State-of-Charge Estimation of Li-ion Battery Packs Based on Optic Fibre Sensor Measurements

This paper presents a battery pack State-of-Charge (SOC) estimation approach by integrating both the cell-based strategy and the pack-based strategy. The approach first utilizes an optic fibre sensor network to monitor variations in strain across the battery cells, based on which a strain model is developed to estimate the SOC of single cells. Then, the cell-based strategy is adopted, for which the SOC of a pack is determined by the highest SOC of single cells observed during charging and the lowest SOC of single cells during discharging. To improve the SOC estimation accuracy of the battery pack strategy, the Thevenin model is employed in conjunction with the Extended Kalman Filter (EKF). The final SOC estimation of the battery pack is then obtained by averaging the results obtained from both the cell-based strategy and the pack-based strategy. Experimental results confirm that this modelling strategy can significantly improve the estimation accuracy and reliability.