Cooperative transportation system for electric vehicles

Electric Vehicles (EVs) are being introduced in the market, but batteries reduced energy storage capacity and the lack of a high density charging infrastructure limit their autonomy range. In order to overcome this limitation, we propose developing a new solution enabling drivers to drive longer distances. This will be achieved by integrating some components of the cooperative transport infrastructure (charging system, public transport system and the vehicle), and by increasing driving autonomy through energy consumption reduction obtained with the improvement of driving efficiency. In this work we show how to create a cooperative system in a mobile device to integrate public transportation real time information in an EV. Integration of EVs with public transport system allows extension of driving autonomy beyond the storing capacity of vehicle’s batteries. Supplying information on availability, schedule and price of public transport allows the driver to plan the journey using EV and public transportation in a complementary way, using functions as car parking booking (and charging) and ticket buying. This information is integrated in a mobile device providing the driver with a collaborative holistic approach of different public transportation infrastructure sources, that can be combined with real traffic information, parking places and charging slots and current driver position, to support the driver decision making process.FEDER Funds - Operational Programme for Competitiveness Factors (COMPETE) PTDC/EEA-EEL/104569/2008 and the project MITPT/ EDAM-SMS/0030/2008.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EEA-EEL/104569/2008, MITPT/EDAM-SMS/0030/2008

Real-time information extraction of an electric vehicle

In this paper is presented the development of a project to extract, in real-time, information’s related with an Electric Vehicle (EV). This project was elaborated to extract data from an EV battery charging device developed at the University of Minho, and from an EV prototype, the VEECO (Veículo Eléctrico ECOlógico – Ecologic Electric Vehicle), developed in a cooperation project of ISEL (Lisbon Superior Institute of Engineering) and the Portuguese company VE. The main goal of this project consists in collecting and transmitting the extracted data to inform the EV driver about the performance and the real behavior of the EV. Thereby, it is created an open interface to manage, in real-time, the main data related with the EV, as the batteries SoC (State-of-Charge), the EV speed, and internal temperatures (like the temperatures of the batteries, motor and power electronics inverter), as well as to control the start and stop of the batteries charging process, and to optimize the charging program (to define the best algorithm to preserve the batteries lifespan). This interface also controls the discharging process of the batteries, in order to make possible to deliver back to the electrical power grid part of the stored energy in the batteries, which is defined by the concept Vehicle-to-Grid (V2G). In the paper are presented and described the two main parts of this work: the real-time information extraction system and the charging device.FEDER Funds - Operational Programme for Competitiveness Factors (COMPETE)Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EEA-EEL/104569/2008, MITPT/EDAM-SMS/0030/2008

Electric vehicle route recommender system

This paper presents a recommender system responsible for processing information that will help the driver in the daily use of his Electric Vehicle (EV), minimizing the problem of range anxiety through a personalized range prediction and by presenting in real time relevant information about the charging stations that can be reached within the range autonomy. Given the success of recommendation systems on automatic delivery of relevant information in numerous areas of usage, this type of systems can also be applied in the electric mobility scenario, with the objective of maximizing the relevance of the information presented to the driver, which should be the strictly needed data for the driver to make important decisions, filtering out the unnecessary information.This work is financed by FEDER Funds, through the Operational Programme for Competitiveness Factors – COMPETE, and by National Funds through FCT – Foundation for Science and Technology of Portugal, under the project PTDC/EEA-EEL/104569/2008 and the project MIT-PT/EDAM-SMS/0030/2008

