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.
Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization
Sae Int. J. Alt. Power
Sae International Journal of Alternative Powertrains ; 6 , 1 ; 1-14
2017-04-11
14 pages
Conference paper
English
An Application of Ant Colony Optimization to Energy Efficient Routing for Electric Vehicles
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