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Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition

Author

Listed:
  • Hongqing Chu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Zongxuan Li

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Jialin Wang

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China)

  • Jinlong Hong

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

Abstract

Fuel-saving-oriented collaborative driving is a highly promising yet challenging endeavor that requires satisfying the driver’s operational intentions while surpassing the driver’s fuel-saving performance. In light of this challenge, the paper introduces an innovative collaborative driving strategy tailored to the objective of fuel conservation in the context of commercial vehicles. An enhancement to this strategy involves the development of a network prediction model for vehicle speed, leveraging insights from driver style recognition. Employing the predicted speed as a reference, a model-predictive-control-based optimal controller is designed to track the reference while optimizing fuel consumption. Furthermore, a straightforward yet effective collaborative rule is proposed to ensure alignment with the driver’s intention. Subsequently, the proposed control scheme is validated through simulation and real-world driving data, revealing that the human–machine cooperative driving controller saves 4% more fuel than human drivers.

Suggested Citation

  • Hongqing Chu & Zongxuan Li & Jialin Wang & Jinlong Hong, 2023. "Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition," Energies, MDPI, vol. 16(17), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6163-:d:1224468
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    References listed on IDEAS

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    1. Jia, Chunchun & Zhou, Jiaming & He, Hongwen & Li, Jianwei & Wei, Zhongbao & Li, Kunang & Shi, Man, 2023. "A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal- and health-constrained awareness," Energy, Elsevier, vol. 271(C).
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