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Improved energy management strategy for plug-in hybrid electric buses based on Pontryagin's minimum principle plus snack optimization

Author

Listed:
  • Sun, Xiaodong
  • Xu, Zhaojian
  • Cai, Yingfeng
  • Chen, Long
  • Tian, Xiang
  • Jin, Zhijia
  • Xue, Mingzhou

Abstract

Plug-in hybrid electric buses (PHEBs) serve as important environmentally-friendly public transportation vehicles. An adaptive instantaneous optimization energy management strategy based on the SO-PMP approach is proposed on the P2 configuration. This strategy takes into account the power interruption during mode switching in hybrid powertrain systems, and a three-stage clutch mechanical model is constructed. The paper initially introduces the application of Pontryagin's Minimum Principle (PMP) in PHEBs. In addition, a fuzzy logic controller is proposed to design the motor torque compensation coefficient by taking the variance between expected torque and real torque and pedal opening as input. Finally, snake optimization (SO) is used to solve the costate in PMP to achieve the best fuel consumption (FC). The strategy utilizes the fast response characteristic of the motor to compensate for the delay characteristic of the engine, and its effectiveness is verified through both simulation and hardware-in-the-loop (HIL) platform. Compared to globally optimal algorithms, the finding demonstrates that the fuel economy of the employed method yields a mere increase of 3.4 %, but it greatly increases the possibility of application in real vehicles.

Suggested Citation

  • Sun, Xiaodong & Xu, Zhaojian & Cai, Yingfeng & Chen, Long & Tian, Xiang & Jin, Zhijia & Xue, Mingzhou, 2025. "Improved energy management strategy for plug-in hybrid electric buses based on Pontryagin's minimum principle plus snack optimization," Energy, Elsevier, vol. 320(C).
    • Handle: RePEc:eee:energy:v:320:y:2025:i:c:s0360544225010448
    DOI: 10.1016/j.energy.2025.135402
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    References listed on IDEAS

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    1. Sun, Chao & Sun, Fengchun & He, Hongwen, 2017. "Investigating adaptive-ECMS with velocity forecast ability for hybrid electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1644-1653.
    2. Hannan, M.A. & Azidin, F.A. & Mohamed, A., 2014. "Hybrid electric vehicles and their challenges: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 135-150.
    3. Zhen Zhu & Lingxin Zeng & Long Chen & Rong Zou & Yingfeng Cai, 2022. "Fuzzy Adaptive Energy Management Strategy for a Hybrid Agricultural Tractor Equipped with HMCVT," Agriculture, MDPI, vol. 12(12), pages 1-21, November.
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    5. Sun, Fengchun & Xiong, Rui & He, Hongwen, 2016. "A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique," Applied Energy, Elsevier, vol. 162(C), pages 1399-1409.
    6. Yao Yu & Shuaihua Hao & Songbao Guo & Zhong Tang & Shuren Chen, 2022. "Motor Torque Distribution Strategy for Different Tillage Modes of Agricultural Electric Tractors," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
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