Plug-in Electric Vehicle to Cloud Data Analytics for Charging Management

Abstract

Electric, plug in electric and plug in hybrid electric vehicles (xEVs) are receiving an utmost attention from automobile industries, policymakers, R&D agencies and vehicle vendors in the contemporary smart transportation era. Penetration of electric vehicle fleet into the existing charging infrastructure multiplies the load on the underlying grid system. Smart grid technologies in collaboration with smart charging management strategies may circumvent the power load, thus enabling a reliable, efficient, consistent and flexible operation of the underlying power grid system. This work demonstrates commercially viable multi-tier cloud enabled vehicle to cloud (V2C) smart fleet charging model for coordinating the charging of xEVs fleet that can support vehicle mobility satisfying the triangle equivalence namely minimum charging tariff, shortest travelling distance and minimum waiting time at the charging station. Following a multi-tier cloud infrastructure for interactive and real-time control and monitoring of the massive vehicle fleet, this work also highlights the Big Data research thrusts, opportunities and challenges that are being evolved due to integration of a distributed cloud framework with the intelligent entities like smart meters, smart charging stations, xEVs etc. for commercial viability, implementation and deployment of emerging transport oriented cities (TOCs).