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On-line Access: 2025-02-28
Received: 2024-01-21
Revision Accepted: 2024-05-11
Crosschecked: 2025-02-28
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Parameter matching and optimization of hybrid excavator swing system
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Chao SHEN, Jianxin ZHU, Jian CHEN, Saibai LI, Lixin YI. Parameter matching and optimization of hybrid excavator swing system[J]. Journal of Zhejiang University Science A, 2025, 26(2): 138-150.
@article{title="Parameter matching and optimization of hybrid excavator swing system",
author="Chao SHEN, Jianxin ZHU, Jian CHEN, Saibai LI, Lixin YI",
journal="Journal of Zhejiang University Science A",
volume="26",
number="2",
pages="138-150",
year="2025",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2400040"
}
%0 Journal Article
%T Parameter matching and optimization of hybrid excavator swing system
%A Chao SHEN
%A Jianxin ZHU
%A Jian CHEN
%A Saibai LI
%A Lixin YI
%J Journal of Zhejiang University SCIENCE A
%V 26
%N 2
%P 138-150
%@ 1673-565X
%D 2025
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2400040
TY - JOUR
T1 - Parameter matching and optimization of hybrid excavator swing system
A1 - Chao SHEN
A1 - Jianxin ZHU
A1 - Jian CHEN
A1 - Saibai LI
A1 - Lixin YI
J0 - Journal of Zhejiang University Science A
VL - 26
IS - 2
SP - 138
EP - 150
%@ 1673-565X
Y1 - 2025
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2400040
Abstract: In this study, a novel synergistic swing energy-regenerative hybrid system (SSEHS) for excavators with a large inertia slewing platform is constructed. With the SSEHS, the pressure boosting and output energy synergy of multiple energy sources can be realized, while the swing braking energy can be recovered and used by means of hydraulic energy. Additionally, considering the system constraints and comprehensive optimization conditions of energy efficiency and dynamic characteristics, an improved multi-objective particle swarm optimization (IMOPSO) combined with an adaptive grid is proposed for parameter optimization of the SSEHS. Meanwhile, a parameter rule-based control strategy is designed, which can switch to a reasonable working mode according to the real-time state. Finally, a physical prototype of a 50-t excavator and its AMESim model is established. The semi-simulation and semi-experiment results demonstrate that compared with a conventional swing system, energy consumption under the 90° rotation condition could be reduced by about 51.4% in the SSEHS before parameter optimization, while the energy-saving efficiency is improved by another 13.2% after parameter optimization. This confirms the effectiveness of the SSEHS and the IMOPSO parameter optimization method proposed in this paper. The IMOPSO algorithm is universal and can be used for parameter matching and optimization of hybrid power systems.
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