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Innovative powertrain and advanced energy management strategy for hybrid hydraulic excavators

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  • Do, Tri Cuong
  • Dinh, Truong Quang
  • Yu, Yingxiao
  • Ahn, Kyoung Kwan

Abstract

This paper presents an innovative powertrain managed by an advanced energy management strategy for hybrid hydraulic excavators to improve the overall energy efficiency. Here, a main pump is driven via a planetary gear by an engine and an electric motor/generator. A double clutch is integrated to adjust torque and speed of engine according to efficiency map enabling higher working efficiency. Potential energy of the boom cylinder can be converted and stored in a battery through an energy regeneration system. The advanced energy management strategy is designed by utilising extremum seeking and fuzzy techniques to optimally distribute power requirement. A fuzzy logic system is designed based on consideration of battery performance and aging to adjust a penalty function subsequently improving the overall system performance while prolonging the component lifetime. Simulations and real-time experiments have been carried out to evaluate the effectiveness of the proposed powertrain managed by the advanced energy management strategy.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023459
    DOI: 10.1016/j.energy.2023.128951
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    References listed on IDEAS

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    1. 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).
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    Citations

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    Cited by:

    1. Van-Hien Nguyen & Tri Cuong Do & Kyoung-Kwan Ahn, 2024. "Implementing PSO-LSTM-GRU Hybrid Neural Networks for Enhanced Control and Energy Efficiency of Excavator Cylinder Displacement," Mathematics, MDPI, vol. 12(20), pages 1-21, October.
    2. Thanh Ha Nguyen & Tri Cuong Do & Van Du Phan & Kyoung Kwan Ahn, 2023. "Working Performance Improvement of a Novel Independent Metering Valve System by Using a Neural Network-Fractional Order-Proportional-Integral-Derivative Controller," Mathematics, MDPI, vol. 11(23), pages 1-21, November.
    3. Nguyen, Van Hien & Do, Tri Cuong & Dang, Tri Dung & Ahn, Kyoung Kwan, 2025. "Improving the efficiency of hybrid hydraulic excavators with a novel powertrain and energy management system," Energy, Elsevier, vol. 323(C).
    4. Van Hien Nguyen & Kyoung Kwan Ahn, 2025. "Performance Evaluation of Beluga Whale Optimization–Long Short-Term Memory–Random Forest Networks for Trajectory Control and Energy Optimization in Excavator Systems," Mathematics, MDPI, vol. 13(7), pages 1-24, April.

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