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Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following

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  • Kaijiang Yu
  • Junqi Yang

Abstract

This paper presents a real-time optimal control approach for the energy management problem of hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) with slope information during car following. The new features of this study are as follows. First, the proposed method can optimize the engine operating points and the driving profile simultaneously. Second, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host vehicle. Third, using the HEV/PHEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Fourth, all of the vehicle operating modes engine charge, electric vehicle, motor assist and electric continuously variable transmission, and regenerative braking, can be realized using the proposed real-time optimal control approach. Computer simulation results are shown among the nonlinear real-time optimal control approach and the ADVISOR rule-based approach. The conclusion is that the nonlinear real-time optimal control approach is effective for the energy management problem of the HEV/PHEV system during car following.

Suggested Citation

  • Kaijiang Yu & Junqi Yang, 2014. "Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-14, June.
  • Handle: RePEc:hin:jnljam:879232
    DOI: 10.1155/2014/879232
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    Cited by:

    1. Xie, Shaobo & Hu, Xiaosong & Liu, Teng & Qi, Shanwei & Lang, Kun & Li, Huiling, 2019. "Predictive vehicle-following power management for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 166(C), pages 701-714.

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