Advanced Energy Management Strategy Development for Plug-in Hybrid Electric Vehicles
Guoyuan Wu | University of California, Riverside
Plug-in hybrid vehicles (PHEVs) have great potential in reducing energy consumption and pollutant emissions, due to the use of electric batteries as another energy source. One of the critical considerations in PHEV development is the design of its energy management strategy, which determines how energy flows in a hybrid powertrain should be managed in response to a variety of system parameters. We propose to develop a generic framework for real-time energy management for PHEVs using connected vehicle technology. Different energy management strategies will be developed, evaluated, analyzed, and compared to existing commercial strategies. It is expected that using transportation system information obtained through being connected will result in greater fuel efficiency and better performance.
Sponsors: US DOT
- Qi, Xuewei, Guoyuan Wu, Kanok Boriboonsomsin, Matthew Barth, Jeffrey Gonder. “Data-Driven Reinforcement Learning-Based Real-Time Energy Management System for Plug-in Hybrid Electric Vehicles.” Transportation Research Record: Journal of the Transportation Research Board, vol. 2572, 2016, pp. 1-8.
- Boriboonsomsin, Kanok, Guoyuan Wu, and Matthew Barth. “Going the Extra Mile: Intelligent Energy Management of Plug-In Hybrid Electric Vehicles.” ACCESS Magazine, Spring 2016, pp. 2-7.
- Qi, Xuewei, Guoyuan Wu, Kanok Boriboonsomsin, and Matthew Barth. “An On-Line Energy Management Strategy for Plug-in Hybrid Electric Vehicles Using an Estimation Distribution Algorithm.” 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), 8-11 October 2014, Qingdao, China.