No abstract

This paper addresses the problem of determining the optimal fleet size of electric car sharing systems. We model the system as a Discrete Event System in a closed queueing network framework considering the specific requirements of the electric vehicle utilization. Hence, we describe the asymptotic behavior of the vehicles and develop an optimization problem for maximizing the system revenue by determining the optimal fleet size. The large-scale of real-world systems results in computational difficulties in obtaining the exact solution, and so an approximate formulation is provided. Some numerical results illustrate and validate the solution method. © 2014 IEEE

their attitude and degree of commitment to the innovations introduced by the electromobility framework.The contribution [2] is about the RESOLVE project dealing with the introduction of Electric L-Category Vehicles in order to reduce CO 2 and other pollutant emissions. The paper proposes a thorough analysis of the main objectives of the project, how to achieve them and its expected impact.In addition, [3] presents a regulatory framework for charging EVs: first, the agents are defined along with their peculiar features and the authors single out new agents for the electricity sector, i.e., the EV owner, the EV supplier-aggregator and the charging point manager. Hence, the specifics of the proposed framework are presented such as the grid connection, the communication and control equipment and the EV charging modes.The authors in [4] identify several key challenges derived by the mobility systems' electrification, also proposing an ecosystem model. Some of these challenges are technical and are related to the vehicles and the battery technology, e.g. the battery life cycle for used battery and the manufacturing process. Other challenges are related to the adopted policies, taxation strategies and market conditions. One of the most important challenges is definitely the lack of a common charging infrastructure.This paper proposes the definition of actors and their interrelations in the context of an electromobility network. Indeed, as a first step for the definition of a new common electromobility framework, it is necessary to clearly determine which actors could benefit from it and in which way they should interact and contribute to the smooth running of the network. First, we describe 9 macro-areas of actors which are grouped according to common features and/or needs. Then, we provide detailed descriptions of all the actors belonging to each macro-area. The description is performed by Unified Modeling Language (UML) class diagrams representing the interrelations between the macro-areas and the actors [9], [10].