State of charge estimation for lithium-ion battery balancing systems considering branch current dynamics under non-ideal switching

State-of-charge (SoC) estimation is essential for lithium-ion battery management systems. In practical battery packs, balancing circuits are commonly used to reduce cell inconsistency. However, most existing balancing-aware methods treat the balancing branch as an ideal binary switch and directly determine the balancing current from the switching command. This simplification neglects branch-current dynamics under non-ideal switching, which may introduce mismatch in cell-current reconstruction and reduce estimation accuracy. To address this issue, this paper proposes an SoC estimation method for lithium-ion battery balancing systems considering branch-current dynamics under non-ideal switching. A transition-state variable α is introduced to describe the continuous evolution of the effective balancing-branch conductance and current following a switching-command change. Based on this model, a non-ideal transition extended Kalman filter (NIT-EKF) is designed for SoC estimation. Experimental results under constant-current charge, constant-current discharge, dynamic discharge, and prescribed parameter mismatch show that the proposed method improves overall SoC and terminal-voltage estimation performance compared with the conventional extended Kalman filter (EKF) and the switching extended Kalman filter based on an ideal branch-switch assumption (ideal-switch SEKF). Under initial SoC bias, the proposed method reduces peak SoC error and improves terminal-voltage prediction. These results demonstrate the value of incorporating effective branch-current dynamics under non-ideal switching into SoC estimation for lithium-ion battery balancing systems.