IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v263y2023ipcs0360544222027633.html
   My bibliography  Save this article

Multi-parameter controlled mechatronics-electro-hydraulic power coupling electric vehicle based on active energy regulation

Author

Listed:
  • Yang, Jian
  • Liu, Bo
  • Zhang, Tiezhu
  • Hong, Jichao
  • Zhang, Hongxin

Abstract

To enhance the hydraulic energy utilization and torque output stability, a novel mechatronics-electro-hydraulic power coupling electric vehicle (MEH-PCEV) is proposed, integrating a hydraulic pump/motor and a motor into a single device for mutual energy conversion. For MEH-PCEVs equipped with multiple energy sources, a cluster analysis method is used to classify the actual road test dataset and provide guiding ideas for designing rule-based energy management strategies (RB-EMS). Simultaneously, for the output torque anomaly phenomenon in RB-EMS, an inverse thinking fuzzy logic optimization energy management strategy (FLO-EMS) conside ring multi-parameter objectives as input is used to adjust the electromagnetic torque in real-time and reasonably allocate the energy flow. The simulation results demonstrate that the electric and total torque output are more stable. The electric peak torque is relieved, with a corresponding increase in the percentage of electrical energy recovery. With the equal power demand, the overall efficiency of the motor working point is substantially improved, and the energy consumption rate is decreased by 24.42%. Under the active regulation of FLO-EMS, hydraulic energy is more reasonably utilized to meet the vehicle demand power while avoiding energy dissipation and waste. Moreover, this work is expected to reference the development and engineering applications of electro-hydraulic coupling systems.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:263:y:2023:i:pc:s0360544222027633
    DOI: 10.1016/j.energy.2022.125877
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222027633
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.125877?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. Yu, Xiao & Lin, Cheng & Zhao, Mingjie & Yi, Jiang & Su, Yue & Liu, Huimin, 2022. "Optimal energy management strategy of a novel hybrid dual-motor transmission system for electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    2. 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).
    3. Ruan, Jiageng & Walker, Paul D. & Watterson, Peter A. & Zhang, Nong, 2016. "The dynamic performance and economic benefit of a blended braking system in a multi-speed battery electric vehicle," Applied Energy, Elsevier, vol. 183(C), pages 1240-1258.
    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. Hao, Yunxiao & Quan, Long & Cheng, Hang & Xia, Lianpeng & Ge, Lei & Zhao, Bin, 2018. "Potential energy directly conversion and utilization methods used for heavy duty lifting machinery," Energy, Elsevier, vol. 155(C), pages 242-251.
    6. Jian Yang & Tiezhu Zhang & Hongxin Zhang & Jichao Hong & Zewen Meng, 2020. "Research on the Starting Acceleration Characteristics of a New Mechanical–Electric–Hydraulic Power Coupling Electric Vehicle," Energies, MDPI, vol. 13(23), pages 1-20, November.
    7. He, Hongwen & Wang, Chen & Jia, Hui & Cui, Xing, 2020. "An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle," Applied Energy, Elsevier, vol. 259(C).
    8. Hu, Jianjun & Mei, Bo & Peng, Hang & Guo, Zihan, 2019. "Discretely variable speed ratio control strategy for continuously variable transmission system considering hydraulic energy loss," Energy, Elsevier, vol. 180(C), pages 714-727.
    9. Yafei Xin & Tiezhu Zhang & Hongxin Zhang & Qinghai Zhao & Jian Zheng & Congcong Wang, 2019. "Fuzzy Logic Optimization of Composite Brake Control Strategy for Load-Isolated Electric Bus," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-14, October.
    10. 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).
    11. Qinghai Zhao & Hongxin Zhang & Yafei Xin, 2021. "Research on Control Strategy of Hydraulic Regenerative Braking of Electrohydraulic Hybrid Electric Vehicles," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, February.
    12. Enang, Wisdom & Bannister, Chris, 2017. "Modelling and control of hybrid electric vehicles (A comprehensive review)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1210-1239.
    13. Li, Yanhua & Wang, Xilian & Fang, Xinyu & Liu, Yuenan & Zhao, Pengyu & Cui, Ruizhen, 2022. "Modeling and control strategy analysis of a hydraulic energy-storage wave energy conversion system," Renewable Energy, Elsevier, vol. 182(C), pages 969-981.
    14. 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.
    15. Yu, Xiao & Lin, Cheng & Xie, Peng & Liang, Sheng, 2022. "A novel real-time energy management strategy based on Monte Carlo Tree Search for coupled powertrain platform via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 256(C).
    16. Xu, Beibei & Chen, Diyi & Venkateshkumar, M. & Xiao, Yu & Yue, Yan & Xing, Yanqiu & Li, Peiquan, 2019. "Modeling a pumped storage hydropower integrated to a hybrid power system with solar-wind power and its stability analysis," Applied Energy, Elsevier, vol. 248(C), pages 446-462.
    17. Shahryar Sorooshian, 2013. "Fuzzy Approach to Statistical Control Charts," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-6, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rekha Guchhait & Biswajit Sarkar, 2023. "Increasing Growth of Renewable Energy: A State of Art," Energies, MDPI, vol. 16(6), pages 1-29, March.
    2. Oleksandr Ivchenko & Vladyslav Andrusiak & Vladyslav Kondus & Ivan Pavlenko & Serhii Petrenko & Andżelika Krupińska & Sylwia Włodarczak & Magdalena Matuszak & Marek Ochowiak, 2023. "Energy Efficiency Indicator of Pumping Equipment Usage," Energies, MDPI, vol. 16(15), pages 1-13, August.
    3. Hu, Jianjun & Guo, Qi & Sun, Zhicheng & Yang, Dianzhao, 2023. "Study on low-frequency torsional vibration suppression of integrated electric drive system considering nonlinear factors," Energy, Elsevier, vol. 284(C).
    4. Jin, Rui & Li, Lei & Liang, Xiaoling & Zou, Xiang & Yang, Zeyuan & Ge, Shuzhi Sam & Huang, Haihong, 2024. "Energy-efficient design of the powertrain for mechanical-electro-hydraulic equipment via configuring multidimensional controllable variables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).

