Congestion avoidance for recharging electric vehicles using smoothed particle hydrodynamics

In this paper, a novel approach for recharging electric vehicles (EVs) is proposed based on managing multiple discrete units of electric power flow, named energy demand particles (EDPs). Key similarities between EDPs and fluid particles (FPs) are established that allow the use of a smoothed particle hydrodynamics (SPH) method for scheduling the recharging times of EVs. It is shown, via simulation, that the scheduling procedure not only minimizes the variance of voltage drops in the secondary circuits, but it also can be used to implement a dynamic demand response and frequency control mechanism. The performance of the proposed scheduling procedure is also compared with alternative approaches recently published in the literature

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Smart Vehicle to Grid Interface Project: Electromobility Management System Architecture and Field Test Results

This paper presents and discusses the electromobility management system developed in the context of the SMARTV2G project, enabling the automatic control of plug-in electric vehicles' (PEVs') charging processes. The paper describes the architecture and the software/hardware components of the electromobility management system. The focus is put in particular on the implementation of a centralized demand side management control algorithm, which allows remote real time control of the charging stations in the field, according to preferences and constraints expressed by all the actors involved (in particular the distribution system operator and the PEV users). The results of the field tests are reported and discussed, highlighting critical issues raised from the field experience.Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

The role of operational research in green freight transportation

Recent years have witnessed an increased awareness of the negative external impacts of freight transportation. The field of Operational Research (OR) has, particularly in the recent years, continued to contribute to alleviating the negative impacts through the use of various optimization models and solution techniques. This paper presents the basic principles behind and an overview of the existing body of recent research on ‘greening’ freight transportation using OR-based planning techniques. The particular focus is on studies that have been described for two heavily used modes for transporting freight across the globe, namely road (including urban and electric vehicles) and maritime transportation, although other modes are also briefly discussed

DEVELOPMENT AND EVALUATION OF AN INTELLIGENT TRANSPORTATION SYSTEMS-BASED ARCHITECTURE FOR ELECTRIC VEHICLES

The rapid development of increasingly complex in-vehicle electronics now offers an unprecedented level of convenience and versatility as well as accelerates the demand for connected driving experience, which can only be achieved in a comprehensive Intelligent Transportation Systems (ITS) technology based architecture. While a number of charging and range related issues continue to impede the Electric Vehicle (EV) market growth, integrating ITS technologies with EVs has the potential to address the problems and facilitate EV operations. This dissertation presents an ITS based vehicle infrastructure communication architecture in which abundant information can be exchanged in real time through vehicle-to-vehicle and vehicle-to- infrastructure communication, so that a variety of in-vehicle applications can be built to enhance the performance of EVs. This dissertation emphasizes on developing two applications that are specifically designed for EVs. First, an Ant Colony Optimization (ACO) based routing and recharging strategy dedicated to accommodate EV trips was devised. The algorithm developed in this study seeks, in real time, the lowest cost route possible without violating the energy constraint and can quickly provide an alternate suboptimal route in the event of unexpected situations (such as traffic congestion, traffic incident and road closure). If the EV battery requires a recharge, the algorithm can be utilized to develop a charging schedule based on recharging locations, recharging cost and wait time, and to simultaneously maintain the minimum total travel time and energy consumption objectives. The author also elucidates a charge scheduling model that maximizes the net profit for each vehicle-to-grid (V2G) enabled EV owner who participates in the grid ancillary services while the energy demands for their trips can be guaranteed as well. By applying ITS technologies, the charge scheduling model can rapidly adapt to changes of variables or coefficients within the model for the purpose of developing the latest optimal charge/discharge schedule. The performance of EVs involved in the architecture was validated by a series of simulations. A roadway network in Charleston, SC was created in the simulator and a comparison between ordinary EVs and connected EVs was performed with a series of simulation experiments. Analysis revealed that the vehicle-to-vehicle and vehicle-to- infrastructure communication technology resulted in not only a reduction of the total travel time and energy consumption, but also in the reduction of the amount of the recharged electricity and corresponding cost, thus significantly relieving the concerns of range anxiety. The routing and recharging strategy also potentially allows for a reduction in the EV battery capacity, in turn reducing the cost of the energy storage system to a reasonable level. The efficiency of the charge scheduling model was validated by estimating optimal annual financial benefits and leveling the additional load from EV charging to maintain a reliable and robust power grid system. The analysis showed that the scheduling model can indeed optimize the profit which substantially offsets the annual energy cost for EV owners and that EV participants can even make a positive net profit with a higher power of the electrical circuit. In addition, the extra load distribution from the optimized EV charging operations was more balanced than that from the unmanaged EV operations. Grid operators can monitor and ease the load in real time by adjusting the prices should the load exceed the capacity. The ITS supported architecture presented in this dissertation can be used in the evolution of a new generation of EVs with new features and benefits for prospective owners. This study suggests a great promise for the integration of EVs with ITS technologies for purpose of promoting sustainable transportation system development