A Conventional Internal Combustion Engine Versus a Range Extended Electric Vehicle Under the Current Regulatory Regime in the United Kingdom

Transport accounts for 22% of greenhouse gas emissions in the United Kingdom and cars are expected tomore than double by 2050. Car manufacturers are continually aiming for a substantially reduced carbonfootprint through improved fuel efficiency and better powertrain performance due to the strict EuropeanUnion emissions standards. However, road tax, not just fuel efficiency, is a key consideration of consumerswhen purchasing a car. While measures have been taken to reduce emissions through stricter standards, infuture, alternative technologies will be used. Electric vehicles, hybrid vehicles and range extended electricvehicles have been identified as some of these future technologies. In this research a virtual test bed of aconventional internal combustion engine and a range extended electric vehicle family saloon car were builtin AVL’s vehicle and powertrain system level simulation tool, CRUISE, to simulate the New EuropeanDrive Cycle and the results were then soft-linked to a techno-economic model to compare the effectivenessof current support mechanisms over the full life cycle of both cars. The key finding indicates that althoughcarbon emissions are substantially reduced, switching is still not financially the best option for either theconsumer or the government in the long run.

A wavelet based drive-by bridge inspection system

This paper investigates a low-cost wavelet-based approach for the preliminary monitoring of bridge structures, consisting of the use of a vehicle fitted with accelerometers on its axles. The approach aims to reduce the need for direct instrumentation of the bridge. A time-frequency analysis is carried out in order to identify the existence and location of damage from vehicle accelerations. Firstly, in theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach. A number of damage indicators are evaluated and compared. A range of parameters such as the bridge span, vehicle speed, damage level and location, signal noise and road roughness are varied in simulations. Secondly, a scaled laboratory experiment is carried out to validate the results of the theoretical analysis and assess the ability of the selected damage indicators to detect changes in the bridge response from vehicle accelerations. 

Development of a Vehicle-Bridge-Soil Dynamic Interaction Model for Scour Damage Modelling

Damage detection in bridges using vibration-based methods is an area of growing research interest. Improved assessment
methodologies combined with state-of-the-art sensor technology are rapidly making these approaches applicable for real-world
structures. Applying these techniques to the detection and monitoring of scour around bridge foundations has remained
challenging; however this area has gained attraction in recent years. Several authors have investigated a range of methods but
there is still significant work required to achieve a rounded and widely applicable methodology to detect and monitor scour.This
paper presents a novel Vehicle-Bridge-Soil Dynamic Interaction (VBSDI) model which can be used to simulate the effect of scour
on an integral bridge. The model outputs dynamic signals which can be analysed to determine modal parameters and the variation
of these parameters with respect to scour can be examined.The key novelty of this model is that it is the first numerical model for
simulating scour that combines a realistic vehicle loadingmodel with a robust foundation soil responsemodel.This paper provides a
description of the model development and explains the mathematical theory underlying themodel. Finally a case study application
of the model using typical bridge, soil, and vehicle properties is provided.

Determining the Presence of Scour around Bridge Foundations Using Vehicle-Induced Vibrations

Bridge scour is the number one cause of failure in bridges located over waterways. Scour leads to rapid losses in foundation stiffness and can cause sudden collapse. Previous research on bridge health monitoring has used changes in natural frequency to identify damage in bridge beams. The possibility of using a similar approach to identifying scour is investigated in this paper. To assess if this approach is feasible, it is necessary to establish how scour affects the natural frequency of a bridge, and if it is possible to measure changes in frequency using the bridge dynamic response to a passing vehicle. To address these questions, a novel vehicle–bridge–soil interaction (VBSI) model was developed. By carrying out a modal study in this model, it is shown that for a wide range of possible soil states, there is a clear reduction in the natural frequency of the first mode of the bridge with scour. Moreover, it is shown that the response signals on the bridge from vehicular loading are sufficient to allow these changes in frequency to be detected.

Selection of the most appropriate roadside vehicle restraint system – the SAVeRS project

Run Off Road (ROR) crashes are road accidents that often result in severe injuries or fatalities. To reduce the severity of ROR crashes, “forgiving roadsides” need to be designed and this includes identifying situations where there is a need for a Vehicle Restraint System (VRS) and what appropriate VRS should be selected for a specific location and traffic condition. Whilst there are standards covering testing, evaluation and classification of VRS within Europe (EN1317 parts 1 to 8), their selection, location and installation requirements are typically based upon national guidelines and standards, often produced by National Road Authorities (NRA) and/or overseeing organisations. Due to local conditions, these national guidelines vary across Europe.
The European SAVeRS project funded by CEDR has developed a practical and readily understandable VRS guidance document and a user-friendly software tool which allow designers and road administrations to select the most appropriate solution in different road and traffic conditions.
This paper describes the main outcomes of the project, the process to select the most appropriate roadside barrier, and the user friendly SAVeRS tool.

