Deborah Perrotta

A HLA-based multi-resolution approach to simulating electric vehicles in simulink and SUMO

Traffic congestion affects not only the economic activity of cities but is also responsible for air quality and global warming problems. The employment of electric buses in metropolitan transportation as an alternative to internal combustion engine buses appears to be a promising eco-sustainable solution. However, an important aspect in evaluating the performance and adequateness of such vehicles is the fact they are immersed in an urban context. This work follows a HLA-based distributed architecture for electric bus powertrain simulation within a realistic urban mobility environment. In that sense, it discusses on coupling the SUMO (Simulation of Urban MObility) microscopic traffic simulator with a model of an electric bus powertrain subsystem designed in the MatLab/Simulink environment. Both the electric bus traction subsystems and the integration have been validated using field test experimental data. The proposed simulation framework is multi-faceted. As a matter of fact it can be used, not only as electric vehicle evaluation tool under different dynamics of traffic conditions and driving behavior, but also as a planner for charging strategies and optimizations.

Driver Attitude and Its Influence on the Energy Waste of Electric Buses

The objective of this paper is to analyze the influence of different driver behaviors on the energy consumption of electric buses. It shows that risk-taking attitudes on traffic are not only dangerous to the driver, to the bus users and to the surroundings, but also promotes a poorer performance of the vehicle itself, increasing its energy consumption and reducing the amount of energy that can be recovered on regenerative braking.

Ontologies for Research Data Description: A Design Process Applied to Vehicle Simulation

Data description is an essential part of research data management, and it is easy to argue for the importance of describing data early in the research workflow. Specific metadata schemas are often proposed to support description. Given the diversity of research domains, such schemas are often missing, and when available they may be too generic, too complex or hard to incorporate in a description platform. In this paper we present a method used to design metadata models for research data description as ontologies. Ontologies are gaining acceptance as knowledge representation structures, and we use them here in the scope of the Dendro platform. The ontology design process is illustrated with a case study from Vehicle Simulation. According to the design process, the resulting model was validated by a domain specialist.

Towards the integration of electric buses in conventional bus fleets

Private individual transportation is becoming cumbersome and expensive, as urban traffic turns more chaotic, fuel prices increase and the effects of pollutant emissions become evident. Public buses are an attractive approach to reducing the cars in use, as they mostly depend on preexistent infrastructure. Making these buses electric would mean even less tailpipe emissions and cheaper consumption costs, when compared to conventional vehicle fleets. However, fully electric bus fleets can prove disadvantageous. We can tackle this with a more conservative approach - using mixed bus fleets, comprised by both electric and conventional buses. This work intends on studying how to obtain a good balance of the different vehicle typologies in the fleet. To fulfill these goals, real data of a bus network in Porto, Portugal, is studied and an evolutionary algorithm devises mixed fleet arrangements, with a brief sensitivity analysis giving us an overview of how to improve our results. As a means of decision support, this work contributes not only with an approach to configure optimized mixed bus fleets, but also with general considerations for managing public transit with electric vehicle fleets.

On the validation of an electric bus simulation model through sensitivity analysis

In the contemporary world, simulation has been gaining a huge importance due to the cost reduction it promotes on many different areas. This paper proposes a validation methodology for the simulation model of an electric bus. This methodology consists in applying the sensitivity analysis method to assess the robustness of the model, compared to real data collected for different scenarios. Data were collected from the operation of the real bus and used in the validation process, which could demonstrate that the models outcomes are valid within a range of changes in the parameters analyzed, namely number of passengers and accessories energy consumption.