模糊逻辑与神经网络的蓄电池容量预测  

Study on estimating storage battery's capacity based on fuzzy logic and neural network technology

作　　者：陶兴华[1] 陈彪[2] 张俊洪[1] 

机构地区：[1]海军工程大学电气工程系,湖北武汉430033 [2]中国人民解放军4806厂,浙江325003

出　　处：《电源技术》2004年第9期578-582,共5页Chinese Journal of Power Sources

摘　　要：蓄电池容量预估的精度由于受到诸多因素的影响而难以让人满意。由于仅通过电池开路电压这一物理量即可与剩余容量建立一一对应关系,基于这种思想,文章在对某型号锂离子蓄电池大量实验的基础上,提取压降变化与剩余容量、电流、温度的一般规律,并通过模糊逻辑控制与神经网络技术手段实现了对蓄电池剩余容量的较准确预估。仿真及实验验证了该系统的有效性。The estimation accuracy of battery capacity was poor because of so many factors'affection. However, the corresponding relative between the capacity and open circuit voltage can be built. Based on lots of experiments, common rules of voltage descent and the capacity, current, temperature was got, then the batter capacity estimation system was built using fuzzy logic and neural network(NN). It was testified by simulation and test results .

关 键 词：蓄电池 剩余容量 模糊逻辑 神经网络 

分 类 号：TM912.2[电气工程—电力电子与电力传动]