Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Perspectives on the design and use of direct alcohol fuel cells fed by alcohol blends

The fast-growing power demand by portable electronic devices has promoted the increase of global production of portable PEM fuel cell, a quarter of them consist of direct methanol fuel cell (DMFC) units. These present the advantage of being fuelled directly with a liquid fuel, as well as direct ethanol fuel cells (DEFC) do.

Influencia de las restricciones medioambientales en el sector eléctrico

El objetivo de esta tesis es la caracterización de la generación térmica representativa de la existente en la realidad, para posteriormente proceder a su modelización y simulación integrándolas en una red eléctrica tipo y llevar a cabo estudios de optimización multiobjetivo económico medioambiental. Para ello, en primera instancia se analiza el contexto energético y eléctrico actual, y más concretamente el peninsular, en el que habiendo desaparecido las centrales de fuelóleo, sólo quedan ciclos combinados y centrales de carbón de distinto rango. Seguidamente se lleva a cabo un análisis de los principales impactos medioambientales de las centrales eléctricas basadas en combustión, representados sobre todo por sus emisiones de CO2, SO2 y NOx, de las medidas de control y mitigación de las mismas y de la normativa que les aplica. A continuación, a partir de las características de los combustibles y de la información de los consumos específicos, se caracterizan los grupos térmicos frente a las funciones relevantes que definen su comportamiento energético, económico y medioambiental, en términos de funciones de salida horarias dependiendo de la carga. Se tiene en cuenta la posibilidad de desnitrificación y desulfuración. Dado que las funciones objetivo son múltiples, y que están en conflicto unas con otras, se ha optado por usar métodos multiobjetivo que son capaces de identificar el contorno de puntos óptimos o frente de Pareto, en los que tomando una solución no existe otra que lo mejore en alguna de las funciones objetivo sin empeorarlo en otra. Se analizaron varios métodos de optimización multiobjetivo y se seleccionó el de las ε constraint, capaz de encontrar frentes no convexos y cuya optimalidad estricta se puede comprobar. Se integró una representación equilibrada de centrales de antracita, hulla nacional e importada, lignito y ciclos combinados en la red tipo IEEE-57, en la que se puede trabajar con siete centrales sin distorsionar demasiado las potencias nominales reales de los grupos, y se programó en Matlab la resolución de flujos óptimos de carga en alterna con el método multiobjetivo integrado. Se identifican los frentes de Pareto de las combinaciones de coste y cada uno de los tres tipos de emisión, y también el de los cuatro objetivos juntos, obteniendo los resultados de costes óptimos del sistema para todo el rango de emisiones. Se valora cuánto le cuesta al sistema reducir una tonelada adicional de cualquier tipo de emisión a base de desplazarse a combinaciones de generación más limpias. Los puntos encontrados aseguran que bajo unas determinadas emisiones no pueden ser mejorados económicamente, o que atendiendo a ese coste no se puede reducir más allá el sistema en lo relativo a emisiones. También se indica cómo usar los frentes de Pareto para trazar estrategias óptimas de producción ante cambios horarios de carga. ABSTRACT The aim of this thesis is the characterization of electrical generation based on combustion processes representative of the actual power plants, for the latter modelling and simulation of an electrical grid and the development of economic- environmental multiobjective optimization studies. In this line, the first step taken is the analysis of the current energetic and electrical framework, focused on the peninsular one, where the fuel power plants have been shut down, and the only ones remaining are coal units of different types and combined cycle. Then it is carried out an analysis of the main environmental impacts of the thermal power plants, represented basically by the emissions of CO2, SO2 y NOx, their control and reduction measures and the applicable regulations. Next, based on the combustibles properties and the information about the units heat rates, the different power plants are characterized in relation to the outstanding functions that define their energy, economic and environmental behaviour, in terms of hourly output functions depending on their load. Optional denitrification and desulfurization is considered. Given that there are multiple objectives, and that they go in conflictive directions, it has been decided the use of multiobjective techniques, that have the ability of identifying the optimal points set, which is called the Pareto front, where taken a solution there will be no other point that can beat the former in an objective without worsening it in another objective. Several multiobjective optimization methods were analysed and pondered, selecting the ε constraint technique, which is able to find no convex fronts and it is opened to be tested to prove the strict Pareto optimality of the obtained solutions. A balanced representation of the thermal power plants, formed by anthracite, lignite, bituminous national and imported coals and combined cycle, was integrated in the IEEE-57 network case. This system was selected because it deals with a total power that will admit seven units without distorting significantly the actual size of the power plants. Next, an AC optimal power flow with the multiobjective method implemented in the routines was programmed. The Pareto fronts of the combination of operative costs with each of the three emissions functions were found, and also the front of all of them together. The optimal production costs of the system for all the emissions range were obtained. It is also evaluated the cost of reducing an additional emission ton of any of the emissions when the optimal production mix is displaced towards cleaner points. The obtained solutions assure that under a determined level of emissions they cannot be improved economically or, in the other way, at a determined cost it cannot be found points of lesser emissions. The Pareto fronts are also applied for the search of optimal strategic paths to follow the hourly load changes.

