Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization

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.


  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01634201
  • Record Type: Publication
  • Source Agency: SAE International
  • Report/Paper Numbers: 2017-01-9075
  • Files: TRIS, SAE
  • Created Date: May 1 2017 9:45AM