基于微分曲线的LiFePO4电池SOC估计算法研究  

Research of SOC estimation algorithm for LiFePO_4 battery based on differential curves

作　　者：侯朝勇[1] 数见昌弘 许守平[1] 彭文凭 

机构地区：[1]中国电力科学研究院,北京100192 [2]横河电机中国有限公司,北京100020

出　　处：《储能科学与技术》2017年第6期1321-1327,共7页Energy Storage Science and Technology

基　　金：国家自然科学基金项目(51407167);国家电网公司科技项目(DG71-14-001)

摘　　要：电池荷电状态是电池剩余容量状态的重要参数,电池荷电状态准确实时的估算是进行电池有效管控的基础。本文首先根据储能用磷酸铁锂电池的开路电压相对SOC变化率的关系,确定电池荷电状态的识别区;分析电池在不同老化程度、环境温度和充放电倍率等因素影响下的电压和容量的微分曲线(dV/dQ vs.Q),提出了在识别区采用微分曲线进行SOC校正的算法;最后,建立了电池实验系统,验证提出的算法的精度和适用性。The state of charge（SOC） of battery is an important parameter for battery capacity state,the accurate and real-time prediction is one of the most essential performances of for battery management system（BMS）.Firstly,according to the open circuit voltage（OCV） characteristic of LiFePO4 battery,the identification zone for SOC is determined.Under different aging conditions,ambient temperature and charge/discharge ratio,the differential curve of voltage versus capacity（dV/dQ vs.Q） against the charging progress was analyzed.Based on analysis results,the correction algorithm of SOC is proposed using the differential curve.Finally,the lithium battery energy storage system is built,the accuracy and applicability of the algorithm is verified by the experimental results.

关 键 词：磷酸铁锂电池 荷电状态 识别区 微分曲线 

分 类 号：TM911[电气工程—电力电子与电力传动]