储能科学与技术2024，Vol.13Issue(5)：1667-1676,10.DOI:10.19799/j.cnki.2095-4239.2023.0869
基于改进模型与优化自适应CKF的锂离子电池快速变温工况下的SOC估计
State-of-charge estimation of lithium-ion batteries in rapid temperature-varying environments based on improved battery model and optimized adaptive cubature Kalman filter
摘要
Abstract
In pursuit of high-precision and robust state monitoring of lithium-ion batteries under an environment with rapid temperature fluctuations,we propose a state-of-charge(SOC)estimation method based on an improved battery model and an optimized adaptive cubature Kalman filter(CKF).First,the discrepancies in SOC definition between a pseudo-two-dimensional electrochemical model and an equivalent circuit model are discussed.Introducing the improved battery model,the SOC results from the equivalent circuit model,calculated by ampere-hour integration,are rectified using intermediate variables.Subsequently,model parameters influenced by environmental temperature are identified from open-circuit voltage and dynamic stress test data under various constant-temperature environments.Moreover,the traditional CKF is optimized based on principles of matrix diagonalization and adaptive covariance matrix,bolstering overall stability and the ability of the proposed SOC estimation method to handle random sampling noise.Finally,experimental validation under six diverse battery operating conditions in rapidly temperature-varying environments demonstrates the accuracy of the established improved battery model and the effectiveness of the proposed SOC estimation method,even under random sampling noise.The results demonstrate the versatility of the proposed SOC estimation method across various battery operating conditions in rapidly temperature-varying environments,with an estimated root mean square error of approximately 1.3%under random sampling noise.关键词
锂离子电池/荷电状态/变温环境/改进电池模型/优化自适应容积卡尔曼滤波Key words
lithium-ion battery/state of charge/temperature-varying environments/improved battery model/optimized adaptive cubature Kalman filter分类
动力与电气工程引用本文复制引用
廉高棨,叶敏,王桥,李岩,麻玉川,孙乙丁,杜鹏辉..基于改进模型与优化自适应CKF的锂离子电池快速变温工况下的SOC估计[J].储能科学与技术,2024,13(5):1667-1676,10.基金项目
陕西省科技创新团队支撑计划项目(2020TD0012),长安大学研究生科研创新实践项目(300103723030). （2020TD0012）
