基于自适应卡尔曼滤波的梯次电池荷电状态估算  

State of Charge Estimation for Cascade Batteries Based on Adaptive Kalman Filtering

作　　者：柴建勇 侯恩广 李岳炀[3] CHAI Jianyong;HOU Enguang;LI Yueyang(Shandong Hi-speed Information Group Co.,Ltd.,Jinan 250101,Shandong,China;School of Rail Transportation,Shandong Jiaotong University,Jinan 250357,Shandong,China;School of Electrical Engineering,University of Jinan,Jinan 250022,Shandong,China)

机构地区：[1]山东高速信息集团有限公司,山东济南250101 [2]山东交通学院轨道交通学院,山东济南250357 [3]济南大学自动化与电气工程学院,山东济南250022

出　　处：《济南大学学报（自然科学版）》2021年第2期165-169,共5页Journal of University of Jinan(Science and Technology)

基　　金：国家自然科学基金项目(61973135);山东省重大科技创新工程项目(2019JZZY010441)。

摘　　要：针对梯次电池荷电状态初始值不明确、估算不准确的问题,提出基于自适应卡尔曼滤波算法的梯次电池荷电状态的估算方法;建立梯次电池的全寿命周期模型,在卡尔曼滤波算法的基础上引入自适应估算原理,实时估算时变噪声,提高滤波稳定性,增强自适应特性。仿真结果表明,当荷电状态初始值为30%、 50%、 60%时,该算法表现出优良的自适应特性、收敛性和准确性,梯次电池的荷电状态都可以快速调整,并且荷电状态估算误差小于3%。To solve the problem that initial values of cascade battery state of charge was uncertain and estimation was inaccurate,a state of charge estimation method for cascade batteries based on adaptive Kalman filtering algorithm was proposed.A full life cycle model of cascade batteries was established.Based on Kalman filtering algorithm,adaptive estimation principle was introduced to estimate time-varying noise in real time,so as to improve filtering stability and enhance adaptive characteristics.The simulation results show that when initial state of charge values are 30%,50%,and 60%,the proposed method has good adaptive characteristics,convergence,and accuracy.The state of charge values of cascade batteries can be adjusted quickly,and the estimation error of state of charge is less than 3%.

关 键 词：梯次电池 荷电状态 自适应卡尔曼滤波 全生命周期电池模型 

分 类 号：TM912.1[电气工程—电力电子与电力传动]