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Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles

Journal Article · · Transportation Research Record: Journal of the Transportation Research Board
 [1];  [2];  [3];  [4]
  1. Center for Sustainable Mobility, Virginia Tech Transportation Institute, Blacksburg, VA; OSTI
  2. Center for Sustainable Mobility, Virginia Tech Transportation Institute, Blacksburg, VA
  3. Center for Sustainable Mobility, Virginia Tech Transportation Institute, Blacksburg, VA; College of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Alexandria, Egypt
  4. Charles E. Via, Jr. Department of Civil and Environmental Engineering, Center for Sustainable Mobility, Virginia Tech Transportation Institute, Blacksburg, VA
+ Show Author Affiliations

This paper develops a multi-objective eco-routing algorithm (eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared with highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single-objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,”“moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared with the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

Research Organization:
Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
EE0008209
OSTI ID:
1980942
Journal Information:
Transportation Research Record: Journal of the Transportation Research Board, Journal Name: Transportation Research Record: Journal of the Transportation Research Board Journal Issue: 12 Vol. 2675; ISSN 0361-1981
Publisher:
SAGE
Country of Publication:
United States
Language:
English

References (16)

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Estimation of Origin-Destination Matrices: Relationship Between Practical and Theoretical Considerations
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journal January 2003
Electric Vehicles Energy Efficient Routing Using Ant Colony Optimization journal April 2017
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City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts journal January 2019
Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration journal April 2018

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Engineering
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