Artificial neural network for state-of-charge estimation of Ni-MH batteries with photovoltaic power system

被引：0
|
作者：
Miyasaka, A. [1 ]
Yamashita, A. [1 ]
Shodai, T. [1 ]
机构：
[1] NTT Energy & Environm Syst Labs, Atsugi, Kanagawa, Japan
来源：
BATTERY/ENERGY TECHNOLOGY (GENERAL) - 216TH ECS MEETING | 2010年 / 25卷 / 35期
关键词：
D O I：
10.1149/1.3414019
中图分类号：
O646 [电化学、电解、磁化学];
学科分类号：
081704 ;
摘要：
We developed a Ni-MH battery module and combined it with a photovoltaic panel as a hybrid power system for meteorological sensors. When the battery is charged with small current, such as less than 5 amperes (0.05 C), a conventional method on the state of charge (SOC) of the battery calculated from the summation of the current of the battery is inaccurate. For estimation of the SOC of the battery module, we therefore introduced an artificial neural network model in which the input data were the temperature and voltage of the battery module. It appears that the new estimation method is more accurate than the conventional one.
引用
收藏
页码：203 / 211
页数：9
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