Smart battery charger for electric mobility in smart grids

In this paper is presented the development of a smart batteries charger for Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs), aiming their integration in Smart Grids. The batteries charging process is controlled by an appropriate control algorithm, aiming to preserve the batteries lifespan. The main features of the equipment are the mitigation of the power quality degradation and the bidirectional operation, as Grid-to-Vehicle (G2V) and as Vehicle-to-Grid (V2G). During the charging process (G2V), the consumed current is sinusoidal and the power factor is unitary. Along the discharging process (V2G), when the equipment allows delivering back to the electrical power grid a small amount of the energy stored in the batteries, the current is also sinusoidal. The V2G mode of operation will be one of the main features of the Smart Grids, both to collaborate with the electrical power grid to increase stability, and to function as a distributed Energy Storage System (ESS). The functioning of the smart batteries charger is shown through simulation and experimental results, both during the charging (G2V) and the discharging (V2G) modes of operation. Also in this paper are shown and briefly described the roles of the key concepts related with the Smart Grids in terms of Systems and Functional Areas, Power Electronics Systems, and Electric Mobility.This work is financed by FEDER Funds, through the Operational Programme for Competitiveness Factors – COMPETE, and by National Funds through FCT – Foundation for Science and Technology of Portugal, under the project PTDC/EEA-EEL/104569/2008 and the project MIT-PT/EDAM-SMS/0030/2008

Mobile geographic range prediction for electric vehicles

Electric Vehicle (EV) requires new driver information systems because drivers need more information. The spread of mobile devices and communications cost reductions gives new business opportunities. Our work proposal is taking into account the range anxiety problem of drivers of EV and using GIS systems, we represent in a map the charging state range based on a predicting driving distance based on driving style, temperature, and charge level. All this information transferred and represented in a mobile device with a information integration of EV and public transportation.Fundação para a Ciência e a Tecnologia (FCT

Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.FCT – Fundação para a Ciência e Tecnologia within the Project Scope: Pest-OE/EEI/UI0319/2014

Data mining approach for range prediction of electric vehicle

Our work proposal is based on the past driving data that are stored in a driver profile, and using real time information about the Electric Vehicle parameters (e.g. speed and energy stored in the batteries), combined with external parameters (e.g. condi-tions of roads, traffic, and weather), determine the range autonomy accurately, taking into account the historical driver behavior. The driver profile is based on the stored data, which acts as training set for a Data Mining approach, in order to estimate the Electric Vehicle range. The Data Mining approach uses a regression model aiming to find the better range autonomy, which is used to represent the current Electric Vehicle range autonomy on a map.Fundação para a Ciência e a Tecnologia (FCT

Electric vehicle assistant based in driver profile

This paper presents the outcomes of a research work consisting in the development of an Electric Vehicle Assistant (EVA), which creates and stores a driver profile where are contained the driving behaviours related with the EV energy consumption, the EV battery charging information, and the performed routes. This is an application for mobile devices that is able to passively track the driver behaviour and to access several information related with the EV in real time. It is also proposed a range prediction approach based on probability to take into account unpredictable effects of personal driving style, traffic or weather.FCT -Fuel Cycle Technologies(SFRH/BD/80155/2011

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.FEDER Funds, through the Operational Programme for Competitiveness Factors – COMPETE, and by National Funds through FCT – Foundation for Science and Technology of Portugal, under the project FCOMP-01–0124-FEDER-02267

Vehicle-to-anything application (v2anything app) for electric vehicles

This paper presents a mobile information system denominated as Vehicle-to-Anything Application (V2Anything App), and explains its conceptual aspects. This application is aimed at giving relevant information to Full Electric Vehicle (FEV) drivers, by supporting the integration of several sources of data in a mobile application, thus contributing to the deployment of the electric mobility process. The V2Anything App provides recommendations to the drivers about the FEV range autonomy, location of battery charging stations, information of the electricity market, and also a route planner taking into account public transportations and car or bike sharing systems. The main contributions of this application are related with the creation of an Information and Communication Technology (ICT) platform, recommender systems, data integration systems, driver profile, and personalized range prediction. Thus, it is possible to deliver relevant information to the FEV drivers related with the electric mobility process, electricity market, public transportation, and the FEV performance.Fundação para a Ciência e Tecnologia (FCT