High-Accuracy State of Charge Estimation Solution of Lithium-Ion Reconfigurable Smart Battery

With of the growing emphasis on refined management of lithium-ion batteries (LIBs), there is a significant demand for the state of charge (SOC) estimation at the individual LIB cell level. Following the emerging concept of reconfigurable smart batteries, a high-accuracy SOC estimation solution is proposed in this paper. In particular, the SOC estimation by the iterative extended Kalman filter (IEKF) is implemented based on smart battery modeling, which innovatively incorporates the cell electrical coupling for information enhancement in cell-level SOC estimation. Experimental results demonstrate that the algorithm enables highly precise SOC estimation, with a maximum SOC estimating error of only 1% for all in-pack cells.