An introduction to swarm robotics

Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.

An introduction to flow and transport in fractal models of porous media: Part I

This special issue gathers together a number of recent papers on fractal geometry and its applications to the modeling of flow and transport in porous media. The aim is to provide a systematic approach for analyzing the statics and dynamics of fluids in fractal porous media by means of theory, modeling and experimentation. The topics covered include lacunarity analyses of multifractal and natural grayscale patterns, random packing's of self-similar pore/particle size distributions, Darcian and non-Darcian hydraulic flows, diffusion within fractals, models for the permeability and thermal conductivity of fractal porous media and hydrophobicity and surface erosion properties of fractal structures.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

Hybridizing concentrated solar power (CSP) with biogas and biomethane as an alternative to natural gas: Analysis of environmental performance using LCA

Concentrating Solar Power (CSP) plants typically incorporate one or various auxiliary boilers operating in parallel to the solar field to facilitate start up operations, provide system stability, avoid freezing of heat transfer fluid (HTF) and increase generation capacity. The environmental performance of these plants is highly influenced by the energy input and the type of auxiliary fuel, which in most cases is natural gas (NG). Replacing the NG with biogas or biomethane (BM) in commercial CSP installations is being considered as a means to produce electricity that is fully renewable and free from fossil inputs. Despite their renewable nature, the use of these biofuels also generates environmental impacts that need to be adequately identified and quantified. This paper investigates the environmental performance of a commercial wet-cooled parabolic trough 50 MWe CSP plant in Spain operating according to two strategies: solar-only, with minimum technically viable energy non-solar contribution; and hybrid operation, where 12 % of the electricity derives from auxiliary fuels (as permitted by Spanish legislation). The analysis was based on standard Life Cycle Assessment (LCA) methodology (ISO 14040-14040). The technical viability and the environmental profile of operating the CSP plant with different auxiliary fuels was evaluated, including: NG; biogas from an adjacent plant; and BM withdrawn from the gas network. The effect of using different substrates (biowaste, sewage sludge, grass and a mix of biowaste with animal manure) for the production of the biofuels was also investigated. The results showed that NG is responsible for most of the environmental damage associated with the operation of the plant in hybrid mode. Replacing NG with biogas resulted in a significant improvement of the environmental performance of the installation, primarily due to reduced impact in the following categories: natural land transformation, depletion of fossil resources, and climate change. However, despite the renewable nature of the biofuels, other environmental categories like human toxicity, eutrophication, acidification and marine ecotoxicity scored higher when using biogas and BM.

Efficient algorithms for dynamic probabilistic safety assessment. An application to convex damage domain.

