A Multi-Scale Time Method for the State of Charge and Parameter Estimation of Lithium-Ion Batteries Using MIUKF-EKF - Ji, Shiyu; Sun, Yi; Chen, Zexing; Liao, Wu (Frontiers in Energy Research, 2022)
Accurate state estimation is essential for the safe and reliable operation of lithium-ion batteries, which nowadays are becoming increasingly used in energy storage system. However, the accura-cy of the battery states assessment to a great extent depends on the accuracy of the battery model parameters. a direct measurement of the SoC is not possible, Kalman filter-based estimation meth-ods are widely used. Which is harder to obtain precisely. However, it is difficult to estimate SOC accurately online and the estimation accuracy is not high. This paper proposes a method for pa-rameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Aiming at the slow-varying characteristics of battery parameters and the fast-varying characteristics of bat-tery SOC, a multi-scale Kalman filter is proposed and used to perform online measurement battery parameters and SOC estimation, so that battery parameters are estimated with macro scale, Bat-tery SoC is estimated with micro scale. The accurate estimate of battery SOC was obtained in real-time through a Kalman filtering algorithm.