LAUSR

Accurate battery state of charge (SOC) estimation can contribute to a reasonable charging/discharging strategy for battery management systems (BMSs). It can also prevent severe damage to the battery (pack) caused by over-charging or over-discharging. This work develops a battery SOC estimation method based on a simplified electrochemical model. Simulated validation under dynamic current loads at room temperature showed a maximum SOC error of less than 2.37% within the whole range for a single cell. The developed method can reach a balance between estimation accuracy and computational cost, with average iterative calculation time of about 0.05 ms. A charging/discharging control strategy for battery packs with deep charging depth and fast speed has also been developed, and it can help identify the “weakest’’ cell according to the definition of battery pack SOC. Statistical results show that the SOC average absolute error (AAE) at two constant discharge C-rates ranged from 0.44% to 1.65%. Analysis and assessment of the accuracy and robustness of the developed method for single cells and battery packs indicate that the SOC estimation accuracy is acceptable and shows potential for applications in BMSs.