Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) for the HEVs with a Near-Optimal Equivalent Factor Considering Driving Conditions

Kyunghwan Choi, Jihye Byun, Sangmin Lee, In Gwun Jang

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

The equivalent consumption minimization strategy (ECMS) has been considered as a practical energy management strategy for the hybrid electric vehicles (HEVs) because it can be implemented in real time while providing satisfactory performance. However, it is still challenging to adjust an equivalent factor (EF) to its own optimal value in real time because the EF is fundamentally affected by the current driving condition. Although many adaptive ECMSs (A-ECMSs) have been developed to adjust the EF based on a charge-sustaining condition, they do not adequately respond to a change in the driving conditions. In this study, a novel ECMS for the HEVs is proposed to provide the near-optimal performance by considering actual driving conditions. First, the near-optimal condition for the EF is defined to consider a driving condition. Based on it, an iterative scheme is presented to numerically obtain the near-optimal EF. Then, the convergence analysis of the iterative scheme is conducted with practical considerations to implementing the proposed method into real-world applications. Simulation results show that the proposed strategy has better adaptability to changes in the driving conditions with a smaller loss of optimality than conventional A-ECMS which relies only on the charge-sustaining condition. The proposed strategy is also experimentally validated under real-world driving conditions.

Original languageEnglish
Pages (from-to)2538-2549
Number of pages12
JournalIEEE Transactions on Vehicular Technology
Volume71
Issue number3
DOIs
StatePublished - 1 Mar 2022

Keywords

  • Adaptive equivalent consumption minimization strategy (A-ECMS)
  • equivalent factor (EF)
  • hybrid electric vehicles (HEVs)
  • near-optimal condition

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