Abstract

Electric vehicles are expected to become one of the key elements of future sustainable transportation systems. The first generation of electric cars are already commercially available but still, suffer from problems and constraints that have to be solved before a mass market might be created. Key aspects that will play an important role in modern electric vehicles are range extension, energy efficiency, safety, comfort as well as communication. An overall solution approach to integrating all these aspects is the development of advanced driver assistance systems to make electric vehicles more intelligent. Driver assistance systems are based on the integration of suitable sensors and actuators as well as electronic devices and software-enabled control functionality to automatically support the human driver. Driver assistance for electric vehicles will differ from the already used systems in fuel-powered cars such as electronic stability programs, adaptive cruise control etc. in a way that they must support energy efficiency while the system itself must also have a low power consumption. In this work, an eco-driving functionality as the first step towards those new driver assistance systems for electric vehicles will be investigated. Using information about the internal state of the car, navigation information as well as advanced information about the environment coming from sensors and network connections, an algorithm will be developed that will adapt the speed of the vehicle automatically to minimize energy consumption. From an algorithmic point of view, a stochastic model predictive control approach will be applied and adapted to the special constraints of the problem. Finally, the solution will be tested in simulations as well as in first experiments with a commercial electric vehicle in the SnT Automation & Robotics Research Group (SnT ARG).

Abstract

Freight transport is a crucial sector for the development of the economy and society, but it also produces negative impacts on the environment and the human health that must be considered. Intermodal freight transport represents an opportunity to achieve a transport of goods with enhanced environmental and competitive characteristics. Hence, intermodal freight transport consists in the transport of goods by at least two modes of transport, in the same loading unit (e.g. container), without handling the goods themselves when changing modes in an intermodal terminal. Intermodal freight transport leads to the shifting of road freight transport in long distances to others modes of transport with improved environmental performance such as rail freight transport and inland waterways transport. This thesis is concerned with a study of the environmental impacts of rail freight intermodality using a life cycle approach. The purpose of this research is to analyse the environmental impacts of the different inland freight transport modes in Belgium (focusing on rail freight transport), and their use in intermodal freight transport routes in Belgium and Europe. In this framework, the Life Cycle Assessment (LCA) methodology constitutes an effective tool to assess the environmental impact of the inland freight transport modes. The system perspective of the LCA methodology implies the need to analyse not only the direct processes related to the transport activity such as energy consumption and exhaust emissions, but also the processes connected with the electricity and fuel production, vehicles (e.g. locomotives and wagons, barges and lorries) and infrastructure (e.g. railway, inland waterways and road). This thesis studies the inland freight transport in Belgium from the period 2006 to 2012. It has been carried out the LCA of rail freight transport (distinguishing between electric and diesel traction), inland waterways transport and road freight transport independently. A comparison between the environmental impacts of these inland freight transport modes has been performed as well. Within rail freight transport, the environmental impacts of electric trains using the electricity supply mix of different European countries have been compared. Moreover, a detailed study of the life cycle phases of construction, maintenance and disposal of railway infrastructure has been conducted. Furthermore, the influence of load factor and emission engine technology in the environmental performance of road transport have been studied. In addition, a study of the environmental impacts of consolidated intermodal freight transport routes in Belgium and Europe have been carried out. The aim of this analysis is the comparison of the environmental impacts of these intermodal routes depending on the transport mode chosen for the major part of the intermodal route. Finally, this thesis studies the environmental impact of the modal splits of inland freight transport in Belgium for several scenarios such as the increase of rail freight transport as a result of the possible development of the intermodal rail freight transport or the optimization of the operational costs. It has been analysed how the change of the modal split and the improvement of the technology used by the different transport modes affects the environmental impacts of inland freight transport in Belgium.

Abstract

International audience; Semi-autonomous driving assistance systems have a high potential to improve the safety and efficiency of the battery electric vehicles that are enduring limited cruising range. This paper presents an ecologically advanced driver assistance system to extend the functionality of the adaptive cruise control system. A real-time stochastic non-linear model predictive controller with probabilistic constraints is presented to compute on-line the safe and energy-efficient cruising velocity profile. The individual chance-constraint is reformulated into a convex second-order cone constraint which is robust for a general class of probability distributions. Finally, the performance of proposed approach in terms of states regulation, constraints fulfilment, and energy efficiency is evaluated on a battery electric vehicle.

Abstract

In this paper we provide an overview of the I-GEAR (incentives and gaming environments for automobile routing) project that is intended to reduce traffic congestion in Luxembourg through the use of persuasive gaming. In order to illustrate some of the issues involved we also present an outline concept of a live game in which we propose to encourage the workshop participants to take part. If a sufficient number of workshop participants take part, this real life game could even be used as a small scale study within the project.