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Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization
ISSN: 2167-4191, e-ISSN: 2167-4205
Published April 11, 2017 by SAE International in United States
Citation: Abousleiman, R., Rawashdeh, O., and Boimer, R., "Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization," SAE Int. J. Alt. Power. 6(1):1-14, 2017, https://doi.org/10.4271/2017-01-9075.
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.