    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. 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).
    2. 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).
    3. 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).
    4. Jin, Rui & Li, Lei & Liang, Xiaoling & Zou, Xiang & Yang, Zeyuan & Ge, Shuzhi Sam & Huang, Haihong, 2024. "Energy-efficient design of the powertrain for mechanical-electro-hydraulic equipment via configuring multidimensional controllable variables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    5. Yang, Chao & Sun, Tonglin & Wang, Weida & Li, Ying & Zhang, Yuhang & Zha, Mingjun, 2024. "Regenerative braking system development and perspectives for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
    6. 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.
    7. Cong Geng & Dawen Ning & Linfu Guo & Qicheng Xue & Shujian Mei, 2021. "Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle," Energies, MDPI, vol. 14(8), pages 1-19, April.
    8. 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).
    9. Yu, Xiao & Lin, Cheng & Tian, Yu & Zhao, Mingjie & Liu, Huimin & Xie, Peng & Zhang, JunZhi, 2023. "Real-time and hierarchical energy management-control framework for electric vehicles with dual-motor powertrain system," Energy, Elsevier, vol. 272(C).
    10. 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.
    11. Liu, Huimin & Lin, Cheng & Yu, Xiao & Tao, Zhenyi & Xu, Jiaqi, 2024. "Variable horizon multivariate driving pattern recognition framework based on vehicle-road two-dimensional information for electric vehicle," Applied Energy, Elsevier, vol. 365(C).
    12. Yu, Xiao & Lin, Cheng & Xie, Peng & Liang, Sheng, 2022. "A novel real-time energy management strategy based on Monte Carlo Tree Search for coupled powertrain platform via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 256(C).
    13. Wang, Bohan & Deng, Ziwei & Zhang, Baocheng, 2022. "Simulation of a novel wind–wave hybrid power generation system with hydraulic transmission," Energy, Elsevier, vol. 238(PB).
    14. Jian Yang & Tiezhu Zhang & Hongxin Zhang & Jichao Hong & Zewen Meng, 2020. "Research on the Starting Acceleration Characteristics of a New Mechanical–Electric–Hydraulic Power Coupling Electric Vehicle," Energies, MDPI, vol. 13(23), pages 1-20, November.
    15. Tan, Lisha & He, Xiangyu & Xiao, Guangxin & Jiang, Mengjun & Yuan, Yulin, 2022. "Design and energy analysis of novel hydraulic regenerative potential energy systems," Energy, Elsevier, vol. 249(C).
    16. Zhou, Xiaochuan & Wu, Gang & Wang, Chunyan & Zhang, Ruijun & Shi, Shuaipeng & Zhao, Wanzhong, 2024. "Cooperative optimization of energy recovery and braking feel based on vehicle speed prediction under downshifting conditions," Energy, Elsevier, vol. 301(C).
    17. He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
    18. Cui, Binghan & Wang, Han & Li, Renlong & Xiang, Lizhi & Zhao, Huaian & Xiao, Rang & Li, Sai & Liu, Zheng & Yin, Geping & Cheng, Xinqun & Ma, Yulin & Huo, Hua & Zuo, Pengjian & Lu, Taolin & Xie, Jingyi, 2024. "Ultra-early prediction of lithium-ion battery performance using mechanism and data-driven fusion model," Applied Energy, Elsevier, vol. 353(PA).
    19. Wang, Xin & Luo, Yingbing & Qin, Bin & Guo, Lingzhong, 2022. "Power dynamic allocation strategy for urban rail hybrid energy storage system based on iterative learning control," Energy, Elsevier, vol. 245(C).
    20. Ma, Zhikai & Huo, Qian & Wang, Wei & Zhang, Tao, 2023. "Voltage-temperature aware thermal runaway alarming framework for electric vehicles via deep learning with attention mechanism in time-frequency domain," Energy, Elsevier, vol. 278(C).

    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:263:y:2023:i:pc:s0360544222027633. 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.