火力与指挥控制2013，Vol.38Issue(4)：140-144,5.
PHEV电池电荷状态估计设计及仿真
Design and Simulation of Battery SOC Estimation for PHEV
摘要
Abstract
The battery management system (BMS) of hybrid electrical vehicle (HEV) is the core of power management system components in which the state of charge (SOC) is the main parameter to control the vehicle strategy.Considering of complexity of the driving environment and the nonlinear character of the power battery system,the SOC estimation with advanced BP neural network method is presented to analyze the system in this paper.The artificial neural network (ANN) of SOC measurement methods are designed in this paper.Adequate sample space was obtained through various HEV battery charge and discharge,with measuring demands of the HEV battery management system and estimating characteristics of neural network.The results show that,compared with the traditional off-line SOC estimation method,it can effectively decrease errors and improve the precision of battery SOC.关键词
并联式混合动力汽车/电池电荷估计/人工神经网络Key words
hybrid electrical vehicle(HEV)/ state of charge(SOC)/ artificial neural network(ANN)分类
交通工程引用本文复制引用
付主木,赵瑞..PHEV电池电荷状态估计设计及仿真[J].火力与指挥控制,2013,38(4):140-144,5.基金项目
国家自然科学基金(60904023) （60904023）
河南省科技攻关基金(102102210449) （102102210449）
河南省教育厅自然科学基金资助项目(2008B510003) （2008B510003）