The design of nuclear power plant has to follow a number of regulations aimed at limiting the risks inherent in this type of installation. The goal is to prevent and to limit the consequences of any possible incident that might threaten the public or the environment. To verify that the safety requirements are met a safety assessment process is followed. Safety analysis is as key component of a safety assessment, which incorporates both probabilistic and deterministic approaches. The deterministic approach attempts to ensure that the various situations, and in particular accidents, that are considered to be plausible, have been taken into account, and that the monitoring systems and engineered safety and safeguard systems will be capable of ensuring the safety goals. On the other hand, probabilistic safety analysis tries to demonstrate that the safety requirements are met for potential accidents both within and beyond the design basis, thus identifying vulnerabilities not necessarily accessible through deterministic safety analysis alone. Probabilistic safety assessment (PSA) methodology is widely used in the nuclear industry and is especially effective in comprehensive assessment of the measures needed to prevent accidents with small probability but severe consequences. Still, the trend towards a risk informed regulation (RIR) demanded a more extended use of risk assessment techniques with a significant need to further extend PSA’s scope and quality. Here is where the theory of stimulated dynamics (TSD) intervenes, as it is the mathematical foundation of the integrated safety assessment (ISA) methodology developed by the CSN(Consejo de Seguridad Nuclear) branch of Modelling and Simulation (MOSI). Such methodology attempts to extend classical PSA including accident dynamic analysis, an assessment of the damage associated to the transients and a computation of the damage frequency. The application of this ISA methodology requires a computational framework called SCAIS (Simulation Code System for Integrated Safety Assessment). SCAIS provides accident dynamic analysis support through simulation of nuclear accident sequences and operating procedures. Furthermore, it includes probabilistic quantification of fault trees and sequences; and integration and statistic treatment of risk metrics. SCAIS comprehensively implies an intensive use of code coupling techniques to join typical thermal hydraulic analysis, severe accident and probability calculation codes. The integration of accident simulation in the risk assessment process and thus requiring the use of complex nuclear plant models is what makes it so powerful, yet at the cost of an enormous increase in complexity. As the complexity of the process is primarily focused on such accident simulation codes, the question of whether it is possible to reduce the number of required simulation arises, which will be the focus of the present work. This document presents the work done on the investigation of more efficient techniques applied to the process of risk assessment inside the mentioned ISA methodology. Therefore such techniques will have the primary goal of decreasing the number of simulation needed for an adequate estimation of the damage probability. As the methodology and tools are relatively recent, there is not much work done inside this line of investigation, making it a quite difficult but necessary task, and because of time limitations the scope of the work had to be reduced. Therefore, some assumptions were made to work in simplified scenarios best suited for an initial approximation to the problem. The following section tries to explain in detail the process followed to design and test the developed techniques. Then, the next section introduces the general concepts and formulae of the TSD theory which are at the core of the risk assessment process. Afterwards a description of the simulation framework requirements and design is given. Followed by an introduction to the developed techniques, giving full detail of its mathematical background and its procedures. Later, the test case used is described and result from the application of the techniques is shown. Finally the conclusions are presented and future lines of work are exposed.

An approach to stakeholders involvement in the preparedness for nuclear and radiological emergency response & recovery in Spain

The elaboration of a generic decision-making strategy to address the evolution of an emergency situation, from the stages of response to recovery, and including a planning stage, can facilitate timely, effective and consistent decision making by the response organisations at every level within the emergency management structure and between countries, helping to ensure optimal protection of health, environment, and society. The degree of involvement of stakeholders in this process is a key strategic element for strengthening the local preparedness and response and can help a successful countermeasures strategy. A significant progress was made with the multi-national European project EURANOS (2004-2009) which brought together best practice, knowledge and technology to enhance the preparedness for Europe's response to any radiation emergency and long term contamination. The subsequent establishment of a European Technology Platform and the recent launch of the research project NERIS-TP ("Towards a self sustaining European Technology Platform (NERIS-TP) on Preparedness for Nuclear and Radiological Emergency Response and Recovery") are aimed to continue with the remaining tasks for gaining appropriate levels of emergency preparedness at local level in most European countries. One of the objectives of the NERIS-TP project is: Strengthen the preparedness at the local/national level by setting up dedicated fora and developing new tools or adapting the tools developed within the EURANOS projects (such as the governance framework for preparedness, the handbooks on countermeasures, the RODOS system, and the MOIRA DSS for long term contamination in catchments) to meet the needs of local communities. CIEMAT and UPM in close interaction with the Nuclear Safety Council will explore, within this project, the use and application in Spain of such technical tools, including other national tools and information and communication strategies to foster cooperation between local, national and international stakeholders. The aim is identify and involve relevant stakeholders in emergency preparedness to improve the development and implementation of appropriate protection strategies as part of the consequence management and the transition to recovery. In this paper, an overview of the "state of the art" on this area in Spain and the methodology and work Plan proposed by the Spanish group within the project NERIS to grow the stakeholder involvement in the preparedness to emergency response and recovery is presented.

