Parameter matching and optimization of hybrid excavator swing system  

作　　者：Chao SHEN Jianxin ZHU Jian CHEN Saibai LI Lixin YI 

机构地区：[1]State Key Laboratory of Precision Manufacturing for Extreme Service Performance,Central South University,Changsha 410083,China [2]The National Enterprise R&D Center,Sunward Intelligence Equipment Co.,Ltd.,Changsha 410100,China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2025年第2期138-150,共13页浙江大学学报(英文版)A辑(应用物理与工程)

基　　金：supported by the Changsha Major Science and Technology Plan Project,China(No.kq2207002);the Natural Science Foundation of Hunan Province(No.2023JJ40720);the Postgraduate Innovative Project of Central South University,China(No.2022XQLH058)。

摘　　要：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.

关 键 词：Hybrid system Energy regeneration Swing braking energy Parameter optimization Improved multi-objective particle swarm optimization(IMOPSO) Adaptive grid 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]