Distribution of the coal flow in the mill-duct system of the As Pontes Power Plant using CFD modeling

The efficiency of a Power Plant is affected by the distribution of the pulverized coal within the furnace. The coal, which is pulverized in the mills, is transported and distributed by the primary gas through the mill-ducts to the interior of the furnace. This is done with a double function: dry and enter the coal by different levels for optimizing the combustion in the sense that a complete combustion occurs with homogeneous heat fluxes to the walls. The mill-duct systems of a real Power Plant are very complex and they are not yet well understood. In particular, experimental data concerning the mass flows of coal to the different levels are very difficult to measure. CFD modeling can help to determine them. An Eulerian/Lagrangian approach is used due to the low solid–gas volume ratio.

Power Measurement Methodology for FPGA Devices

The efficiency of power optimization tools depends on information on design power provided by the power estimation models. Power models targeting different power groups can enable fast identification of the most power consuming parts of design and their properties. The accuracy of these estimation models is highly dependent on the accuracy of the method used for their characterization. The highest precision is achieved by using physical onboard measurements. In this paper, we present a measurement methodology that is primarily aimed at calibrating and validating high-level dynamic power estimation models. The measurements have been carefully designed to enable the separation of the interconnect power from the logic power and the power of the clock circuitry, so that each of these power groups can be used for the corresponding model validation. The standard measurement uncertainty is lower than 2% of the measured value even with a very small number of repeated measurements. Additionally, the accuracy of a commercial low-level power estimation tool has been also assessed for comparison purposes. The results indicate that the tool is not suitable for power estimation of data path-oriented designs.

Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of estimating the target’s position when we use received signal strength indicator (RSSI) due to the nonlinear relationship between the measured signal and the true position of the target. Many of the existing approaches suffer either from high computational complexity (e.g., particle filters) or lack of accuracy. Further, many of the proposed solutions are centralized which make their application to a sensor network questionable. Depending on the application at hand and, from a practical perspective it could be convenient to find a balance between localization accuracy and complexity. Into this direction we approach the maximum likelihood location estimation problem by solving a suboptimal (and more tractable) problem. One of the main advantages of the proposed scheme is that it allows for a decentralized implementation using distributed processing tools (e.g., consensus and convex optimization) and therefore, it is very suitable to be implemented in real sensor networks. If further accuracy is needed an additional refinement step could be performed around the found solution. Under the assumption of independent noise among the nodes such local search can be done in a fully distributed way using a distributed version of the Gauss-Newton method based on consensus. Regardless of the underlying application or function of the sensor network it is al¬ways necessary to have a mechanism for data reporting. While some approaches use a special kind of nodes (called sink nodes) for data harvesting and forwarding to the outside world, there are however some scenarios where such an approach is impractical or even impossible to deploy. Further, such sink nodes become a bottleneck in terms of traffic flow and power consumption. To overcome these issues instead of using sink nodes for data reporting one could use collaborative beamforming techniques to forward directly the generated data to a base station or gateway to the outside world. In a dis-tributed environment like a sensor network nodes cooperate in order to form a virtual antenna array that can exploit the benefits of multi-antenna communications. In col-laborative beamforming nodes synchronize their phases in order to add constructively at the receiver. Some of the inconveniences associated with collaborative beamforming techniques is that there is no control over the radiation pattern since it is treated as a random quantity. This may cause interference to other coexisting systems and fast bat-tery depletion at the nodes. Since energy-efficiency is a major design issue we consider the development of a distributed collaborative beamforming scheme that maximizes the network lifetime while meeting some quality of service (QoS) requirement at the re¬ceiver side. Using local information about battery status and channel conditions we find distributed algorithms that converge to the optimal centralized beamformer. While in the first part we consider only battery depletion due to communications beamforming, we extend the model to account for more realistic scenarios by the introduction of an additional random energy consumption. It is shown how the new problem generalizes the original one and under which conditions it is easily solvable. By formulating the problem under the energy-efficiency perspective the network’s lifetime is significantly improved. Resumen La proliferación de las redes inalámbricas de sensores junto con la gran variedad de posi¬bles aplicaciones relacionadas, han motivado el desarrollo de herramientas y algoritmos necesarios para el procesado cooperativo en sistemas distribuidos. Una de las aplicaciones que suscitado mayor interés entre la comunidad científica es la de localization, donde el conjunto de nodos de la red intenta estimar la posición de un blanco localizado dentro de su área de cobertura. El problema de la localization es especialmente desafiante cuando se usan niveles de energía de la seal recibida (RSSI por sus siglas en inglés) como medida para la localization. El principal inconveniente reside en el hecho que el nivel de señal recibida no sigue una relación lineal con la posición del blanco. Muchas de las soluciones actuales al problema de localization usando RSSI se basan en complejos esquemas centralizados como filtros de partículas, mientas que en otras se basan en esquemas mucho más simples pero con menor precisión. Además, en muchos casos las estrategias son centralizadas lo que resulta poco prácticos para su implementación en redes de sensores. Desde un punto de vista práctico y de implementation, es conveniente, para ciertos escenarios y aplicaciones, el desarrollo de alternativas que ofrezcan un compromiso entre complejidad y precisión. En esta línea, en lugar de abordar directamente el problema de la estimación de la posición del blanco bajo el criterio de máxima verosimilitud, proponemos usar una formulación subóptima del problema más manejable analíticamente y que ofrece la ventaja de permitir en¬contrar la solución al problema de localization de una forma totalmente distribuida, convirtiéndola así en una solución atractiva dentro del contexto de redes inalámbricas de sensores. Para ello, se usan herramientas de procesado distribuido como los algorit¬mos de consenso y de optimización convexa en sistemas distribuidos. Para aplicaciones donde se requiera de un mayor grado de precisión se propone una estrategia que con¬siste en la optimización local de la función de verosimilitud entorno a la estimación inicialmente obtenida. Esta optimización se puede realizar de forma descentralizada usando una versión basada en consenso del método de Gauss-Newton siempre y cuando asumamos independencia de los ruidos de medida en los diferentes nodos. Independientemente de la aplicación subyacente de la red de sensores, es necesario tener un mecanismo que permita recopilar los datos provenientes de la red de sensores. Una forma de hacerlo es mediante el uso de uno o varios nodos especiales, llamados nodos “sumidero”, (sink en inglés) que actúen como centros recolectores de información y que estarán equipados con hardware adicional que les permita la interacción con el exterior de la red. La principal desventaja de esta estrategia es que dichos nodos se convierten en cuellos de botella en cuanto a tráfico y capacidad de cálculo. Como alter¬nativa se pueden usar técnicas cooperativas de conformación de haz (beamforming en inglés) de manera que el conjunto de la red puede verse como un único sistema virtual de múltiples antenas y, por tanto, que exploten los beneficios que ofrecen las comu¬nicaciones con múltiples antenas. Para ello, los distintos nodos de la red sincronizan sus transmisiones de manera que se produce una interferencia constructiva en el recep¬tor. No obstante, las actuales técnicas se basan en resultados promedios y asintóticos, cuando el número de nodos es muy grande. Para una configuración específica se pierde el control sobre el diagrama de radiación causando posibles interferencias sobre sis¬temas coexistentes o gastando más potencia de la requerida. La eficiencia energética es una cuestión capital en las redes inalámbricas de sensores ya que los nodos están equipados con baterías. Es por tanto muy importante preservar la batería evitando cambios innecesarios y el consecuente aumento de costes. Bajo estas consideraciones, se propone un esquema de conformación de haz que maximice el tiempo de vida útil de la red, entendiendo como tal el máximo tiempo que la red puede estar operativa garantizando unos requisitos de calidad de servicio (QoS por sus siglas en inglés) que permitan una decodificación fiable de la señal recibida en la estación base. Se proponen además algoritmos distribuidos que convergen a la solución centralizada. Inicialmente se considera que la única causa de consumo energético se debe a las comunicaciones con la estación base. Este modelo de consumo energético es modificado para tener en cuenta otras formas de consumo de energía derivadas de procesos inherentes al funcionamiento de la red como la adquisición y procesado de datos, las comunicaciones locales entre nodos, etc. Dicho consumo adicional de energía se modela como una variable aleatoria en cada nodo. Se cambia por tanto, a un escenario probabilístico que generaliza el caso determinista y se proporcionan condiciones bajo las cuales el problema se puede resolver de forma eficiente. Se demuestra que el tiempo de vida de la red mejora de forma significativa usando el criterio propuesto de eficiencia energética.