A process for managing interaction between experimenters to get useful similar replications

Context: A replication is the repetition of an experiment. Several efforts have been made to adopt replication as a common practice in software engineering. There are different types of replications, depending on their purpose. Similar replications keep the experimental conditions as alike as possible to the original ones. External similar replications, where the replicating experimenters are not the same people as the original experimenters, have been a stumbling block. Several attempts at combining the results of replications have resulted in failure. Software engineering does not appear to be well suited to such replications, because it works with complex experimentally immature contexts. Software engineering settings have a large number of variables, and the role that many of them play is unknown. A successful (or useful) similar replication helps to better understand the phenomenon under study by verifying results and/or identifying contextual variables that could influence (or not) the results, through the combination of experimental results. Objective: To be able to get successful similar replications, there needs to be interaction between original and replicating experimenters. In this paper, we propose an interaction process for achieving successful similar replications. Method: This process consists of: an adaptation meeting, where experimenters tailor the experiment to the new setting; querying, to settle occasional inquiries while the experiment is being run; and a combination meeting, where experimenters meet to discuss the combination of replication outcomes with previous results. To check its effectiveness, the process has been tested on three different replications of the same experiment. Results: The proposed interaction process has helped to identify new contextual variables that could potentially influence (or not) the experimental results in the three replications run. Additionally, the interaction process has helped to uncover certain problems and deviations that occurred during some of the replications that we would have not been aware of otherwise. Conclusions: There are signs that suggest that it is possible to get successful similar replications in soft- ware engineering experimentation, when there is appropriate interaction among experimenters.

Water option contracts for reducing water supply risks: an application to the Tagus-Segura Transfer

