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Journal of Zhejiang University SCIENCE A 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/jzus.A2400040


Parameter matching and optimization of hybrid excavator swing system


Author(s):  Chao SHEN, Jianxin ZHU, Jian CHEN, Saibai LI, Lixin YI

Affiliation(s):  State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Central South University, Changsha 410083, China; more

Corresponding email(s):   zjianx-918@163.com

Key Words:  Hybrid system, Energy regeneration, Swing braking energy, Parameter optimization, MOPSO, Adaptive grid


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, 1998, -1(-1): .

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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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