基于粒子群算法的复合储能式系统控制优化  

Control Optimization of Composite Energy Storage System Based on Particle Swarm Optimization

作　　者：徐大雨 林慕义[1,2] 陈勇 XU Da-yu;LIN Mu-yi;CHEN Yong(School of Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192;Beijing Laboratory for New Energy Vehicle,Beijing 100192)

机构地区：[1]北京信息科技大学机电工程学院,北京100192 [2]北京电动车辆协同创新中心,北京100192

出　　处：《液压与气动》2021年第8期102-108,共7页Chinese Hydraulics & Pneumatics

基　　金：国家自然科学基金(51608040);北京市自然科学基金(3174049)。

摘　　要：由于复合储能式系统装载机的结构复杂,所以对系统的模糊控制策略要求较高,而现有的利用专家经验对控制器设定的模糊控制规则主观性较强,很难实现系统的最优控制。利用粒子群算法对模糊控制策略进行优化,并将优化后的控制策略通过MATLAB/Simulink所搭建的装载机整车的后向仿真模型进行试验仿真分析。结果表明:通过粒子群算法优化后的控制器控制性更好,且整车的燃油经济性更佳;通过dSPACE进行硬件在环试验,试验与仿真结果基本一致,进而验证了优化结果的有效性。Due to the complex structure of the composite energy storage system loader,the control strategy for the fuzzy control of the system is relatively high.However,the existing fuzzy control rules that use expert experience to set the controller are highly subjective.So it is difficult to achieve optimal control of the system.Using particle swarm algorithm to optimize the control strategy in the fuzzy controller,and testing it through the backward simulation model of the loader vehicle built by MATLAB/Simulink.The results show that the controller optimized by the particle swarm algorithm has better controllability and better fuel economy of the vehicle.Finally,the hardware-in-the-loop test was carried out through dSPACE.The test and simulation results are basically consistent,which verifies the effectiveness of the optimization results.

关 键 词：复合储能系统 模糊控制 粒子群算法 硬件在环 

分 类 号：TH137[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]