Deeply Integrated Vehicle Dynamic and Powertrain Operation for Efficient Plug-in Hybrid Electric Bus

The emerging connected and automated vehicle (CAV) technology has opened the door for developing innovative applications and systems to improve vehicle energy efficiency. While most of the recent research has been focused on optimizing vehicle dynamic (VD) and powertrain (PT) operation in isolation, there exists untapped potential to further improve vehicle fuel efficiency through a co-optimization of VD&PT control. In this paper, the authors develop an eco-operation solution for a plug-in hybrid electric bus (PHEB) which seamlessly integrates state-of-the-art CAV applications with advanced powertrain optimization strategies, aiming at improving vehicle energy efficiency and reducing tailpipe emissions. The proposed eco-operation system have 6 components, including traffic/signal timing information acquirement, information integration, scenario identification, powertrain, trajectory planning and a MATLAB/Simulink model for validation and fine-tuning. A deeply integrated vehicle dynamic and powertrain control algorithm is proposed in the paper to optimize the energy-efficiency. Based on the key logic of powertrain control strategy of PHEB, the authors develop a simplified PHEB powertrain model, and put it into their graph based optimization model as the edge cost to derive the optimal speed profile, which is further fine-tuned in the Simulink model. The proposed mode is validated in multiple numerical tests under Eco-Approach and Departure, Eco-Stop and Launch and Eco-Cruise scenarios, and shows significant performance (above 20%) in energy-saving.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADC80 Standing Committee on Alternative Transportation Fuels and Technologies.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Hao, Peng
  • Boriboonsomsin, Kanok
  • Wu, Guoyuan
  • Gao, Zhiming
  • LaClair, Tim J
  • Barth, Matthew
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 6p

Subject/Index Terms

• TRT Terms: Algorithms; Autonomous vehicles; Connected vehicles; Ecodriving; Electric buses; Energy consumption; Plug-in hybrid vehicles; Power trains; Vehicle dynamics; Vehicle performance
• Subject Areas: Energy; Highways; Operations and Traffic Management; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01698116
• Record Type: Publication
• Report/Paper Numbers: 19-03195
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:51PM