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Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system

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  • Du, Jiuyu
  • Zhang, Xiaobin
  • Wang, Tianze
  • Song, Ziyou
  • Yang, Xueqing
  • Wang, Hewu
  • Ouyang, Minggao
  • Wu, Xiaogang

Abstract

The potential of reducing fuel consumption, harmful emission and cost benefit for plug-in electric hybrid buses depended largely on the power management strategy for specific hybrid electric powertrain configuration, especially for those with compound energy storage system. Hybrid energy storage system in this research comprise high energy lithium iron phosphate batteries and super-capacitors, therefore, the key of improving the life cycle cost-benefit is to extend the cycle life for lithium battery. This paper presents an optimal control strategy for the serial-parallel plug-in hybrid electric buses based on the lithium battery degradation model to minimize life cycle operating cost. To derive the globally optimal strategy, an algorithm based on two-dimensional Pontryagin's minimum principle is proposed. With the optimal strategy, the battery degradation is significantly reduced, and the total cost is reduced by 21.7% compared with a plug-in hybrid electric bus with single type energy storage. Further embodies the advantages of hybrid energy storage systems and optimization algorithms.

Suggested Citation

  • Du, Jiuyu & Zhang, Xiaobin & Wang, Tianze & Song, Ziyou & Yang, Xueqing & Wang, Hewu & Ouyang, Minggao & Wu, Xiaogang, 2018. "Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system," Energy, Elsevier, vol. 165(PA), pages 153-163.
  • Handle: RePEc:eee:energy:v:165:y:2018:i:pa:p:153-163
    DOI: 10.1016/j.energy.2018.09.084
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    7. Huang, Jiangfan & An, Qing & Zhou, Mingyu & Tang, Ruoli & Dong, Zhengcheng & Lai, Jingang & Li, Xin & Yang, Xiangguo, 2024. "A self-adaptive joint optimization framework for marine hybrid energy storage system design considering load fluctuation characteristics," Applied Energy, Elsevier, vol. 361(C).
    8. Zhou, Yu & Wang, Hua & Wang, Yun & Yu, Bin & Tang, Tianpei, 2024. "Charging facility planning and scheduling problems for battery electric bus systems: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    9. López-Ibarra, Jon Ander & Gaztañaga, Haizea & Saez-de-Ibarra, Andoni & Camblong, Haritza, 2020. "Plug-in hybrid electric buses total cost of ownership optimization at fleet level based on battery aging," Applied Energy, Elsevier, vol. 280(C).
    10. Tobias Frambach & Ralf Kleisch & Ralf Liedtke & Jochen Schwarzer & Egbert Figgemeier, 2022. "Environmental Impact Assessment and Classification of 48 V Plug-in Hybrids with Real-Driving Use Case Simulations," Energies, MDPI, vol. 15(7), pages 1-21, March.
    11. Hu, Jiayi & Li, Jianqiu & Hu, Zunyan & Xu, Liangfei & Ouyang, Minggao, 2021. "Power distribution strategy of a dual-engine system for heavy-duty hybrid electric vehicles using dynamic programming," Energy, Elsevier, vol. 215(PA).
    12. Chen, Hui & Zhang, Zehui & Guan, Cong & Gao, Haibo, 2020. "Optimization of sizing and frequency control in battery/supercapacitor hybrid energy storage system for fuel cell ship," Energy, Elsevier, vol. 197(C).
    13. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Development of energy management system based on a rule-based power distribution strategy for hybrid power sources," Energy, Elsevier, vol. 175(C), pages 1055-1066.
    14. Zeng, Ziling & Wang, Shuaian & Qu, Xiaobo, 2022. "On the role of battery degradation in en-route charge scheduling for an electric bus system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    15. Yongquan Sun & Saurabh Saxena & Michael Pecht, 2018. "Derating Guidelines for Lithium-Ion Batteries," Energies, MDPI, vol. 11(12), pages 1-19, November.
    16. Ying Yang & Zhenpo Wang & Shuo Wang & Ni Lin, 2022. "An Investigation of Opportunity Charging with Hybrid Energy Storage System on Electric Bus with Two-Speed Transmission," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
    17. Gao, Xinjia & Wu, Xiaogang & Xia, Yinlong & Li, Yalun, 2024. "Life extension of a multi-unit energy storage system by optimizing the power distribution based on the degradation ratio," Energy, Elsevier, vol. 286(C).
    18. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Ruan, Haijun & Jiang, Zhihao, 2021. "Adaptive energy management of a battery-supercapacitor energy storage system for electric vehicles based on flexible perception and neural network fitting," Applied Energy, Elsevier, vol. 292(C).
    19. Manzolli, Jônatas Augusto & Trovão, João Pedro & Antunes, Carlos Henggeler, 2022. "A review of electric bus vehicles research topics – Methods and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    20. Bouguenna, Ibrahim Farouk & Azaiz, Ahmed & Tahour, Ahmed & Larbaoui, Ahmed, 2019. "Robust neuro-fuzzy sliding mode control with extended state observer for an electric drive system," Energy, Elsevier, vol. 169(C), pages 1054-1063.

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