An Adaptive Hybrid SOC Estimation Method for Lithium-Ion Batteries Using Voltage Residual and Adaptive Correction Factors

In battery management systems (BMS), accurate state-of-charge (SOC) estimation is essential for reliable and efficient operation of lithium-ion batteries. Conventional current integration methods suffer from cumulative errors over long-term operation, while voltage-based methods are sensitive to polarization effects and measurement noise, leading to unstable correction behavior. To address these limitations, this paper proposes an adaptive hybrid SOC estimation method that combines current integration with voltage-based correction. The proposed method derives a voltage residual using an equivalent circuit model and converts it into SOC correction based on the OCV–SOC relationship. In addition, adaptive correction factors and a mode-switching strategy are employed to regulate the correction strength and selectively apply voltage-based correction depending on operating conditions. Experimental validation using a long-term dynamic current profile demonstrates that the proposed method effectively suppresses cumulative error and improves estimation accuracy and stability across the entire SOC range.