| 铅酸蓄电池自放电程度的人工神经网络检测 |
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| 引用本文： | 范红军,殷合香,郑卫东. 铅酸蓄电池自放电程度的人工神经网络检测[J]. 自动化与信息工程, 2011, 32(1): 34-36 |
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| 作者姓名： | 范红军 殷合香 郑卫东 |
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| 作者单位： | 海军航空工程学院青岛分院 |
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| 摘 要： | 本文提出基于人工神经网络的铅酸蓄电池自放电程度检测方法,并以蓄电池开路端电压变化量、工作温度、蓄电池老化程度作为输入建立了BP神经网络。实例证明,BP神经网络检测蓄电池自放电程度的方法便捷可行,且具有较高准确性。
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| 关 键 词： | 铅酸蓄电池 自放电程度 BP神经网络 |
Testing with Artificial Neural Network to the Self-Discharge Degree of Lead-Acid Battery |
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| Fan Hongjun,Yin Hexiang,Zheng Weidong. Testing with Artificial Neural Network to the Self-Discharge Degree of Lead-Acid Battery[J]. Automation & Information Engineering, 2011, 32(1): 34-36 |
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| Authors: | Fan Hongjun Yin Hexiang Zheng Weidong |
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| Affiliation: | Fan Hongjun Yin Hexiang Zheng Weidong (Naval Aeronautical Engineering Institute Qingdao Branch) |
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| Abstract: | A measurement to testing the self-discharge degree of lead-acid battery is presented based on artificial neural network. And A BP neural network with the battery opening voltage working temperature and degree of new or old as inputs is established. The example shows that the BP network can test the self-discharge degree expediently, and the result is highly veracious. |
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| Keywords: | Lead-Acid Batteries Self-Discharge Degree BP Neural Network |
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