基于径向基过程神经元网络的锂电池SOC算法  

A Training Algorithm of Battery SOC Based on RBF Neural Networks Model

作　　者：于文韬 白鹏飞 王玉芬 孙丽媛 

机构地区：[1]河北汉光重工有限责任公司 [2]海军驻保定地区航空军事代表室

出　　处：《化工自动化及仪表》2018年第2期157-159,共3页Control and Instruments in Chemical Industry

摘　　要：提出基于径向基过程神经元网络算法计算锂电池的SOC,该方法应用的是梯度下降模式。介绍径向基过程神经元网络的推导,将电压、电流和温度的时间动态数据序列作为网络的输入,以实测采样数据作为样本,组建网络模型,并与安时积分法进行对比实验。Having RBF neural network algorithm based to calculate lithium battery＇s SOC was proposed and the gradient descent method was adopted to realize it.Deducing RBF process neural network and having the dynamic time of data of the sequence voltage,current and temperature taken as the sample of the input of the network to build a network model and to compared it with ampere-hour integral method for the experiment.

关 键 词：径向基过程神经元网络算法 锂电池 SOC计算 动态数据 

分 类 号：TH862.7[机械工程—仪器科学与技术]