Model predictive control power management strategies for HEVs: A review

Yanjun Huang, Hong Wang*, Amir Khajepour, Hongwen He, Jie Ji

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

462 Citations (Scopus)

Abstract

This paper presents a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time. Research on MPC-based power management systems for HEVs has intensified recently due to its many inherent merits. The categories of the existing PMSs are identified from the latest literature, and a brief study of each type is conducted. Then, the MPC approach is introduced and its advantages are discussed. Based on the acquisition method of driver behavior used for state prediction and the dynamic model used, the MPC is classified and elaborated. Factors that affect the performance of the MPC are put forward, including prediction accuracy, design parameters, and solvers. Finally, several important issues in the application of MPC-based power management strategies and latest developing trends are discussed. This paper not only provides a comprehensive analysis of MPC-based power management strategies for HEVs but also puts forward the future and emphasis of future study, which will promote the development of energy management controller with high performance and low cost for HEVs.

Original languageEnglish
Pages (from-to)91-106
Number of pages16
JournalJournal of Power Sources
Volume341
DOIs
Publication statusPublished - 15 Feb 2017

Keywords

  • Hybrid electric vehicles
  • Model predictive control
  • Power management strategy

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