负载方向智能识别的挖掘机斗杆内收节能控制方法OA
Energy-saving control method for excavator arm retraction based on intelligent load direction recognition
针对液压挖掘机斗杆内收过程中节流损失引发的能耗过高问题,提出一种基于负载方向智能识别的斗杆内收节能控制方法.基于动臂、斗杆及铲斗油缸的位移传感器数据,建立斗杆、铲斗系统运动学模型,实时计算其复合重心位置,预测斗杆油缸负载力由拉力转为推力的理论切换区间;依据油缸两腔压力数据动态计算实际负载力,于理论切换区间内精准定位拉力到推力的转换点;重新设计斗杆回油回路和对应的节能控制方法,以降低回油过程中的能量损失.研究结果表明:在保证斗杆内收动作平稳性的前提下,新系统斗杆内收动作推力阶段能耗降低了40.8%,完整内收动作的总能耗降低了17%.本研究为液压挖掘机斗杆内收操作的节能优化提供了工程上可行的技术途径.
To reduce the energy consumption caused by throttling losses during excavator arm retraction,this paper proposes an energy-saving control method based on intelligent load direction recognition.First,displacement data from the boom,arm,and bucket cylinders are used to establish a kinematic model of the working device.The composite center of gravity is calculated in real time,and the theoretical transition interval in which the load force acting on the arm cylinder changes from a pulling load to a pushing load is predicted.Then,the actual load force is dynamically determined using pressure data from both chambers of the arm cylinder,enabling accurate identification of the load transition point within the predicted interval.Based on the load characteristics,the arm return hydraulic circuit is redesigned,and a corresponding energy-saving control strategy is developed to reduce energy losses during the return process.Experimental results demonstrate that the proposed method ensures smooth arm retraction while reducing energy consumption during the pushing-load phase by 40.8%and lowering the total energy consumption of a complete retraction cycle by 17%.The proposed method provides an engineeringly feasible solution for improving the energy efficiency of hydraulic excavator arm retraction operations.
刘宇超;高国强;孙依凡;令狐钊;杨书仪;刘朝富;习毅
湖南科技大学 机电工程学院,湖南 湘潭 411201湖南科技大学 机电工程学院,湖南 湘潭 411201湖南科技大学 机电工程学院,湖南 湘潭 411201贵阳永青智控科技股份有限公司,贵阳 550000湖南科技大学 机电工程学院,湖南 湘潭 411201贵阳永青智控科技股份有限公司,贵阳 550000湖南科技大学 机电工程学院,湖南 湘潭 411201
机械制造
挖掘机斗杆内收回油节流损失节能控制
excavatorarm retractionreturn oil throttling lossenergy-saving control
《重庆大学学报》 2026 (9)
48-59,12
湖南省教育厅资助项目(23B0496)国家博士后基金资助项目(2023M731822)湖南省研究生科研创新项目(CX20240869). Supported by Project of Hunan Provincial Education Department(23B0496),National Postdoctoral Fund(2023M731822),and Hunan Provincial Graduate Student Research Innovation Program(CX20240869).
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