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Optimization and control of battery-flywheel compound energy storage system during an electric vehicle braking

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  • Wang, Wei
  • Li, Yan
  • Shi, Man
  • Song, Yuling

Abstract

Combining the advantages of battery’s high specific energy and flywheel system’s high specific power, synthetically considering the effects of non-linear time-varying factors such as battery’s state of charge (SOC), open circuit voltage (OCV) and heat loss as well as flywheel’s rotating speed and its motor characteristic, the mathematical models of a battery-flywheel compound energy storage system are established. Taking the recovered braking energy of the system as an objective, an energy optimization method based on GA is proposed to obtain the optimal electric braking torque and current distribution factor under different working conditions, which realizes the current distribution between the battery and the flywheel as well as the allocation between the mechanical braking torque and the electric braking torque. Simultaneously, a double neural networks-based adaptive PI vector control method is proposed to regulate the rotating speed of the flywheel motor. Research results demonstrate that using the proposed methods the overall recovered energy increases by 1.17times and the maximum charging current of the battery decreases by 42.27% compared with a single battery system, and the stability and robustness of the flywheel system are significantly improved, which provides theoretical and technical references for making the energy management plan of electric vehicles.

Suggested Citation

  • Wang, Wei & Li, Yan & Shi, Man & Song, Yuling, 2021. "Optimization and control of battery-flywheel compound energy storage system during an electric vehicle braking," Energy, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:energy:v:226:y:2021:i:c:s0360544221006538
    DOI: 10.1016/j.energy.2021.120404
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    References listed on IDEAS

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    Cited by:

    1. Kai Xu & Youguang Guo & Gang Lei & Jianguo Zhu, 2023. "A Review of Flywheel Energy Storage System Technologies," Energies, MDPI, vol. 16(18), pages 1-32, September.
    2. Ouyang, Tiancheng & Qin, Peijia & Xie, Shutao & Tan, Xianlin & Pan, Mingming, 2023. "Flexible dispatch strategy of purchasing-selling electricity for coal-fired power plant based on compressed air energy storage," Energy, Elsevier, vol. 267(C).
    3. Zewen Meng & Tiezhu Zhang & Hongxin Zhang & Qinghai Zhao & Jian Yang, 2021. "Energy Management Strategy for an Electromechanical-Hydraulic Coupled Power Electric Vehicle Considering the Optimal Speed Threshold," Energies, MDPI, vol. 14(17), pages 1-12, August.
    4. Dong, Zhe & Li, Bowen & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2022. "Power-pressure coordinated control of modular high temperature gas-cooled reactors," Energy, Elsevier, vol. 252(C).
    5. Alexandre De Bernardinis & Richard Lallemand & Abdelfatah Kolli, 2023. "Highly Efficient Three-Phase Bi-Directional SiC DC–AC Inverter for Electric Vehicle Flywheel Emulator," Energies, MDPI, vol. 16(12), pages 1-15, June.

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