Model Predictive Control for Hybrid Electric Vehicle Platooning Using Slope Information

Kaijiang Yu, Haizhu Yang, Xingguo Tan, Taketoshi Kawabe, Yanan Guo, Qing Liang, Ziyi Fu, Zheng Zheng

Research output: Contribution to journalReview article

35 Citations (Scopus)

Abstract

This paper presents a new model predictive control (MPC) system for hybrid electric vehicle (HEV) platooning using slope information to improve fuel economy. The new features of this study are as follows. First, a system for HEV platooning has been developed considering varying drag coefficients and road gradients. Second, the general model of the aerodynamic drag coefficient of different vehicles in a platoon is developed. Third, simulations and analysis (under different parameters, i.e., road conditions, prediction horizon, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. Fourth, the spacing between the vehicles in the platoon is designed in the objective function to ensure driving safety. The MPC problem is solved using a discrete numerical computation method: the continuation and generalized minimum residual method.

Original languageEnglish
Article number7390284
Pages (from-to)1894-1909
Number of pages16
JournalIEEE Transactions on Intelligent Transportation Systems
Volume17
Issue number7
DOIs
Publication statusPublished - Jul 2016

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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