Guided Eco-Driving of Fuel Cell Hybrid Electric Vehicles via Model Predictive Control

Bo Liu, Chao Sun*, Xiaodong Wei, Da Wen, Changjiu Ning, Haoyu Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Eco-driving of fuel cell hybrid electric vehicles (FCHEVs) is a coupled problem of speed planning and energy management, and Model predictive control (MPC) is widely used in this field. To improve the global optimality of the traditional short-horizon MPC method, this paper proposes a guided MPC system for the eco-driving of FCHEVs. A hierarchical control framework is adopted where the long-term layer provides global vehicle speed and battery energy references under traffic light scenarios and the short-term layer realizes reference trajectory following while keeping a safe and comfortable distance from the preceding vehicle. The simulation result shows that the proposed guided MPC method can achieve better fuel economy than the traditional MPC method, especially when short-term vehicle speed and battery energy are both guided.

Original languageEnglish
Title of host publication2023 IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350344455
DOIs
Publication statusPublished - 2023
Event19th IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Milan, Italy
Duration: 24 Oct 202327 Oct 2023

Publication series

Name2023 IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Proceedings

Conference

Conference19th IEEE Vehicle Power and Propulsion Conference, VPPC 2023
Country/TerritoryItaly
CityMilan
Period24/10/2327/10/23

Keywords

  • eco-driving
  • energy management
  • fuel cell hybrid electric vehicle
  • guided model predictive control
  • speed planning

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