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E-platooning: Optimizing platoon formation for long-haul transportation with electric commercial vehicles

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  • Scholl, Joachim
  • Boysen, Nils
  • Scholl, Armin

Abstract

Recent technological developments allow to connect vehicles via digital data transmission, so that a queue of trucks can safely be driven in close proximity. The lower air resistance of these truck platoons decreases fuel consumption and, thus, contributes to reducing the carbon footprint of road-based freight transportation. The efficiency of platooning depends not only on the aerodynamic drag, which considerably reduces with decreasing inter-vehicle distance. Whether a suitable platooning partner can be found also depends on the trucks’ willingness-to-wait and on a successful platoon formation process. Electric vehicles have to wait while loading their batteries anyway. Therefore, it might be possible to successfully coordinate charging with waiting for partner trucks. Furthermore, driving in a platoon reduces energy consumption, so that electric trucks can increase their driving ranges, which gives them an additional motive for platooning. This paper provides optimization approaches to schedule the platoon formation process of electric commercial vehicles via a central platform. Given a set of trucks with predetermined routes and time windows for their on-time arrivals at their destinations, we derive driving, charging and platoon formation schedules, such that total energy costs are minimized. We formulate the problem, analyze its computational complexity, and provide a novel matheuristic. Its suitable performance is documented by extensive computational experiments. Furthermore, we apply our algorithm to quantify the performance gains when platooning electric trucks and benchmark these outcomes with individual driving schedules of electric trucks and with platoons of traditional trucks powered by a combustion engine.

Suggested Citation

  • Scholl, Joachim & Boysen, Nils & Scholl, Armin, 2023. "E-platooning: Optimizing platoon formation for long-haul transportation with electric commercial vehicles," European Journal of Operational Research, Elsevier, vol. 304(2), pages 525-542.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:2:p:525-542
    DOI: 10.1016/j.ejor.2022.04.013
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