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Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control

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  • Wu, Jian
  • Wang, Xiangyu
  • Li, Liang
  • Qin, Cun'an
  • Du, Yongchang

Abstract

Regenerative braking is a key technology for hybrid electric vehicles (HEVs) to improve fuel economy, and it is a multi-objective control problem, which should ensure vehicle braking safety, recover more energy, and protect components from aging. As is known, battery is the most sensitive component in hybrid powertrain, so a large recover current can cause damage to the battery and reduce its life. However, the damage to is usually ignored in regenerative braking. Therefore, this paper proposed a hierarchical control strategy with battery aging consideration to solve the problem. In the up-level controller, the control targets are to recover more energy and minimize aging of the battery in general braking mode, and ensuring the vehicle braking safety in emergency braking mode at the same time. The low-level controller receives the commands of the up-level controller, and controls the pneumatic braking system and the electric motor (EM). The constraints of maximum EM torque and maximum battery charging power are set to protect the EM and the battery. Simulation tests are designed to indicate the effects of regenerative braking on battery aging and the control effectiveness of the proposed method, and controller-in-the-loop tests are carried out to verify the real-time calculation performance.

Suggested Citation

  • Wu, Jian & Wang, Xiangyu & Li, Liang & Qin, Cun'an & Du, Yongchang, 2018. "Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control," Energy, Elsevier, vol. 145(C), pages 301-312.
    • Handle: RePEc:eee:energy:v:145:y:2018:i:c:p:301-312
    DOI: 10.1016/j.energy.2017.12.138
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    10. Gao, Zhiming & LaClair, Tim & Ou, Shiqi & Huff, Shean & Wu, Guoyuan & Hao, Peng & Boriboonsomsin, Kanok & Barth, Matthew, 2019. "Evaluation of electric vehicle component performance over eco-driving cycles," Energy, Elsevier, vol. 172(C), pages 823-839.
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    13. Baodi Zhang & Sheng Guo & Xin Zhang & Qicheng Xue & Lan Teng, 2020. "Adaptive Smoothing Power Following Control Strategy Based on an Optimal Efficiency Map for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 13(8), pages 1-25, April.
    14. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2019. "Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain," Energy, Elsevier, vol. 187(C).
    15. Hanwu Liu & Yulong Lei & Yao Fu & Xingzhong Li, 2020. "An Optimal Slip Ratio-Based Revised Regenerative Braking Control Strategy of Range-Extended Electric Vehicle," Energies, MDPI, vol. 13(6), pages 1-21, March.
    16. Zhao, Mingjie & Shi, Junhui & Lin, Cheng, 2019. "Optimization of integrated energy management for a dual-motor coaxial coupling propulsion electric city bus," Applied Energy, Elsevier, vol. 243(C), pages 21-34.
    17. Nicu Bizon & Phatiphat Thounthong, 2020. "Energy Efficiency and Fuel Economy of a Fuel Cell/Renewable Energy Sources Hybrid Power System with the Load-Following Control of the Fueling Regulators," Mathematics, MDPI, vol. 8(2), pages 1-22, January.
    18. Li, Shuangqi & He, Hongwen & Zhao, Pengfei, 2021. "Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective," Energy, Elsevier, vol. 230(C).
    19. Ramesh Kumar Chidambaram & Dipankar Chatterjee & Barnali Barman & Partha Pratim Das & Dawid Taler & Jan Taler & Tomasz Sobota, 2023. "Effect of Regenerative Braking on Battery Life," Energies, MDPI, vol. 16(14), pages 1-24, July.
    20. Qiwei Lu & Bangbang He & Zhixuan Gao & Cheng Che & Xuteng Wei & Jihui Ma & Zhichun Zhang & Jiantao Luo, 2019. "An Optimized Regulation Scheme of Improving the Effective Utilization of the Regenerative Braking Energy of the Whole Railway Line," Energies, MDPI, vol. 12(21), pages 1-19, October.

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