The introduction of Electric Vehicles (EVs) has placed a strain on the aged and already overworked electrical grid. With each EV requiring the same amount of power as 3 to 140 single family homes, depending on how fast the charge occurs, measures need to be taken in order to protect the electrical grid from serious damage. The electric grid renovations proposed by the U.S. department of energy, commonly referred to as the smart grid, could help accommodate an even greater EV penetration. The introduction of the smart grid and other cutting-edge technologies create the potential for applications which provide new consumer conveniences and aid in the preservation of the electrical grid. This thesis aims to create one such application through the production of a prototype system which takes advantage of current and in-development technologies in order to route an electric vehicle to the closest and least detrimental charge station based on current conditions. Traffic conditions are assessed based on data collected from both ITSs (Intelligent Transportation Systems) and VANETs (Vehicle Ad-hoc Networks), while grid information is gathered through the early stages of the Smart Grid. The system is hosted in a cloud environment base on the current trend of offloading Information Technology systems to the "cloud"; this also allows for the advantages of a shared data space between sub-systems. As part of the thesis the prototype system was put through a stress test in a simulated environment in order to both establish system requirements and determine scalability for use with larger maps. The system requirements were compared with the technical specifications of an off-the-shelf GPS routing device. It was determined that such a device could not handle routing with such extensive underlying data, and will require hosting the prototype in a cloud environment. The system was also used to perform a case study on charging station placement in the Greater Rochester area. It was determined that the current charging stations are insufficient for a significant number of electric vehicles and that adding even six stations would provide a greater EV operational area and provide a more uniform distribution of charging station usage.
Department, Program, or Center
Computer Engineering (KGCOE)
Decker, Christopher, "Electric vehicle charging and routing management via multi-infrastructure data fusion" (2012). Thesis. Rochester Institute of Technology. Accessed from
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