El agua es un recurso cada vez más escaso y valioso. Por ello, los recursos hídricos disponibles deben asignarse de una forma eficiente entre los diferentes usos. El cambio climático aumentará la frecuencia y severidad de los eventos extremos, y podría incrementar la demanda de agua de los cultivos. El empleo de mecanismos flexibles de asignación de agua puede ser imprescindible para hacer frente a este aumento en la variabilidad del balance hídrico y para asegurar que los riesgos de suministro, y no solo los recursos, son compartidos de manera eficiente entre los usuarios. Los mercados de agua permiten la reasignación de los recursos hídricos, favoreciendo su transferencia desde los usos de menor a los de mayor valor. Diferentes tipos de mercados de agua se han establecido en diferentes partes del mundo, ayudando a los participantes a afrontar los problemas de escasez de agua en esas zonas. En España, los intercambios de agua están permitidos desde 1999, aunque la participación de los usuarios en el mercado ha sido limitada. Hay varios aspectos de los mercados de agua en España que deben mejorarse. Esta tesis, además de proponer una serie de cambios en el marco regulatorio, propone la introducción de contratos de opción de agua como una posible mejora. La principal ventaja de este tipo de contratos es la estabilidad legal e institucional que éstos proporcionan tanto a compradores como vendedores. Para apoyar esta propuesta, se han llevado a cabo diferentes análisis que muestran el potencial de los contratos de opción como herramienta de reducción del riesgo asociado a una oferta de agua inestable. La Cuenca del Segura (Sureste de España), la Cuenca del Tajo y el Acueducto Tajo- Segura han sido seleccionados como casos de estudio. Tres análisis distintos aplicados a dicha región se presentan en esta tesis: a) una evaluación de los contratos de opción como mecanismo para reducir los riesgos de disponibilidad de agua sufridos por los regantes en la Cuenca del Segura; b) un marco teórico para analizar las preferencias de los regantes por diferentes mecanismos de gestión del riesgo de disponibilidad de agua, su disposición a pagar por ellos y los precios aproximados de estos instrumentos (seguro de sequía y contratos de opción de agua); y c) una evaluación del papel de los contratos de opción en las decisiones de aprovisionamiento de agua de una comunidad de regantes ante una oferta de agua incierta. Los resultados muestran el potencial de reducción del riesgo de los contratos de opción para regantes en España, pero pueden ser extrapolados a otros sectores o regiones. Las principales conclusiones de esta tesis son: a) la agricultura será uno de los sectores más afectados por el cambio climático. Si los precios del agua aumentan, la rentabilidad de los cultivos puede caer hasta niveles negativos, lo que podría dar lugar al abandono de cultivos de regadío en algunas zonas de España. Las políticas de cambio climático y de agua deben estar estrechamente coordinadas para asegurar un uso de agua eficiente y la rentabilidad de la agricultura; b) aunque los mercados de agua han ayudado a algunos usuarios a afrontar problemas de disponibilidad del recurso en momentos de escasez, hay varios aspectos que deben mejorarse; c) es necesario desarrollar mercados de agua más flexibles y estables para garantizar una asignación eficiente de los recursos entre los usuarios de agua; d) los resultados muestran los beneficios derivados del establecimiento de un contrato de opción entre usuarios de agua del Tajo y del Segura para reducir el riesgo de disponibilidad de agua en la cuenca receptora; e) la disposición a pagar de los regantes por un contrato de opción de agua o un seguro de sequía hidrológica, que representa el valor que tienen estos mecanismos para aquellos usuarios de agua que se enfrentan a riesgos relacionados con la disponibilidad del recurso, es consistente con los resultados obtenidos en estudios previos y superior al precio de mercado de estos instrumentos, lo que favorece la viabilidad de estos mecanismos de gestión del riesgo ; y f) los contratos de opción podrían ayudar a optimizar las decisiones de aprovisionamiento de agua bajo incertidumbre, proporcionando más estabilidad y flexibilidad que los mercados temporales de agua. ABSTRACT Water is becoming increasingly scarce and valuable. Thus, existing water resources need to be efficiently allocated among users. Climate change is expected to increase the frequency and severity of extreme events, and it may also increase irrigated crops' water demand. The implementation of flexible allocation mechanisms could be essential to cope with this increased variability of the water balance and ensure that supply risks, and not only water resources, are also efficiently shared and managed. Water markets allow for the reallocation of water resources from low to high value uses. Different water trading mechanisms have been created in different parts of the world and have helped users to alleviate water scarcity problems in those areas. In Spain, water trading is allowed since 1999, although market activity has been limited. There are several issues in the Spanish water market that should be improved. This thesis, besides proposing several changes in the legislative framework, proposes the introduction of water option contracts as a potential improvement. The main advantage for both buyer and seller derived from an option contract is the institutional and legal stability it provides. To support this proposal, different analyses have been carried out that show the potential of option contracts as a risk reduction tool to manage water supply instability. The Segura Basin (Southeast Spain), the Tagus Basin and the Tagus-Segura inter-basin Transfer have been selected as the case study. Three different analyses applied to this region are presented in this thesis: a) an evaluation of option contracts as a mechanisms to reduce water supply availability risks in the Segura Basin; b) a theoretical framework for analyzing farmer’s preferences for different water supply risk management tools and farmers’ willingness to pay for them, together with the assessment of the prices of these mechanisms (drought insurance and water option contracts); and c) an evaluation of the role of option contracts in water procurement decisions under uncertainty. Results show the risk-reduction potential of option contracts for the agricultural sector in Spain, but these results can be extrapolated to other sectors or regions. The main conclusions of the thesis are: a) agriculture would be one of the most affected sectors by climate change. With higher water tariffs, crop’s profitability can drop to negative levels, which may result in the abandoning of the crop in many areas. Climate change and water policies must be closely coordinated to ensure efficient water use and crops’ profitability; b) although Spanish water markets have alleviated water availability problems for some users during water scarcity periods, there are several issues that should be improved; c) more flexible and stable water market mechanisms are needed to allocate water resources and water supply risks among competing users; d) results show the benefits derived from the establishment of an inter-basin option contract between water users in the Tagus and the Segura basins for reducing water supply availability risks in the recipient area; e) irrigators’ willingness to pay for option contracts or drought insurance, that represent the value that this kind of trading mechanisms has for water users facing water supply reliability problems, are consistent with results obtained in previous works and higher than the prices of this risk management tools, which shows the feasibility of these mechanisms; and f) option contracts would help to optimize water procurement decisions under uncertainty, providing more flexibility and stability than the spot market.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

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.

Introduction to Special issue on Reconfigurable computing and FPGAs

During the last three decades, FPGA technology has quickly evolved to become a major subject of research in computer and electrical engineering as it has been identified as a powerful alternative for creating highly efficient computing systems. FPGA devices offer substantial performance improvements when compared against traditional processing architectures via custom design and reconfiguration capabilities.