Optimal current control for sub-unity power factor correction

Switching mode power supplies (SMPS) are subject to low power factor and high harmonic distortions. Active power-factor correction (APFC) is a technique to improve the power factor and to reduce the harmonic distortion of SMPSs. However, this technique results in double frequency output voltage variation which can be reduced by using a large output capacitance. Using large capacitors increases the cost and size of the converter. Furthermore, the capacitors are subject to frequent failures mainly caused by evaporation of the electrolytic solution which reduce the converter reliability. This thesis presents an optimal control method for the input current of a boost converter to reduce the size of the output capacitor. The optimum current waveform as a function of weighing factor is found by using the Euler Lagrange equation. A set of simulations are performed to determine the ideal weighing which gives the lowest possible output voltage variation as the converter still meets the IEC-61000-3-2 class-A harmonics requirements with a power factor of 0.8 or higher. The proposed method is verified by the experimental work. A boost converter is designed and it is run for different power levels, 100 W, 200 W and 400 W. The desired output voltage ripple is 10 V peak to peak for the output voltage of 200 Vdc. This ripple value corresponds to a ± 2.5% output voltage ripple. The experimental and the simulation results are found to be quite matching. A significant reduction in capacitor size, as high as 50%, is accomplished by using the proposed method.

Low Mass Calibration Target for MM-Wave Remote Sensing Instruments

The reliability of millimeter and sub-millimeter wave radiometer measurements is dependent on the accuracy of the loads they employ as calibration targets. In the recent past on-board calibration loads have been developed for a variety of satellite remote sensing instruments. Unfortunately some of these have suffered from calibration inaccuracies which had poor thermal performance of the calibration target as the root cause. Stringent performance parameters of the calibration target such as low reflectivity, high temperature uniformity, low mass and low power consumption combined with low volumetric requirements remain a challenge for the space instrument developer. In this paper we present a novel multi-layer absorber concept for a calibration load which offers an excellent compromise between very good radiometric performance and temperature uniformity and the mass and volumetric constraints required by space-borne calibration targets.

The Face of Power

Objective: In humans and other animals, open, expansive postures (compared to contracted postures) are evolutionary developed expressions of power and have been shown to cause neuroendocrine and behavioral changes (Carney, Cuddy, & Yap, 2010). In the present study we aimed to investigate whether power postures have a bearing on the participant’s facial appearance and whether others are able to distinguish faces after “high power posing” from faces after “low power posing”. Methods: 16 models were photographed 4-5 minutes after having adopted high and low power postures. Two different high power and two different low power postures were held for 2 minutes each. Power-posing sessions were performed on two consecutive days. High and low power photographs of each model were paired and an independent sample of 100 participants were asked to pick the more dominant and the more likeable face of each pair. Results: Photographs that were taken after adopting high power postures were chosen significantly more often as being more dominant looking. There was no preference when asked to choose the more likeable photograph (chance level). A further independent sample rated each photograph for head tilt, making it unlikely that dominance ratings were caused merely by the posture of the head. Consistently, facial width-to-height ratio did not differ between faces after high and low power posing. Conclusions: Postures associated with high power affect facial appearance, leading to a more dominant looking face. This finding may have implications for everyday life, for instance when a dominant appearance is needed.

Impact of N2 plasma power and duration on AlGaN/GaN HEMT

urface treatments have been recently shown to play an active role in electrical characteristics in AlGaN/GaN HEMTs, in particular during the passivation processing [1-4]. However, the responsible mechanisms are partially unknown and further studies are demanding. The effects of power and time N2 plasma pre-treatment prior to SiN deposition using PE-CVD (plasma enhanced chemical vapour deposition) on GaN and AlGaN/GaN HEMT have been investigated. The low power (60 W) plasma pre-treatment was found to improve the electronic characteristics in GaN based HEMT devices, independently of the time duration up to 20 min. In contrast, high power (150 and 210 W) plasma pretreatment showed detrimental effects in the electronic properties (Fig. 1), increasing the sheet resistance of the 2DEG, decreasing the 2DEG charge density in AlGaN/GaN HEMTs, transconductance reduction and decreasing the fT and fmax values up to 40% respect to the case using 60 W N2 plasma power. Although AFM (atomic force microscopy) results showed AlGaN and GaN surface roughness is not strongly affected by the N2-plasma, KFM (Kelvin force microscopy) surface analysis shows significant changes in the surface potential, trending to increase its values as the plasma power is higher. The whole results point at energetic ions inducing polarization-charge changes that affect dramatically to the 2-DEG charge density and the final characteristics of the HEMT devices. Therefore, we conclude that AlGaN surface is strongly sensitive to N2 plasma power conditions, which turn to be a key factor to achieve a good surface preparation prior to SiN passivation.

