文献类型：会议论文

英文题名：Research of MH-Ni Battery State of Charge Estimation based on Grey System Neural Network Model

作者：Long, Jianxiong[1]

第一作者：龙建雄

通讯作者：Long, JX[1]

机构：[1]Beijing Union Univ, Coll Appl Sci & Technol, Beijing 102200, Peoples R China

第一机构：北京联合大学应用科技学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Appl Sci & Technol, Beijing 102200, Peoples R China.|[1141775]北京联合大学应用科技学院;[11417]北京联合大学;

会议论文集：International Conference on Mechanical Materials and Manufacturing Engineering (ICMMME 2011)

会议日期：JUN 20-22, 2011

会议地点：Nanchang, PEOPLES R CHINA

语种：英文

外文关键词：State of Charge (SOC); Grey System Neural Network; MH-Ni Battery; Inner Resistance

摘要：In order to effectively achieve MH-Ni battery state of charge estimation, grey system neural network model is put forward to predict battery state of charge by using the parameters of battery pulse current response signal as input for grey system neural network. The state of charge is as the network output and the response parameters of the battery pulse current as the input. The results show that its prediction accuracy of the state of charge can be achieved to requirements of the electric vehicles in applications by this method to predict the state of charge.