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A double variable control load sensing system for electric hydraulic excavator

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  • Lin, Tianliang
  • Lin, Yuanzheng
  • Ren, Haoling
  • Chen, Haibin
  • Li, Zhongshen
  • Chen, Qihuai

Abstract

Traditional electric excavator only uses the electric machine to replace the engine and simulate its original working mode, which will not give full play to the advantages of the electric drive technology and result in poor control performance as well as low energy efficiency. In this paper, a load sensing system based on displacement adaptive and variable speed control is proposed for electric excavator to extend the flow matching range of power train system and satisfy the flow demand under different load conditions. Furthermore, a novel control strategy based on the hierarchical differential pressure control is studied. Through the control strategy, the novel load sensing system can adjust the load sensing pressure difference in stages without mutual interference, so as to maintain the power train system operation in high efficiency area, and reduce the energy loss of the valve. To verify the feasibility of the system and control strategy, the simulations and experimental test are carried out. The results show that the system and control strategy can improve the control performance effectively. The energy consumption can be also decreased by 19%–70%.

Suggested Citation

  • Lin, Tianliang & Lin, Yuanzheng & Ren, Haoling & Chen, Haibin & Li, Zhongshen & Chen, Qihuai, 2021. "A double variable control load sensing system for electric hydraulic excavator," Energy, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:energy:v:223:y:2021:i:c:s0360544221002486
    DOI: 10.1016/j.energy.2021.119999
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    References listed on IDEAS

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    1. Chen, Qihuai & Lin, Tianliang & Ren, Haoling & Fu, Shengjie, 2019. "Novel potential energy regeneration systems for hybrid hydraulic excavators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 130-145.
    2. Jorge Leon-Quiroga & Brittany Newell & Mahesh Krishnamurthy & Andres Gonzalez-Mancera & Jose Garcia-Bravo, 2020. "Energy Efficiency Comparison of Hydraulic Accumulators and Ultracapacitors," Energies, MDPI, vol. 13(7), pages 1-23, April.
    3. Lin, Tianliang & Lin, Yuanzheng & Ren, Haoling & Chen, Haibin & Chen, Qihuai & Li, Zhongshen, 2020. "Development and key technologies of pure electric construction machinery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
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    Cited by:

    1. Do, Tri Cuong & Dinh, Truong Quang & Yu, Yingxiao & Ahn, Kyoung Kwan, 2023. "Innovative powertrain and advanced energy management strategy for hybrid hydraulic excavators," Energy, Elsevier, vol. 282(C).
    2. Wang, Feng & Lin, Zichang & Li, Jiaqi & Zhang, Chen & Xiao, Jin & Xu, Bing, 2024. "A free piston engine generator powered hybrid wheel loader with independent electric drive," Energy, Elsevier, vol. 286(C).
    3. Yong Nie & Jiajia Liu & Gang Liu & Litong Lyu & Jie Li & Zheng Chen, 2022. "Force Tracking Impedance Control of Hydraulic Series Elastic Actuators Interacting with Unknown Environment," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    4. Lin, Zichang & Lin, Zhenchuan & Wang, Feng & Xu, Bing, 2024. "A series electric hybrid wheel loader powertrain with independent electric load-sensing system," Energy, Elsevier, vol. 286(C).
    5. 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).

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