模糊神经网络技术的铅酸蓄电池性能检测研究  

Led-acid battery performance testing research based on neural network technology

作　　者：赵徐成[1] 王旭昆 朱逸天 孙默圆 凌军 

机构地区：[1]空军勤务学院航空四站系 [2]解放军95968部队 [3]沈阳航空四站厂

出　　处：《电源技术》2016年第12期2405-2406,2414,共3页Chinese Journal of Power Sources

摘　　要：提出了蓄电池动态内阻的概念。论证了铅酸蓄电池内阻与剩余容量之间良好的相关性。以铅酸蓄电池动态内阻、电解液密度和电解液温度为判定蓄电池容量和瞬间放电能力的特征矢量。设计了动态电子负载和蓄电池特征矢量检测系统,采集蓄电池特征矢量数据,经模糊神经网络对融合的数据进行综合推理,以测定蓄电池的剩余容量和瞬间放电能力。最后,对一组10块2 V600 Ah的铅酸蓄电池进行性能测试。lead-acid battery, The concept of dynamic internal resistance of the battery was put forward. Good correlation between battery internal resistance and residual capacity was demonstrated. The dynamic resistance of lead-acid electrolyte density and temperature of the electrolyte were regarded as the feature vector to determine battery capacity and discharge capacity. Dynamic electronic load and battery characteristic vector detection system were designed. The battery characteristics of vector data was collected. The data fusion of integrated reasoning of fuzzy neural network was used to determine the residual capacity of the battery, and discharge capacity. Finally, a performance testing was done for the lead-acid battery for a group of 10 to 2 volts 600 Ah.

关 键 词：铅酸蓄电池 动态内阻 神经网络 剩余容量 

分 类 号：TM912[电气工程—电力电子与电力传动]