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OA

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.