锂电池分段分数阶建模与荷电状态估计  

Segment fractional order modeling and state-of-charge estimation of lithium batteries

作　　者：杨睿 张向文[1,2] YANG Rui;ZHANG Xiangwen(School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin Guangxi 541004,China;Guangxi Key Laboratory of Automatic Detecting Technology and Instruments,Guilin Guangxi 541004,China)

机构地区：[1]桂林电子科技大学电子工程与自动化学院,广西桂林541004 [2]广西自动检测技术与仪器重点实验室,广西桂林541004

出　　处：《电源技术》2022年第1期63-67,共5页Chinese Journal of Power Sources

基　　金：国家自然科学基金项目(51465011);广西自然科学基金项目(2018GXNSFAA281282);广西自动检测技术与仪器重点实验室主任基金项目(YQ17110);桂林电子科技大学研究生教育创新计划(2019YCXS091)。

摘　　要：为提高等效电路模型准确性,考虑等效电容分数阶本质和锂电池充放电不同阶段的不同变化特性,采用分数阶微积分理论建立了基于二阶RC模型的电池分段分数阶等效电路模型。用粒子群算法分段辨识分数阶阶数,通过混合脉冲功率特性(HPPC)实验辨识模型参数,使模型更符合电池实际工作状态。实验结果显示,新模型能够更准确地模拟电池充放电特性变化。构造分数阶卡尔曼滤波算法(FOKF)来估计电池荷电状态(SOC),分别与扩展卡尔曼滤波(EKF)算法、实验参考值进行比较。结果显示,所提算法的估计精度更高,均方根误差为0.95%,比EKF算法减少了45.4%。In order to improve the accuracy of the equivalent circuit model,this paper establishes a segment fractional order equivalent circuit model based on the second order RC model,by using the theory of fractional order calculus.Simultaneously,the fractional nature of the equivalent capacitance and the different property of the lithium battery at different stages of charging and discharging process are considered in this paper.The particle swarm optimization algorithm was used to identify the segment fractional order,meanwhile,the hybrid pulse power characteristic experiment(HPPC)was used for identifying the model parameters,and therefore the model could be closer to the actual working state of the battery.According to the results,the new model simulates the battery characteristics changes more accurately during the charging and discharging process.Finally,a fractional order of Kalman filter algorithm(FOKF)was designed to estimate the battery state-of-charge(SOC),which was compared with the extended Kalman filtering algorithm(EKF)and the experimental reference value,respectively.The results show that the root mean square error of the proposed new algorithm is 0.95%,which is lower 45.4%than that of EKF,so the new algorithm has higher accuracy.

关 键 词：分数阶等效电路模型 参数辨识 分数阶卡尔曼滤波算法 荷电状态估计 

分 类 号：TM912[电气工程—电力电子与电力传动]