Loss model for a high frequency and low load DC/DC synchronous buck converter

This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time and a good accuracy. It has been validated by simulation and experimentally with one Ga, power transistor and two Si MOSFETs. Results show good agreement between measurements and the model.

Hybrid behavioral-analytical loss model for a high frequency and low load DC/DC buck converter

This work presents a behavioral-analytical hybrid loss model for a buck converter. The model has been designed for a wide operating frequency range up to 4MHz and a low power range (below 20W). It is focused on the switching losses obtained in the power MOSFETs. Main advantages of the model are the fast calculation time (below 8.5 seconds) and a good accuracy, which makes this model suitable for the optimization process of the losses in the design of a converter. It has been validated by simulation and experimentally with one GaN power transistor and three Si MOSFETs. Results show good agreement between measurements and the model

Propuesta de aplicación de una red de sensores en emergencias

El auge y evolución de los sistemas de comunicaciones móviles y de las redes inalámbricas avanzadas, sucedido desde principios del siglo XXI, han propiciado el uso de Redes de Sensores Inalámbricos (RSI) en múltiples ámbitos de interés. Dichas redes están típicamente compuestas por dispositivos inalámbricos autónomos que incorporan sensores para la recogida de datos de distinta naturaleza. Las RSI se caracterizan por su escalabilidad, ausencia de cableado, pequeño tamaño, bajo consumo, gran variedad de magnitudes físico/químicas medibles, entre otras, cuyas cualidades las hace muy interesantes para su aplicación en multitud de escenarios de la Sociedad de la Información, tales como domótica, agricultura y ganadería, medioambiente, salud, procesos industriales, logística, seguridad o ciudades inteligentes, ente otras. En este Trabajo Fin de Máster, se propone el uso de las RSI en el escenario de Emergencias donde cobra gran importancia la usabilidad, la fiabilidad, la disponibilidad, y la robustez de los sistemas a emplear en condiciones hostiles, especialmente en las de bomberos. Es por ello que se analizarán previamente los trabajos de RSI desarrollados para estos entornos y que sugieren qué aplicaciones garantizan el cumplimiento de los requerimientos mencionados. Se aborda la utilización de una primera RSI para la monitorización ambiental de tres Centros de Procesado de Datos (CPD) del departamento de TI de Emergencias, siendo este un entorno sin movilidad, más controlado y que aporta la adquisición de experiencia en la utilización de las RSI de cara a un entorno móvil más complejo. A continuación, para el entorno móvil se ha desarrollado y validado un prototipo experimental de RSI para el seguimiento de salida de parques de bomberos de vehículos con su dotación. Así mismo se implementa un prototipo para la ayuda a la localización de bomberos y/o personas en un siniestro. Estas RSI se desarrollan e implantan en el entorno de Emergencias del Ayuntamiento de Madrid, entidad sin cuyo apoyo habría sido imposible la aplicación práctica de este trabajo. SUMMARY. The rise and evolution of mobile communication systems and advanced wireless networks in early XXI century have allowed to taking advantage of Wireless Sensor Networks (WSN). These networks are composed of independent wireless devices that incorporate sensors for collecting data of different nature. The WSN is characterized by its scalability, no wiring, small size, low power consumption, wide range of physical magnitudes measurable, among others. These qualities make them very interesting for application in many scenarios to the Information Society, such as, domotic, agriculture, smart environment, ehealth, industrial control, logistics, security and smart cities, among others. This work proposes to use WSN in the emergency scenario where is very important the usability, reliability, availability, and robustness of the systems to be used in hostile conditions, especially in fire-fighters environment. That is why WSN works in emergency will be studied to tackle what applications compliance with the above requirements. The first WSN developed will be environmental monitoring of three CPDs IT department Emergency. This scenario is a non-mobile environment, more controlled and bring gaining experience in the use of WSN to face mobile environment which is more complex. Then, for the mobile environment is developed an experimental prototype of WSN for tracking fire vehicles living fire stations with their equipment. Another prototype is foreseen to be implemented to assist fire-fighters location and / or people in a disaster. These WSN are developed and implemented for Madrid City Emergency, whose involvement was critical to put this research into stage.

