteilla toteutettu järjestelmä koostuu viidestä moduulista: biopotentiaalien mittausmoduuli, langattoman tiedonvälityksen radiomoduuli, tehon ja kellosignaalin keräysmoduuli, ohjauslogiikkamoduuli, ja kehon ulkopuolinen lukijamoduuli. Kehitysalusta on muokattavissa eri biopotentiaalien mittauksien tarpeisiin. Mittausetupään tehollinen bittimäärä on 9 bittiä. Langatonta tiedonsiirtoa tuetaan 840 - 960 MHz taajuuskaistalla 640 kbps siirtonopeuksiin asti. Järjestelmällä voidaan demonstroida kahden kantoaallon yhtäaikaista käyttämistä, jolloin tehon- ja tiedonsiirto voidaan tarvittaessa erottaa toisistaan. Tehoa voidaan kerätä ja kellosignaaleja muodostaa 6,75 MHz ja 865 MHz taajuuksien radiosignaaleilta, jotka molemmat voidaan luoda hallitusti lukijamoduulilla. Ohjauslogiikka on toteutettu käyttäen ohjelmoitavaa porttimatriisipiiriä. Kehitysalustaa voidaan käyttää uusien implanttijärjestelmien suunnittelussa, esimerkiksi eri tiedonsiirtotapojen, antennirakenteiden, ohjauslogiikan ja digitaalisten algoritmien arvioinnissa

Design and Development of Microcontroller System, Embedded Circuits and Applications

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