IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v285y2023ics0360544223029420.html
   My bibliography  Save this article

An energy active regulation management strategy based on driving mode recognition for electro-hydraulic hybrid vehicles

Author

Listed:
  • Li, Lin
  • Zhang, Tiezhu
  • Lu, Liqun
  • Zhang, Hongxin
  • Yang, Jian
  • Zhang, Zhen

Abstract

Electro-hydraulic hybrid vehicles(EHHVs) have shown astonishing advantages in energy utilization and recovery. However, the key factor affecting the energy efficiency lies in the selection and switching conditions of driving modes. This paper introduces the structure and working principle of an electro-hydraulic hybrid vehicle that combines planetary gear mechanism. And an energy active regulation management strategy combined with driving mode recognition(DMR) and fuzzy control strategy is proposed. Firstly, a driving mode feature parameter evaluation is presented based on the collected speed and the principal component analysis(PCA). Secondly, K-means clustering algorithm is applied to identify offline driving modes through the extraction of driving short cycles. Then, combined with the PCA results, a Learning Vector Quantization neural network(LVQ) is constructed to recognize driving modes. Simultaneously, a fuzzy controller is added to allocate torque ratio. Finally, the DMR and fuzzy controller are combined to realize the energy active regulation of motors and hydraulic pump/motor. Experimental results indicate that energy management strategies based on DMR and fuzzy controller can realize optimal switching between modes according to condition recognition. It improves the utilization rate of the accumulator, and reduces battery energy consumption compared with traditional strategies.

