IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i8p1118-d106592.html
   My bibliography  Save this article

Investigation on a Power Coupling Steering System for Dual-Motor Drive Tracked Vehicles Based on Speed Control

Author

Listed:
  • Li Zhai

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Co-Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Hong Huang

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Co-Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Steven Kavuma

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Co-Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

Abstract

Double-motor drive tracked vehicles (2MDTV) are widely used in the tracked vehicle industry due to the development of electric vehicle drive systems. The aim of this paper is to solve the problem of insufficient propulsion motor torque in low-speed, small-radius steering and insufficient power in high-speed large-radius steering. In order to do this a new type of steering system with a coupling device is designed and a closed-loop control strategy based on speed is adopted to improve the lateral stability of the vehicle. The work done entails modeling and simulating the 2MDTV and the proposed control strategy in RecurDyn and Matlab/Simulink. The simulation results show that the 2MDTV with the coupling device outputs more torque and power in both steering cases compared to the 2MDTV without the coupling device, and the steering stability of the vehicle is improved by using the strategy based on speed.

Suggested Citation

  • Li Zhai & Hong Huang & Steven Kavuma, 2017. "Investigation on a Power Coupling Steering System for Dual-Motor Drive Tracked Vehicles Based on Speed Control," Energies, MDPI, vol. 10(8), pages 1-17, August.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1118-:d:106592
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/8/1118/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/8/1118/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Hong & Huang, Yanjun & Khajepour, Amir & He, Hongwen & Cao, Dongpu, 2017. "A novel energy management for hybrid off-road vehicles without future driving cycles as a priori," Energy, Elsevier, vol. 133(C), pages 929-940.
    2. Wang, Hong & Huang, Yanjun & Khajepour, Amir & Song, Qiang, 2016. "Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle," Applied Energy, Elsevier, vol. 182(C), pages 105-114.
    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. Li Zhai & Rufei Hou & Tianmin Sun & Steven Kavuma, 2018. "Continuous Steering Stability Control Based on an Energy-Saving Torque Distribution Algorithm for a Four in-Wheel-Motor Independent-Drive Electric Vehicle," Energies, MDPI, vol. 11(2), pages 1-19, February.
    2. Hong Huang & Li Zhai & Zeda Wang, 2018. "A Power Coupling System for Electric Tracked Vehicles during High-Speed Steering with Optimization-Based Torque Distribution Control," Energies, MDPI, vol. 11(6), pages 1-17, June.

    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. 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.
    2. Wu, Jingda & He, Hongwen & Peng, Jiankun & Li, Yuecheng & Li, Zhanjiang, 2018. "Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus," Applied Energy, Elsevier, vol. 222(C), pages 799-811.
    3. 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).
    4. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    5. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    6. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    7. Wei Zhang & Jixin Wang & Shaofeng Du & Hongfeng Ma & Wenjun Zhao & Haojie Li, 2019. "Energy Management Strategies for Hybrid Construction Machinery: Evolution, Classification, Comparison and Future Trends," Energies, MDPI, vol. 12(10), pages 1-26, May.
    8. Zhang, Wei & Wang, Jixin & Liu, Yong & Gao, Guangzong & Liang, Siwen & Ma, Hongfeng, 2020. "Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery," Applied Energy, Elsevier, vol. 275(C).
    9. Xie, Shaobo & Lang, Kun & Qi, Shanwei, 2020. "Aerodynamic-aware coordinated control of following speed and power distribution for hybrid electric trucks," Energy, Elsevier, vol. 209(C).
    10. Wang, Yue & Zeng, Xiaohua & Song, Dafeng & Yang, Nannan, 2019. "Optimal rule design methodology for energy management strategy of a power-split hybrid electric bus," Energy, Elsevier, vol. 185(C), pages 1086-1099.
    11. Tri Cuong Do & Hoai Vu Anh Truong & Hoang Vu Dao & Cong Minh Ho & Xuan Dinh To & Tri Dung Dang & Kyoung Kwan Ahn, 2019. "Energy Management Strategy of a PEM Fuel Cell Excavator with a Supercapacitor/Battery Hybrid Power Source," Energies, MDPI, vol. 12(22), pages 1-24, November.
    12. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    13. Yang, Chao & Li, Liang & You, Sixiong & Yan, Bingjie & Du, Xian, 2017. "Cloud computing-based energy optimization control framework for plug-in hybrid electric bus," Energy, Elsevier, vol. 125(C), pages 11-26.
    14. Wang, Yue & Zeng, Xiaohua & Song, Dafeng, 2020. "Hierarchical optimal intelligent energy management strategy for a power-split hybrid electric bus based on driving information," Energy, Elsevier, vol. 199(C).
    15. Kong, Yan & Xu, Nan & Liu, Qiao & Sui, Yan & Jia, Yifan, 2024. "Variable horizon-based predictive energy management strategy for plug-in hybrid electric vehicles and determination of a suitable predictive horizon," Energy, Elsevier, vol. 294(C).
    16. Chen, Ruihu & Yang, Chao & Ma, Yue & Wang, Weida & Wang, Muyao & Du, Xuelong, 2022. "Online learning predictive power coordinated control strategy for off-road hybrid electric vehicles considering the dynamic response of engine generator set," Applied Energy, Elsevier, vol. 323(C).
    17. Halder, Pobitra & Babaie, Meisam & Salek, Farhad & Shah, Kalpit & Stevanovic, Svetlana & Bodisco, Timothy A. & Zare, Ali, 2024. "Performance, emissions and economic analyses of hydrogen fuel cell vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    18. Gong, Jun & Zhang, Daqing & Guo, yong & Liu, Changsheng & Zhao, Yuming & Hu, Peng & Quan, weicai, 2019. "Power control strategy and performance evaluation of a novel electro-hydraulic energy-saving system," Applied Energy, Elsevier, vol. 233, pages 724-734.
    19. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    20. Li, Xiaolong & Xie, Changjun & Quan, Shuhai & Huang, Liang & Fang, Wei, 2018. "Energy management strategy of thermoelectric generation for localized air conditioners in commercial vehicles based on 48 V electrical system," Applied Energy, Elsevier, vol. 231(C), pages 887-900.

    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:gam:jeners:v:10:y:2017:i:8:p:1118-:d:106592. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.