Data-Flow analysis of prolog programs with extra-logical features

Abstract interpretation-based data-flow analysis of logic programs is at this point relatively well understood from the point of view of general frameworks and abstract domains. On the other hand, comparatively little attention has been given to the problems which arise when analysis of a full, practical dialect of the Prolog language is attempted, and only few solutions to these problems have been proposed to date. Such problems relate to dealing correctly with all builtins, including meta-logical and extra-logical predicates, with dynamic predicates (where the program is modified during execution), and with the absence of certain program text during compilation. Existing proposals for dealing with such issues generally restrict in one way or another the classes of programs which can be analyzed if the information from analysis is to be used for program optimization. This paper attempts to fill this gap by considering a full dialect of Prolog, essentially following the recently proposed ISO standard, pointing out the problems that may arise in the analysis of such a dialect, and proposing a combination of known and novel solutions that together allow the correct analysis of arbitrary programs using the full power of the language.

Relativistic high-current electron-beam stopping-power characterization in solids and plasmas: collisional versus resistive effects.

We present experimental and numerical results on intense-laser-pulse-produced fast electron beams transport through aluminum samples, either solid or compressed and heated by laser-induced planar shock propagation. Thanks to absolute K� yield measurements and its very good agreement with results from numerical simulations, we quantify the collisional and resistive fast electron stopping powers: for electron current densities of � 8 � 1010 A=cm2 they reach 1:5 keV=�m and 0:8 keV=�m, respectively. For higher current densities up to 1012 A=cm2, numerical simulations show resistive and collisional energy losses at comparable levels. Analytical estimations predict the resistive stopping power will be kept on the level of 1 keV=�m for electron current densities of 1014 A=cm2, representative of the full-scale conditions in the fast ignition of inertially confined fusion targets.

The NACIR Project: New Applications for CPV'S: A fast way to improve reliability and Technology progress

