Growing concerns about the environment, energy dependency, and the unstable fuel prices have increased the sales of electric vehicles. Energy-efficient routing for electric vehicles requires novel algorithmic challenges because traditional routing algorithms are designed for fossil-fueled vehicles. Negative edge costs, battery power and capacity limits, vehicle parameters that are only available at query time, alongside the uncertainty make the task of electric vehicle routing a challenging problem. In this paper, we present a solution to the energy-efficient routing problem for electric vehicles using ant colony optimization. Simulation and real-world test results demonstrate savings in the energy consumption of electric vehicles when driven on the generated routes. Real-world test results revealed more than 9% improvements in the energy consumption of the electric vehicle when driven on the recommended route rather than the routes proposed by Google Maps and MapQuest.


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    Title :

    Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization


    Additional title:

    Sae Int. J. Alt. Power


    Contributors:


    Publication date :

    2017-04-11


    Size :

    14 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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