Impact of N2 plasma power discharge on AlGaN/GaN HEMT performance

The effects of power and time conditions of in situ N2 plasma treatment, prior to silicon nitride (SiN) passivation, were investigated on an AlGaN/GaN high-electron mobility transistor (HEMT). These studies reveal that N2 plasma power is a critical parameter to control the SiN/AlGaN interface quality, which directly affects the 2-D electron gas density. Significant enhancement in the HEMT characteristics was observed by using a low power N2 plasma pretreatment. In contrast, a marked gradual reduction in the maximum drain-source current density (IDS max) and maximum transconductance (gm max), as well as in fT and fmax, was observed as the N2 plasma power increases (up to 40% decrease for 210 W). Different mechanisms were proposed to be dominant as a function of the discharge power range. A good correlation was observed between the device electrical characteristics and the surface assessment by atomic force microscopy and Kelvin force microscopy techniques.

Wireless Sensor Network Solution for Sustainable Food Production

Environmental monitoring has become a key aspect in food production over the last few years. Due to their low cost, low power consumption and flexibility, Wireless Sensor Networks (WSNs) have turned up as a very convenient tool to be used in these environments where no intrusion is a must. In this work, a WSN application in a food factory is presented. The paper gives an overview of the system set up, covering from the initial study of the parameters and sensors, to the hardware-software design and development needed for the final tests in the factory facilities.

On-the-fly dynamic reprogramming mechanism for increasing the energy efficiency and supporting multi-experimental capabilities in WSNs

Remote reprogramming capabilities are one of the major concerns in WSN platforms due to the limitations and constraints that low power wireless nodes poses, especially when energy efficiency during the reprogramming process is a critical factor for extending the battery life of the devices. Moreover, WSNs are based on low-rate protocols in which as greater the amount of data is sent, the more the possibility to lose packets during the transmitting process is. In order to overcome these limitations, in this work a novel on-the-fly reprogramming technique for modifying and updating the application running on the wireless sensor nodes is designed and implemented, based on a partial reprogramming mechanism that significantly reduces the size of the files to be downloaded to the nodes, therefore diminishing their power/time consumption. This powerful mechanism also addresses multi-experimental capabilities because it provides the possibility to download, manage, test and debug multiple applications into the wireless nodes, based on a memory map segmentation of the core. Being an on-the-fly reprogramming process, no additional resources to store and download the configuration file are needed.

FPGA-Based Wireless Sensor Node Architecture for High Performance Applications

While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements.

Power-Aware Multi-Objective Evolvable Hardware System on an FPGA

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.

Monolithic master oscillator power amplifier at 1.58 µm for lidar measurements

Nowadays the interest in high power semiconductor devices is growing for applications such as telemetry, lidar system or free space communications. Indeed semiconductor devices can be an alternative to solid state lasers because they are more compact and less power consuming. These characteristics are very important for constrained and/or low power supply environment such as airplanes or satellites. Lots of work has been done in the 800-1200 nm range for integrated and free space Master Oscillator Power Amplifier (MOPA) [1]-[3]. At 1.5 ?m, the only commercially available MOPA is from QPC [4]: the fibred output power is about 700 mW and the optical linewidth is 500 kHz. In this paper, we first report on the simulations we have done to determine the appropriate vertical structure and architecture for a good MOPA at 1.58 ?m (section II). Then we describe the fabrication of the devices (section III). Finally we report on the optical and electrical measurements we have done for various devices (section IV).