Determinants of uptake and maintenance of active commuting to school

The objective was to identify determinants of uptake and maintenance of active school travel (AST) over 4 years in children aged 9 at baseline. Data from wave 1 (n=8502) and 2 (n=7479) of the Growing Up in Ireland study were analysed. At 9- and 13-years 25% and 20% engaged in AST. Children were more likely to maintain or take-up AST if they lived in an urban area. Change in distance to school influenced both maintenance and adoption of AST, with a negative impact seen for increased distance between 9 and 13 years and a positive impact seen for decreased distance. Some factors which predict uptake and maintenance of AST are modifiable and can inform intervention development.

Effect of vehicle characteristics on safety, fuel use and emissions

Nos últimos anos, o número de vítimas de acidentes de tráfego por milhões de habitantes em Portugal tem sido mais elevado do que a média da União Europeia. Ao nível nacional torna-se premente uma melhor compreensão dos dados de acidentes e sobre o efeito do veículo na gravidade do mesmo. O objetivo principal desta investigação consistiu no desenvolvimento de modelos de previsão da gravidade do acidente, para o caso de um único veículo envolvido e para caso de uma colisão, envolvendo dois veículos. Além disso, esta investigação compreendeu o desenvolvimento de uma análise integrada para avaliar o desempenho do veículo em termos de segurança, eficiência energética e emissões de poluentes. Os dados de acidentes foram recolhidos junto da Guarda Nacional Republicana Portuguesa, na área metropolitana do Porto para o período de 2006-2010. Um total de 1,374 acidentes foram recolhidos, 500 acidentes envolvendo um único veículo e 874 colisões. Para a análise da segurança, foram utilizados modelos de regressão logística. Para os acidentes envolvendo um único veículo, o efeito das características do veículo no risco de feridos graves e/ou mortos (variável resposta definida como binária) foi explorado. Para as colisões envolvendo dois veículos foram criadas duas variáveis binárias adicionais: uma para prever a probabilidade de feridos graves e/ou mortos num dos veículos (designado como veículo V1) e outra para prever a probabilidade de feridos graves e/ou mortos no outro veículo envolvido (designado como veículo V2). Para ultrapassar o desafio e limitações relativas ao tamanho da amostra e desigualdade entre os casos analisados (apenas 5.1% de acidentes graves), foi desenvolvida uma metodologia com base numa estratégia de reamostragem e foram utilizadas 10 amostras geradas de forma aleatória e estratificada para a validação dos modelos. Durante a fase de modelação, foi analisado o efeito das características do veículo, como o peso, a cilindrada, a distância entre eixos e a idade do veículo. Para a análise do consumo de combustível e das emissões, foi aplicada a metodologia CORINAIR. Posteriormente, os dados das emissões foram modelados de forma a serem ajustados a regressões lineares. Finalmente, foi desenvolvido um indicador de análise integrada (denominado “SEG”) que proporciona um método de classificação para avaliar o desempenho do veículo ao nível da segurança rodoviária, consumos e emissões de poluentes.Face aos resultados obtidos, para os acidentes envolvendo um único veículo, o modelo de previsão do risco de gravidade identificou a idade e a cilindrada do veículo como estatisticamente significativas para a previsão de ocorrência de feridos graves e/ou mortos, ao nível de significância de 5%. A exatidão do modelo foi de 58.0% (desvio padrão (D.P.) 3.1). Para as colisões envolvendo dois veículos, ao prever a probabilidade de feridos graves e/ou mortos no veículo V1, a cilindrada do veículo oposto (veículo V2) aumentou o risco para os ocupantes do veículo V1, ao nível de significância de 10%. O modelo para prever o risco de gravidade no veículo V1 revelou um bom desempenho, com uma exatidão de 61.2% (D.P. 2.4). Ao prever a probabilidade de feridos graves e/ou mortos no veículo V2, a cilindrada do veículo V1 aumentou o risco para os ocupantes do veículo V2, ao nível de significância de 5%. O modelo para prever o risco de gravidade no veículo V2 também revelou um desempenho satisfatório, com uma exatidão de 40.5% (D.P. 2.1). Os resultados do indicador integrado SEG revelaram que os veículos mais recentes apresentam uma melhor classificação para os três domínios: segurança, consumo e emissões. Esta investigação demonstra que não existe conflito entre a componente da segurança, a eficiência energética e emissões relativamente ao desempenho dos veículos.

Plataforma de informação e de apoio ao voo de aeronaves não tripuladas (UAV)

Trabalho de projeto de mestrado, Educação (Especialidade de Educação e Tecnologias Digitais), Universidade de Lisboa, Instituto de Educação, 2014