Suggested Citation

  • Li, Lin & Zhang, Tiezhu & Lu, Liqun & Zhang, Hongxin & Yang, Jian & Zhang, Zhen, 2023. "An energy active regulation management strategy based on driving mode recognition for electro-hydraulic hybrid vehicles," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223029420
    DOI: 10.1016/j.energy.2023.129548
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223029420
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129548?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Huanlong & Chen, Guanpeng & Li, Dafa & Wang, Jiawei & Zhou, Jianyi, 2021. "Energy active adjustment and bidirectional transfer management strategy of the electro-hydrostatic hydraulic hybrid powertrain for battery bus," Energy, Elsevier, vol. 230(C).
    2. Hong, Jichao & Wang, Zhenpo & Zhang, Tiezhu & Yin, Huaixian & Zhang, Hongxin & Huo, Wei & Zhang, Yi & Li, Yuanyuan, 2019. "Research on integration simulation and balance control of a novel load isolated pure electric driving system," Energy, Elsevier, vol. 189(C).
    3. Liu, Teng & Tan, Wenhao & Tang, Xiaolin & Zhang, Jinwei & Xing, Yang & Cao, Dongpu, 2021. "Driving conditions-driven energy management strategies for hybrid electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. Liu, Huanlong & Chen, Guanpeng & Xie, Chixin & Li, Dafa & Wang, Jiawei & Li, Shun, 2020. "Research on energy-saving characteristics of battery-powered electric-hydrostatic hydraulic hybrid rail vehicles," Energy, Elsevier, vol. 205(C).
    5. Hu, Jie & Liu, Di & Du, Changqing & Yan, Fuwu & Lv, Chen, 2020. "Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition," Energy, Elsevier, vol. 198(C).
    6. Lin Li & Tiezhu Zhang & Kaiwei Wu & Liqun Lu & Lianhua Lin & Haigang Xu, 2022. "Design and Research on Electro-Hydraulic Drive and Energy Recovery System of the Electric Excavator Boom," Energies, MDPI, vol. 15(13), pages 1-17, June.
    7. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    8. Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
    9. Hong, Jichao & Wang, Zhenpo & Yao, Yongtao, 2019. "Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    10. Zhang, Zhen & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Yang, Jian & Jia, Qingxiao, 2023. "Double deep Q-network guided energy management strategy of a novel electric-hydraulic hybrid electric vehicle," Energy, Elsevier, vol. 269(C).
    11. Tian, Xiang & Cai, Yingfeng & Sun, Xiaodong & Zhu, Zhen & Xu, Yiqiang, 2019. "An adaptive ECMS with driving style recognition for energy optimization of parallel hybrid electric buses," Energy, Elsevier, vol. 189(C).
    12. 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).
    13. Liu, Huanlong & Jiang, Yue & Li, Shun, 2019. "Design and downhill speed control of an electric-hydrostatic hydraulic hybrid powertrain in battery-powered rail vehicles," Energy, Elsevier, vol. 187(C).
    14. Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
    15. Li, Lin & Zhang, Tiezhu & Sun, Binbin & Wu, Kaiwei & Sun, Zehao & Zhang, Zhen & Lin, Lianhua & Xu, Haigang, 2023. "Research on electro-hydraulic ratios for a novel mechanical-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 270(C).
    16. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    17. Hong, Jichao & Wang, Zhenpo & Qu, Changhui & Zhou, Yangjie & Shan, Tongxin & Zhang, Jinghan & Hou, Yankai, 2022. "Investigation on overcharge-caused thermal runaway of lithium-ion batteries in real-world electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    18. Xiong, Rui & Sun, Wanzhou & Yu, Quanqing & Sun, Fengchun, 2020. "Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles," Applied Energy, Elsevier, vol. 279(C).
    19. Yu, Wei & Wang, Ruochen, 2019. "Development and performance evaluation of a comprehensive automotive energy recovery system with a refined energy management strategy," Energy, Elsevier, vol. 189(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Huanlong & Chen, Guanpeng & Li, Dafa & Wang, Jiawei & Zhou, Jianyi, 2021. "Energy active adjustment and bidirectional transfer management strategy of the electro-hydrostatic hydraulic hybrid powertrain for battery bus," Energy, Elsevier, vol. 230(C).
    2. Li, Lin & Zhang, Tiezhu & Sun, Binbin & Wu, Kaiwei & Sun, Zehao & Zhang, Zhen & Lin, Lianhua & Xu, Haigang, 2023. "Research on electro-hydraulic ratios for a novel mechanical-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 270(C).
    3. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    4. Zhang, Zhen & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Yang, Jian & Jia, Qingxiao, 2023. "Double deep Q-network guided energy management strategy of a novel electric-hydraulic hybrid electric vehicle," Energy, Elsevier, vol. 269(C).
    5. Yang, Jian & Liu, Bo & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin, 2023. "Multi-parameter controlled mechatronics-electro-hydraulic power coupling electric vehicle based on active energy regulation," Energy, Elsevier, vol. 263(PC).
    6. Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
    7. Liu, Huanlong & Wang, Xu & Tian, Hao & Gan, Shicheng & Zhou, Jianyi & Wang, Jiawei, 2024. "Energy-saving starting method of electric motor based on the battery-accumulator hybrid drive," Energy, Elsevier, vol. 286(C).
    8. Hong, Jichao & Zhang, Tiezhu & Zhang, Zhen & Zhang, Hongxin, 2023. "Investigation of energy management strategy for a novel electric-hydraulic hybrid vehicle: Self-adaptive electric-hydraulic ratio," Energy, Elsevier, vol. 278(C).
    9. Hu, Dong & Xie, Hui & Song, Kang & Zhang, Yuanyuan & Yan, Long, 2023. "An apprenticeship-reinforcement learning scheme based on expert demonstrations for energy management strategy of hybrid electric vehicles," Applied Energy, Elsevier, vol. 342(C).
    10. Du, Guodong & Zou, Yuan & Zhang, Xudong & Liu, Teng & Wu, Jinlong & He, Dingbo, 2020. "Deep reinforcement learning based energy management for a hybrid electric vehicle," Energy, Elsevier, vol. 201(C).
    11. Daniel Egan & Qilun Zhu & Robert Prucka, 2023. "A Review of Reinforcement Learning-Based Powertrain Controllers: Effects of Agent Selection for Mixed-Continuity Control and Reward Formulation," Energies, MDPI, vol. 16(8), pages 1-31, April.
    12. Wei, Changyin & Sun, Xiuxiu & Chen, Yong & Zang, Libin & Bai, Shujie, 2021. "Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle," Energy, Elsevier, vol. 230(C).
    13. Shanshan Guo & Zhiqiang Han & Jun Wei & Shenggang Guo & Liang Ma, 2022. "A Novel DC-AC Fast Charging Technology for Lithium-Ion Power Battery at Low-Temperatures," Sustainability, MDPI, vol. 14(11), pages 1-10, May.
    14. Li, Guozhen & Zhang, Zhenyu & Shi, Wankai & Li, Wenyong, 2023. "Energy management strategy and simulation analysis of a hybrid train based on a comprehensive efficiency optimization," Applied Energy, Elsevier, vol. 349(C).
    15. Ma, Bin & Guo, Xing & Li, Penghui, 2023. "Adaptive energy management strategy based on a model predictive control with real-time tuning weight for hybrid energy storage system," Energy, Elsevier, vol. 283(C).
    16. 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.
    17. Guo, Xiaokai & Yan, Xianguo & Chen, Zhi & Meng, Zhiyu, 2022. "Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network," Energy, Elsevier, vol. 260(C).
    18. Guo, Shanshan & Yang, Ruixin & Shen, Weixiang & Liu, Yongsheng & Guo, Shenggang, 2022. "DC-AC hybrid rapid heating method for lithium-ion batteries at high state of charge operated from low temperatures," Energy, Elsevier, vol. 238(PB).
    19. Huang, Ying & Wang, Shilong & Li, Ke & Fan, Zhuwei & Xie, Haiming & Jiang, Fachao, 2023. "Multi-parameter adaptive online energy management strategy for concrete truck mixers with a novel hybrid powertrain considering vehicle mass," Energy, Elsevier, vol. 277(C).
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223029420. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.