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Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results

Author

Listed:
  • Dapai Shi

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Sciences, Xiangyang 441053, China)

  • Junjie Guo

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Sciences, Xiangyang 441053, China)

  • Kangjie Liu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Qingling Cai

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Sciences, Xiangyang 441053, China)

  • Zhenghong Wang

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Sciences, Xiangyang 441053, China)

  • Xudong Qu

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Sciences, Xiangyang 441053, China)

Abstract

Plug-in hybrid electric vehicles (PHEVs) have gradually become an important member of new energy vehicles because of the advantages of both electric and hybrid electric vehicles. A fast and effective energy management strategy can significantly improve the fuel-saving performance of vehicles. By observing the dynamic programming (DP) simulation results, it was found that the vehicle is in the charge-depleting mode, the state of charge (SOC) drops to the minimum at the end of the journey, and the SOC decreases linearly with the mileage. As such, this study proposed an improved rule-based (IRB) strategy enlightened by the DP strategy, which is different from previous rule-based (RB) strategies. Introducing the reference SOC curve and SOC adaptive adjustment, the IRB strategy ensures that the SOC decreases linearly with the driving distance, and the SOC drops to the minimum at the end of the journal, similar to the result of the DP strategy. The fuel economy of PHEV in the RB and DP energy management strategies can be considered as their worst-case and best-case scenarios, respectively. The simulation results show that the fuel consumption of the IRB strategy under the China Light-duty Vehicle Test Cycle is 3.16 L/100 km, which is 7.87% less than that of the RB strategy (3.43 L/100 km), and has reached 44.41% of the fuel-saving effect of the DP strategy (2.84 L/100 km).

Suggested Citation

  • Dapai Shi & Junjie Guo & Kangjie Liu & Qingling Cai & Zhenghong Wang & Xudong Qu, 2023. "Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results," Sustainability, MDPI, vol. 15(13), pages 1-13, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10472-:d:1185923
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    References listed on IDEAS

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