Railway vehicle modelling for the vehicle-track interaction compatibility analysis

Railway vehicle homologation, with respect to running dynamics, is addressed via dedicated norms. The results required, such as, accelerations and/or wheel-rail contact forces, obtained from experimental tests or simulations, must be available. Multibody dynamics allows the modelling of railway vehicles and their representation in real operations conditions, being the realism of the multibody models greatly influenced by the modelling assumptions. In this paper, two alternative multibody models of the Light Rail Vehicle 2000 (LRV) are constructed and simulated in a realistic railway track scenarios. The vehicle-track interaction compatibility analysis consists of two stages: the use of the simplified method described in the norm "UIC 518-Testing and Approval of Railway Vehicles from the Point of View of their Dynamic Behaviour-Safety-Track Fatigue-Running Behaviour" for decision making; and, visualization inspection of the vehicle motion with respect to the track via dedicated tools for understanding the mechanisms involved.

Estudo e análise das redes centradas em conteúdos

A Internet, conforme a conhecemos, foi projetada com base na pilha de protocolos TCP/IP, que foi desenvolvida nos anos 60 e 70 utilizando um paradigma centrado nos endereços individuais de cada máquina (denominado host-centric). Este paradigma foi extremamente bem-sucedido em interligar máquinas através de encaminhamento baseado no endereço IP. Estudos recentes demonstram que, parte significativa do tráfego atual da Internet centra-se na transferência de conteúdos, em vez das tradicionais aplicações de rede, conforme foi originalmente concebido. Surgiram então novos modelos de comunicação, entre eles, protocolos de rede ponto-a-ponto, onde cada máquina da rede pode efetuar distribuição de conteúdo (denominadas de redes peer-to-peer), para melhorar a distribuição e a troca de conteúdos na Internet. Por conseguinte, nos últimos anos o paradigma host-centric começou a ser posto em causa e apareceu uma nova abordagem de Redes Centradas na Informação (ICN - information-centric networking). Tendo em conta que a Internet, hoje em dia, basicamente é uma rede de transferência de conteúdos e informações, porque não centrar a sua evolução neste sentido, ao invés de comunicações host-to-host? O paradigma de Rede Centrada no Conteúdo (CCN - Content Centric Networking) simplifica a solução de determinados problemas de segurança relacionados com a arquitetura TCP/IP e é uma das principais propostas da nova abordagem de Redes Centradas na Informação. Um dos principais problemas do modelo TCP/IP é a proteção do conteúdo. Atualmente, para garantirmos a autenticidade e a integridade dos dados partilhados na rede, é necessário garantir a segurança do repositório e do caminho que os dados devem percorrer até ao seu destino final. No entanto, a contínua ineficácia perante os ataques de negação de serviço praticados na Internet, sugere a necessidade de que seja a própria infraestrutura da rede a fornecer mecanismos para os mitigar. Um dos principais pilares do paradigma de comunicação da CCN é focalizar-se no próprio conteúdo e não na sua localização física. Desde o seu aparecimento em 2009 e como consequência da evolução e adaptação a sua designação mudou atualmente para Redes de Conteúdos com Nome (NNC – Named Network Content). Nesta dissertação, efetuaremos um estudo de uma visão geral da arquitetura CCN, apresentando as suas principais características, quais os componentes que a compõem e como os seus mecanismos mitigam os tradicionais problemas de comunicação e de segurança. Serão efetuadas experiências com o CCNx, que é um protótipo composto por um conjunto de funcionalidades e ferramentas, que possibilitam a implementação deste paradigma. O objetivo é analisar criticamente algumas das propostas existentes, determinar oportunidades, desafios e perspectivas para investigação futura.

Battery management system for electric racing cars

With the introduction of the electrics cars into the market new technologies regarding the battery are being developed and new problems to be solved, one of them the battery management system because each type of cell requires a specific way of handling. This research is done using the active research method to find out the actual problem on this subject and features a BMS should have, understand how they work and how to develop them applied to the purpose on this work. Once the features the BMS should have are clarified, it’s possible to develop a BMS for an electric racing car. The decisions are made taking into consideration the nature of the vehicle being developed. After the project done it’s clear to see that what was developed was not only the BMS itself but all the other factors around it, such as CAN communication, safety control, diagnostics and so on.

Multi-objective Parallel Particle Swarm Optimization for Day-ahead Vehicle-To-Grid Scheduling

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle- To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.

Autonomous bathymetry for risk assessment with ROAZ robotic surface vehicle

The use of unmanned marine robotic vehicles in bathymetric surveys is discussed. This paper presents recent results in autonomous bathymetric missions with the ROAZ autonomous surface vehicle. In particular, robotic surface vehicles such as ROAZ provide an efficient tool in risk assessment for shallow water environments and water land interface zones as the near surf zone in marine coast. ROAZ is an ocean capable catamaran for distinct oceanographic missions, and with the goal to fill the gap were other hydrographic surveys vehicles/systems are not compiled to operate, like very shallow water rivers and marine coastline surf zones. Therefore, the use of robotic systems for risk assessment is validated through several missions performed either in river scenario (in a very shallow water conditions) and in marine coastlines.

An efficient numerical scheme for solving multi-dimensional fractional optimal control problems with a quadratic performance index

The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

Manoeuvre Based Mission Control System for an Autonomous Surface Vehicle

In this work the mission control and supervision system developed for the ROAZ Autonomous Surface Vehicle is presented. Complexity in mission requirements coupled with flexibility lead to the design of a modular hierarchical mission control system based on hybrid systems control. Monitoring and supervision control for a vehicle such as ROAZ mission is not an easy task using tools with low complexity and yet powerful enough. A set of tools were developed to perform both on board mission control and remote planning and supervision. “ROAZ- Mission Control” was developed to be used in support to bathymetric and security missions performed in river and at seas.

ROAZ and ROAZ II Autonomous Surface Vehicle Design and Implementation

International Lifesaving Congress 2007, La Coruna, Spain, December, 2007

Forest fire detection with a small fixed wing autonomous aerial vehicle

In this work a forest fire detection solution using small autonomous aerial vehicles is proposed. The FALCOS unmanned aerial vehicle developed for remote-monitoring purposes is described. This is a small size UAV with onboard vision processing and autonomous flight capabilities. A set of custom developed navigation sensors was developed for the vehicle. Fire detection is performed through the use of low cost digital cameras and near-infrared sensors. Test results for navigation and ignition detection in real scenario are presented.

ROAZ Autonomous Surface Vehicle Design and Implementation

The design of an Autonomous Surface Vehicle for operation in river and estuarine scenarios is presented. Multiple operations with autonomous underwater vehicles and support to AUV missions are one of the main design goals in the ROAZ system. The mechanical design issues are discussed. Hardware, software and implementation status are described along with the control and navigation system architecture. Some preliminary test results concerning a custom developed thruster are presented along with hydrodynamic drag calculations by the use of computer fluid dynamic methods.

Swordfish: an Autonomous Surface Vehicle for Network Centric Operations

The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).

Autonomous Surface Vehicle Docking Manoeuvre with Visual Information

This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.