基于改进粒子群优化算法的混凝土泵车全局功率匹配  

Global Power Matching of Concrete Pump Truck Based on Advanced Particle Swarm Optimization Algorithm

作　　者：饶红艳 王少杰[1] 侯亮[1] 苏德赢 RAO Hong-yan;WANG Shao-jie;HOU Liang;SU De-ying(Department of Mechanical&Electrical Engineering,Xiamen University,Xiamen 361101,China)

机构地区：[1]厦门大学机电工程系,福建厦门361101

出　　处：《东北大学学报（自然科学版）》2023年第6期840-848,共9页Journal of Northeastern University(Natural Science)

基　　金：国家重点研发计划项目(2020YFB1709901,2020YFB1709904);福建省自然科学基金资助项目(2022J01060);福建省中央引导地方专项(2020L3002).

摘　　要：针对混凝土泵车全局功率匹配技术存在优化算法求解质量差的问题,本文提出了一种基于改进粒子群算法的工况自适应混凝土泵车全局功率匹配策略.首先,在MWorks平台上构建基于发动机与液压泵等特性数据,集成液压､机械､控制､负载与动力五大模块的泵送系统模型;然后,采用改进粒子群算法进行全局匹配优化,输出不同作业需求下的参数经济匹配值;最后,基于构建的泵送系统仿真平台,分析典型工况下不同功率匹配策略的节能效果.结果表明:所提策略与传统策略相比,轻､中､重载工况分别节油5.86%,5.24%和1.74%.The optimization algorithm of concrete pump truck global power matching technology has poor solution quality,this paper proposed a condition adaptive global power matching strategy based on advanced particle swarm optimization.Firstly,based on the characteristic data of engine and hydraulic pump,a pumping system model on MWorks that integrated five major modules of hydraulic,mechanical,control,load and power is builted;Then,the advanced particle swarm optimization algorithm is used for global matching optimization and output the economic matching value of parameters under different operation requirements;Finally,a pumping system simulation platform is established to analyze the energy-saving effect of different power matching strategies under typical conditions.The results show that compared with the traditional strategy,strategy proposed saves fuel by 5.86%,5.24%and 1.74%under light,medium and heavy operation,respectively.

关 键 词：泵送系统 功率匹配 APSO算法 节能优化 MWorks仿真 

分 类 号：TP113[自动化与计算机技术—控制理论与控制工程]