LAUSR

For power batteries used in the electric vehicle, accurate state-of-charge (SOC) and state-of-health (SOH) are important. Meanwhile, the current rate in actual working conditions often varies dramatically. However, the influence of current rates on voltage and battery states estimation has been neglected for a long time. To solve this problem, in this article, a hierarchical estimation model considering the current rate is proposed. The fractional-order model is used in the battery modeling, the data-driven method is used to identify parameters, and a multiscale dual extended Kalman filter (DEKF) is used in estimation of battery states. For SOC estimation, the proposed method improves the accuracy by 35.8% and 36.5% compared with traditional DEKF under two conditions. For SOH estimation, the proposed method improves the accuracy by 34.8% and 43.1% under two current conditions.