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Mode shift map design and integrated energy management control of a multi-mode hybrid electric vehicle

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  • Zhuang, Weichao
  • Zhang, Xiaowu
  • Li, Daofei
  • Wang, Liangmo
  • Yin, Guodong

Abstract

Multi-mode hybrid electric vehicles (HEVs) have become popular in recent years because of their high efficiency and excellent overall performance. However, the introduction of multiple operating modes has led to some issues, e.g., mode shift problems, which are not observed in conventional HEVs with a single mode. Similar to a gear shift map in conventional vehicles, the mode shift map in multi-mode HEVs needs to be properly designed. In this study, the energy management algorithm of a multi-mode HEV is optimized using dynamic programming (DP) considering the mode shift frequency and energy losses. A mode shift map is then extracted from the operating points of the DP results using the support vector machine (SVM). By combining the derived mode shift map and the equivalent consumption minimization strategy (ECMS), a real-time control strategy is proposed for the online energy management of the multi-mode HEV. The results of a case study show the effectiveness of the proposed mode shift map and energy management strategy.

Suggested Citation

  • Zhuang, Weichao & Zhang, Xiaowu & Li, Daofei & Wang, Liangmo & Yin, Guodong, 2017. "Mode shift map design and integrated energy management control of a multi-mode hybrid electric vehicle," Applied Energy, Elsevier, vol. 204(C), pages 476-488.
    • Handle: RePEc:eee:appene:v:204:y:2017:i:c:p:476-488
    DOI: 10.1016/j.apenergy.2017.07.059
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    14. Zhao, Mingjie & Shi, Junhui & Lin, Cheng, 2019. "Optimization of integrated energy management for a dual-motor coaxial coupling propulsion electric city bus," Applied Energy, Elsevier, vol. 243(C), pages 21-34.
    15. Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2021. "Real-Time Approximate Equivalent Consumption Minimization Strategy Based on the Single-Shaft Parallel Hybrid Powertrain," Energies, MDPI, vol. 14(23), pages 1-22, November.
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