基于固定电阻放电的蓄电池SOC在线估算方法  

New on-line estimation method of battery SOC based on discharge through fixed resistor

作　　者：廉春原[1] 李蓓[1] 蔡纪鹤[1] 

机构地区：[1]常州工学院,江苏常州213001

出　　处：《电源技术》2015年第11期2395-2399,共5页Chinese Journal of Power Sources

基　　金：国家自然科学基金项目(51077047);常州工学院自然科学基金项目(YN1108);常州工学院自然科学基金项目(YN1302)

摘　　要：针对传统蓄电池SOC估算方法不能在线测量、误差较大等缺点,提出一种基于固定电阻放电与神经网络预测相结合的SOC在线估算新方法。该方法在蓄电池正常工作过程中周期性切换到固定电阻放电状态,并根据该状态下的电池端电压值来估算SOC。实验结果表明,相比传统方法,该方法具有能在线测量、精度高、无累积误差等特点,具有很好的工程实用价值。Aiming at the problem that traditional methods of SOC estimation for battery could not be applied to the on-line measurement and could result in big error, then a new on-line estimation method of battery SOC was proposed based on discharge through fixed resistor and neural network prediction. By switching the working mode of battery periodically from normal working mode to the mode of discharge through fixed resistor and measuring the terminal voltage of battery, SOC estimation was achieved. Experimental results validate that this new method can be used online with higher precision and no accumulation error compared with traditional method and it has the actual application value.

关 键 词：蓄电池 SOC 固定电阻放电 神经网络 

分 类 号：TM912[电气工程—电力电子与电力传动]