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

Authors :
Chu, Hongqing
Li, Zongxuan
Wang, Jialin
Hong, Jinlong
Source :
Energies (19961073). Sep2023, Vol. 16 Issue 17, p6163. 21p.
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19961073
Volume :
16
Issue :
17
Database :
Academic Search Index
Journal :
Energies (19961073)
Publication Type :
Academic Journal
Accession number :
171858425
Full Text :
https://doi.org/10.3390/en16176163