Highlights ► Simulated varying charging networks of electric vehicles (EVs). ► Optimized the total time needed for the EV fast-charging process. ► Total time to recharge decreased with connected vehicle technologies. ► Total amount of charging power output is reduced with connected vehicle technology. ► Benefits increased with increased market penetration level of EVs.

    Abstract Due to the tremendous political, economical, and environmental pressures the transportation sector is facing, the United States finds itself devoting more energy to innovative solutions such as electric vehicle (EV) technologies. The purpose of this study was to analyze how utilizing real-time information dissemination transferring capabilities to vehicles, as envisioned in the “connected vehicle” system, could effectively facilitate the EV charging process at fast-charging stations (CS). By simulating a traffic network of EVs in MATLAB, it was found that the total time due to the battery charging process was optimized at both the individual EV and the entire network levels for EVs that were able to use connected vehicle communications. As a result of this optimization, the improvement of two vehicle parameters, extra travel time due to charging and time spent in the CS queue, as well as two CS parameters, queue length and total energy output, were measured. Through connected vehicle technologies, the average extra travel time due to charging and the average time spent in the CS queue were significantly reduced, resulting in benefits at both a network level and individual vehicle level. However, as a tradeoff of the optimization, the charging infrastructure may need to be upgraded in order to increase the capacity of the network. Most importantly, the benefits of connected vehicle systems were found to steadily increase as the market penetration level of EVs also increased in the varying simulation scenarios.


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    Title :

    Utilizing real-time information transferring potentials to vehicles to improve the fast-charging process in electric vehicles


    Contributors:


    Publication date :

    2012-10-26


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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