The main goal of this proposal is to join together the owners of the most advanced CPV technology, with respect to the state of the art, in order to research from its leading position new applications for CPV systems. In addition to opening up new markets, it will unveil possible sources of failure in new environments outside Europe, in order to assure component reliability. The proposed project will also try to improve the current technology of the industrial partners (ISOFOTON and CONCENTRIX) by accelerating the learning curve that CPV must follow in order to reach the competitive market, and lowering the cost under the current flat panel PV significantly within 3-4 years. The use of CPV systems in remote areas, together with harsher radiation, ambient and infrastructure conditions will help to increase the rate of progress of this technology. In addition, the ISFOC s contribution, which brings together seven power plants from seven CPV technologies up to 3 MWpeak, will allow creating the most complete database of components and systems performance to be generated as well as the effects of radiation and meteorology on systems operations. Finally, regarding the new applications for CPV subject, the project will use a CPV system sized 25 kWp in a stand-alone station in Egypt (NWRC) for the first time for water pumping and irrigation purposes. In a similar way ISOFOTON will connect up to 25 kWp CPV to the Moroccan ONE utility grid. From the research content point of view of this project, which is directly addressed by the scope of the call, the cooperative research between UPM, FhG-ISE and the two companies will be favoured by the fact that all are progressing in similar directions: developing two-stage optics CPV systems. In addition to these technology improvements the UPM is very interested in developing a new concept of module, recently patented, which will fulfil all required characteristics of a good CPV with less components and reducing cost.

Comparison of V2IC control with voltage mode and current mode controls for high frequency (MHz) and very fast response applications

High switching frequencies (several MHz) allow the integration of low power DC/DC converters. Although, in theory, a high switching frequency would make possible to implement a conventional Voltage Mode control (VMC) or Peak Current Mode control (PCMC) with very high bandwidth, in practice, parasitic effects and robustness limits the applicability of these control techniques. This paper compares VMC and CMC techniques with the V2IC control. This control is based on two loops. The fast internal loop has information of the output capacitor current and the error voltage, providing fast dynamic response under load and voltage reference steps, while the slow external voltage loop provides accurate steady state regulation. This paper shows the fast dynamic response of the V2IC control under load and output voltage reference steps and its robustness operating with additional output capacitors added by the customer.

An overview of fast DC-DC converters for envelope amplifier in RF transmitters

In the last years, RF power amplifiers are taking advantage of the switched dc-dc converters to use them in several architectures that may improve the efficiency of the amplifier, keeping a good linearity. The use of linearization techniques such as Envelope Elimination and Restoration (EER) and Envelope Tracking (ET) requires a very fast dc-dc power converter to provide variable voltage supply to the power amplifier but theoretically the efficiency can be much higher than using the classical amplifiers belonging to classes A, B or AB. The purpose of this paper is to analyze the state of the art of the power converters used as envelope amplifiers in this application where a fast output voltage variation is required. The power topologies will be explored and several important parameters such as efficiency, bandwidth and output voltage range will be discussed.

Flow and wakes in large wind farms in complex terrain and offshore

Power losses due to wind turbine wakes are of the order of 10 and 20% of total power output in large wind farms. The focus of this research carried out within the EC funded UPWIND project is wind speed and turbulence modelling for large wind farms/wind turbines in complex terrain and offshore in order to optimise wind farm layouts to reduce wake losses and loads.

Flow and wakes in complex terrain and offshore. Model development and verification in UPWIND

The paper presents research conducted in the Flow workpackage of the EU funded UPWIND project which focuses on improving models for flow within and downwind of large wind farms in complex terrain and offshore. The main activity is modelling the behaviour of wind turbine wakes in order to improve power output predictions.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Electrodynamic tether at Jupiter II:Fast moon tour after capture

An electrodynamic bare-tether mission to Jupiter,following the capture of a spacecraft (SC) into an equatorial highly elliptical orbit with perijove at about 1.3 times the Jovian radius, is discussed. Repeated applications of the propellantless Lorentz drag on a spinning tether, at the perijove vicinity, can progressively lower the apojove at constant perijove, for a tour of Galilean moons. Electrical energy is generated and stored as the SC moves from an orbit at 1 : 1 resonance with a moon, down to resonance with the next moon; switching tether current off, stored power is then used as the SC makes a number of flybys of each moon. Radiation dose is calculated throughout the mission,during capture, flybys and moves between moons. The tour mission is limited by both power needs and accumulated dose. The three-stage apojove lowering down to Ganymede, Io, and Europa resonances would total less than 14 weeks, while 4 Ganymede, 20 Europa, and 16 Io flybys would add up to 18 weeks, with the entire mission taking just over seven months and the accumulated radiation dose keeping under 3 Mrad (Si) at 10-mm Al shield thickness.