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Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness

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  • Du, Jiuyu
  • Chen, Jingfu
  • Song, Ziyou
  • Gao, Mingming
  • Ouyang, Minggao

Abstract

Energy management strategy and battery capacity are the primary factors for the energy efficiency of range-extended electric buses (REEBs). To improve the energy efficiency of REEBs developed by Tsinghua University, an optimal design method of global optimization-based strategy is investigated. It is real-time and adaptive to variable traction battery capacities of series REEBs. For simulation, the physical model of REEB and key components are established. The optimal strategy is first extracted by the power split ratio (PSR) from REEB simulation result with dynamic program (DP) algorithm. The power distribution map is obtained by series simulations for variable battery capacity options. The control law for developing optimal strategy are achieved by cluster regression for power distribution data. To verify the effect of the proposed energy management strategy, characteristics of powertrain, energy efficiency, operating cost, and computing time are ultimately analyzed. Simulation results show that the energy efficiency of the global optimization-based strategy presented in this paper is similar to that of the DP strategy. Therefore, the overall energy efficiency can be significantly improved compared with that of the CDCS strategy, and operating costs can be substantially reduced. The feasibility of candidate control strategies is thereby assessed via the employment of variable parameters.

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  • Du, Jiuyu & Chen, Jingfu & Song, Ziyou & Gao, Mingming & Ouyang, Minggao, 2017. "Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness," Energy, Elsevier, vol. 121(C), pages 32-42.
    • Handle: RePEc:eee:energy:v:121:y:2017:i:c:p:32-42
    DOI: 10.1016/j.energy.2016.12.120
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    7. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
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    9. Lihe Xi & Xin Zhang & Chuanyang Sun & Zexing Wang & Xiaosen Hou & Jibao Zhang, 2017. "Intelligent Energy Management Control for Extended Range Electric Vehicles Based on Dynamic Programming and Neural Network," Energies, MDPI, vol. 10(11), pages 1-18, November.
    10. Loïc Joud & Rui Da Silva & Daniela Chrenko & Alan Kéromnès & Luis Le Moyne, 2020. "Smart Energy Management for Series Hybrid Electric Vehicles Based on Driver Habits Recognition and Prediction," Energies, MDPI, vol. 13(11), pages 1-17, June.
    11. Guo, Hongqiang & Sun, Qun & Wang, Chong & Wang, Qinpu & Lu, Silong, 2018. "A systematic design and optimization method of transmission system and power management for a plug-in hybrid electric vehicle," Energy, Elsevier, vol. 148(C), pages 1006-1017.
    12. Salman, Waleed & Qi, Lingfei & Zhu, Xin & Pan, Hongye & Zhang, Xingtian & Bano, Shehar & Zhang, Zutao & Yuan, Yanping, 2018. "A high-efficiency energy regenerative shock absorber using helical gears for powering low-wattage electrical device of electric vehicles," Energy, Elsevier, vol. 159(C), pages 361-372.
    13. Qiu, Chengqun & Wang, Guolin & Meng, Mingyu & Shen, Yujie, 2018. "A novel control strategy of regenerative braking system for electric vehicles under safety critical driving situations," Energy, Elsevier, vol. 149(C), pages 329-340.
    14. Liu, Teng & Wang, Bo & Yang, Chenglang, 2018. "Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning," Energy, Elsevier, vol. 160(C), pages 544-555.
    15. Chen, Zheng & Hu, Hengjie & Wu, Yitao & Zhang, Yuanjian & Li, Guang & Liu, Yonggang, 2020. "Stochastic model predictive control for energy management of power-split plug-in hybrid electric vehicles based on reinforcement learning," Energy, Elsevier, vol. 211(C).
    16. Song, Ziyou & Hou, Jun & Li, Xuefeng & Wu, Xiaogang & Hu, Xiaosong & Hofmann, Heath & Sun, Jing, 2020. "The sequential algorithm for combined state of charge and state of health estimation of lithium-ion battery based on active current injection," Energy, Elsevier, vol. 193(C).
    17. Xiaogang Wu & Dianyu Zheng & Tianze Wang & Jiuyu Du, 2019. "Torque Optimal Allocation Strategy of All-Wheel Drive Electric Vehicle Based on Difference of Efficiency Characteristics between Axis Motors," Energies, MDPI, vol. 12(6), pages 1-16, March.
    18. Wang, Yaxin & Lou, Diming & Xu, Ning & Fang, Liang & Tan, Piqiang, 2021. "Energy management and emission control for range extended electric vehicles," Energy, Elsevier, vol. 236(C).
    19. Dennis Dreier & Björn Rudin & Mark Howells, 2020. "Comparison of management strategies for the charging schedule and all-electric operation of a plug-in hybrid-electric bi-articulated bus fleet," Public Transport, Springer, vol. 12(2), pages 363-404, June.
    20. Piotr Wróblewski & Wojciech Drożdż & Wojciech Lewicki & Paweł Miązek, 2021. "Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas," Energies, MDPI, vol. 14(8), pages 1-24, April.
    21. Wu, Zhou & Ling, Rui & Tang, Ruoli, 2017. "Dynamic battery equalization with energy and time efficiency for electric vehicles," Energy, Elsevier, vol. 141(C), pages 937-948.
    22. García-Vázquez, Carlos A. & Llorens-Iborra, Francisco & Fernández-Ramírez, Luis M. & Sánchez-Sainz, Higinio & Jurado, Francisco, 2017. "Comparative study of dynamic wireless charging of electric vehicles in motorway, highway and urban stretches," Energy, Elsevier, vol. 137(C), pages 42-57.
    23. Paweł Krawczyk & Artur Kopczyński & Jakub Lasocki, 2022. "Modeling and Simulation of Extended-Range Electric Vehicle with Control Strategy to Assess Fuel Consumption and CO 2 Emission for the Expected Driving Range," Energies, MDPI, vol. 15(12), pages 1-41, June.

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