基于神经网络的液压混合动力车辆蓄能器SOC状态预测研究  

Research on Prediction of SOC State of Accumulator of Hydraulic Hybrid Vehicle Based on Neural Network

作　　者：周鹏 吴相稷 ZHOU Peng;WU Xiangji(Faculty of Electrical and Mechanical Engineering,Kunming Metallurgy College,Kunming 650033,China;Faculty of Transportation Engineering,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明冶金高等专科学校电气与机械学院,云南昆明650033 [2]昆明理工大学交通工程学院,云南昆明650500

出　　处：《昆明冶金高等专科学校学报》2021年第1期55-58,共4页Journal of Kunming Metallurgy College

基　　金：昆明冶金高等专科学校科研基金项目:重型串联式液压混合动力汽车控制策略研究(2019XJZK07)。

摘　　要：建立基于神经网络的液压混合动力车辆液压蓄能器SOC荷压状态模型,通过选取某重型液压混合动力车辆,搭建Matlab/Simulink平台下仿真模型。在FUDS仿真循环工况下,分析车辆的实际车速与期望车速、车速误差参数、蓄能器SOC预测状态参数等,得出结论:在液压蓄能器ACC的荷压状态开启值为0.2,荷压状态关闭值为0.5时,发动机与蓄能器的工作协调最好。SOC值的响应较好,达到了预期效果。The hydraulic accumulator(SOC)load model of hydraulic hybrid vehicles based on neural network control is established.By selecting a certain heavy-duty hydraulic hybrid vehicle,the simulation model under Matlab/Simulink platform is built.In the FUDS simulation cycle,the actual vehicle speed and expected speed,vehicle speed errorparameters,the SOC predict state parameters,etc.are analyzed.It is concluded that when the opening value of hydraulic accumulator ACC is 0.2 and the closing value is 0.5,the coordination between engine and accumulator is the best.The response of SOC value is good,and the expected effect is achieved.

关 键 词：液压混合动力 联邦城市循环工况 神经网络控制液压蓄能器 荷压状态 车速误差 

分 类 号：U491.8[交通运输工程—交通运输规划与管理]