4.7 Article

Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks

Journal

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 23, Issue 8, Pages 11287-11300

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2021.3102496

Keywords

Energy consumption; Batteries; Fuels; Routing; Urban areas; Directed graphs; Torque; Vehicle routing; traffic control; energy management; intelligent vehicles

Funding

  1. NSF [ECCS-1509084, DMS-1664644, CNS-1645681]
  2. AFOSR [FA9550-19-1-0158]
  3. ARPA-E's NEXTCAR Program [DEAR0000796]
  4. MathWorks

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The study introduces an algorithm for eco-routing for PHEVs and validates its effectiveness using traffic data from the city of Boston, demonstrating significant energy savings of around 12%. The algorithm also shows near real-time execution time.
We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and an optimal power-train control strategy over this route. In order to show the effectiveness of our method in practice, we use a HERE Maps API to apply our algorithms based on traffic data in the city of Boston with more than 110,000 links. Moreover, we validate the performance of our eco-routing algorithm using speed profiles collected from a traffic simulator (SUMO) as input to a high-fidelity energy model to calculate energy consumption costs. Our results show significant energy savings (around 12%) for PHEVs with a near real-time execution time for the algorithm.

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