广东电力2026，Vol.39Issue(8)：36-44,9.DOI:10.3969/j.issn.1007-290X.2026.08.004
基于双平方根无迹卡尔曼滤波的储能电池SOC与SOH联合估计方法
Joint Estimation of State of Charge and State of Health for Energy Storage Batteries Based on Double Square-root Unscented Kalman Filter
摘要
Abstract
To address the issues of strong coupling between state of charge(SOC)and state of health(SOH)of the lithium-ion batteries under dynamic operating conditions in the energy storage systems,and insufficient accuracy and divergence of traditional joint estimation algorithms,a joint estimation method based on dual square root unscented Kalman filter(Dual-SRUKF)is proposed.The method constructs a second-order RC equivalent circuit model and designs a dual-filter parallel coupling structure.One SRUKF module estimates the ohmic resistance representing SOH in real-time,while the other updates SOC dynamically,achieving mutual correction through parameter iteration.The square root algorithm using Cholesky decomposition and QR decomposition ensures the numerical stability of the filter.Experiments under constant current and typical urban dynamic cycles demonstrate that the estimation mean absolute error of SOC is 0.48%,and the mean absolute error of SOH is as low as 0.042%.The convergence speed is improved by 37.8%,effectively solving the filter divergence problem.The research provides reliable technical support for enhancing the operational economy and full lifecycle health management of energy storage systems.关键词
锂离子电池/荷电状态/健康状态/储能系统/卡尔曼滤波Key words
lithium-ion battery/state of charge/state of health/energy storage system/Kalman filtering分类
信息技术与安全科学引用本文复制引用
张艳辉,赵天任..基于双平方根无迹卡尔曼滤波的储能电池SOC与SOH联合估计方法[J].广东电力,2026,39(8):36-44,9.基金项目
国家重点研发项目(2025YFE0109500) （2025YFE0109500）
广东省基础与应用基础研究基金海上风电联合基金项目(2023A1515240014) （2023A1515240014）
