基于温度补偿的动力锂电池SOC估算方法  

State of Charge Estimation of Lithiumion Power Battery Considering Temperature Influence

作　　者：刘新天 彭泳 何耀 郑昕昕 LIU Xin-tian;PENG Yong;HE Yao;ZHENG Xin-xin(School of Electrical and Automation Engineering,Hefei University of Technology,Hefei Anhui 230009,China)

机构地区：[1]合肥工业大学电气与自动化工程学院,安徽合肥230009>

出　　处：《计算机仿真》2021年第5期66-69,328,共5页Computer Simulation

基　　金：国家自然科学基金(61603120);国家自然科学基金(21373074);安徽省国际合作项目(1303063010)。

摘　　要：动力电池的荷电状态(State of Charge,SOC)是电动汽车的重要参数之一,直接影响电动汽车的安全控制与可续行里程的评估。电池总容量作为估算电池SOC的重要变量之一,其与使用环境温度密切相关,而在SOC估计算法中常被认为是恒定值,从而影响不同环境温度下锂电池SOC估计精度。为实现对锂电池SOC的准确估计,考虑温度对锂电池容量等特性参数的影响,通过引入温度补偿模型,并结合扩展卡尔曼滤波(Extended Kalman Filter,EKF)算法实现对锂电池SOC的动态估计。在不同环境温度下模拟电动汽车实际工况对锂电池进行放电试验,并比较未经温度补偿的SOC算法与补偿后的SOC算法精度。研究结果表明,所提出的方法适用于不同温度的锂电池,能实现较为精确的估计。As an important parameter of the electric vehicles,the State-of-Charge(SOC)of Lithium-ion battery has a direct influence on security control and the remainder driving range estimation.The capacity which plays an important role in SOC estimation changes with the ambient temperature,but as a constant value in most instances,so the SOC estimation accuracy decreases in different temperatures.In order to achieve accurate estimation of lithium battery SOC,considering the influence of temperature on characteristic parameters such as lithium battery capacity,dynamic estimation of lithium battery SOC was realized by introducing temperature compensation model and combining Extended Kalman Filter(EKF)algorithm.The discharge test of the lithium battery was carried out under the actual operating conditions of the simulated electric vehicle under different ambient temperatures,and the accuracy of the SOC algorithm without temperature compensation and the accuracy of the compensated SOC algorithm were compared.The research results show that the proposed method is suitable for lithium batteries with different temperatures,which can achieve a more accurate estimation.

关 键 词：电动汽车 锂电池 荷电状态 温度补偿 扩展卡尔曼滤波 

分 类 号：TM743[电气工程—电力系统及自动化]