Análisis de ataques avanzados y sus técnicas de detección

Los ataques a redes de información son cada vez más sofisticados y exigen una constante evolución y mejora de las técnicas de detección. Para ello, en este proyecto se ha diseñado e implementado una plataforma cooperativa para la detección de intrusiones basada en red. En primer lugar, se ha realizado un estudio teórico previo del marco tecnológico relacionado con este ámbito, en el que se describe y caracteriza el software que se utiliza para realizar ataques a sistemas (malware) así como los métodos que se utilizan para llegar a transmitir ese software (vectores de ataque). En el documento también se describen los llamados APT, que son ataques dirigidos con una gran inversión económica y temporal. Estos pueden englobar todos los malware y vectores de ataque existentes. Para poder evitar estos ataques, se estudiarán los sistemas de detección y prevención de intrusiones, describiendo brevemente los algoritmos que se tienden a utilizar en la actualidad. En segundo lugar, se ha planteado y desarrollado una plataforma en red dedicada al análisis de paquetes y conexiones para detectar posibles intrusiones. Este sistema está orientado a sistemas SCADA (Supervisory Control And Data Adquisition) aunque funciona sobre cualquier red IPv4/IPv6, para ello se definirá previamente lo que es un sistema SCADA, así como sus partes principales. Para implementar el sistema se han utilizado dispositivos de bajo consumo llamados Raspberry PI, estos se ubican entre la red y el equipo final que se quiera analizar. En ellos se ejecutan 2 aplicaciones desarrolladas de tipo cliente-servidor (la Raspberry central ejecutará la aplicación servidora y las esclavas la aplicación cliente) que funcionan de forma cooperativa utilizando la tecnología distribuida de Hadoop, la cual se explica previamente. Mediante esta tecnología se consigue desarrollar un sistema completamente escalable. La aplicación servidora muestra una interfaz gráfica que permite administrar la plataforma de análisis de forma centralizada, pudiendo ver así las alarmas de cada dispositivo y calificando cada paquete según su peligrosidad. El algoritmo desarrollado en la aplicación calcula el ratio de paquetes/tiempo que entran/salen del equipo final, procesando los paquetes y analizándolos teniendo en cuenta la información de señalización, creando diferentes bases de datos que irán mejorando la robustez del sistema, reduciendo así la posibilidad de ataques externos. Para concluir, el proyecto inicial incluía el procesamiento en la nube de la aplicación principal, pudiendo administrar así varias infraestructuras concurrentemente, aunque debido al trabajo extra necesario se ha dejado preparado el sistema para poder implementar esta funcionalidad. En el caso experimental actual el procesamiento de la aplicación servidora se realiza en la Raspberry principal, creando un sistema escalable, rápido y tolerante a fallos. ABSTRACT. The attacks to networks of information are increasingly sophisticated and demand a constant evolution and improvement of the technologies of detection. For this project it is developed and implemented a cooperative platform for detect intrusions based on networking. First, there has been a previous theoretical study of technological framework related to this area, which describes the software used for attacks on systems (malware) as well as the methods used in order to transmit this software (attack vectors). In this document it is described the APT, which are attacks directed with a big economic and time inversion. These can contain all existing malware and attack vectors. To prevent these attacks, intrusion detection systems and prevention intrusion systems will be discussed, describing previously the algorithms tend to use today. Secondly, a platform for analyzing network packets has been proposed and developed to detect possible intrusions in SCADA (Supervisory Control And Data Adquisition) systems. This platform is designed for SCADA systems (Supervisory Control And Data Acquisition) but works on any IPv4 / IPv6 network. Previously, it is defined what a SCADA system is and the main parts of it. To implement it, we used low-power devices called Raspberry PI, these are located between the network and the final device to analyze it. In these Raspberry run two applications client-server developed (the central Raspberry runs the server application and the slaves the client application) that work cooperatively using Hadoop distributed technology, which is previously explained. Using this technology is achieved develop a fully scalable system. The server application displays a graphical interface to manage analytics platform centrally, thereby we can see each device alarms and qualifying each packet by dangerousness. The algorithm developed in the application calculates the ratio of packets/time entering/leaving the terminal device, processing the packets and analyzing the signaling information of each packet, reating different databases that will improve the system, thereby reducing the possibility of external attacks. In conclusion, the initial project included cloud computing of the main application, being able to manage multiple concurrent infrastructure, but due to the extra work required has been made ready the system to implement this funcionality. In the current test case the server application processing is made on the main Raspberry, creating a scalable, fast and fault-tolerant system.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.