基于径向基函数网络的MH/Ni电池建模及容量预测

被引:6
|
作者
邓超
史鹏飞
机构
[1] 哈尔滨工业大学应用化学系
关键词
放电容量; 径向基函数; MH/Ni电池; 人工神经网络;
D O I
暂无
中图分类号
TM911 [化学电源、电池、燃料电池];
学科分类号
摘要
Prediction of discharge capacity was the key task for battery management system in electric vehicles. The basic mechanism of radial basis function (RBF) neural network was briefly analyzed,and the structure of the network was optimized by improved algorithm. The influence of temperature and current on discharge capacity of MH/Ni batteries was discussed. A neural network model of MH/Ni batteries was set up based on RBF neural network. Discharge capacity of batteries under different conditions was estimated with the application of the model. The results showed that the model was of high accuracy and was more efficient in respect of training process than BP network. The simulation tests revealed that the modeling method based on RBF network was feasible.The artificial neural network technique avoids complicated analytic process of mathematic modeling. It provides a new effective and accurate method of prediction of discharge capacity for battery management system.
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页码:673 / 677
页数:5
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