Junfu Li1,2, Lixin Wang1, Chao Lyu1, and Michael Pecht2
1 School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, PR China
2 CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
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.
This article is available online here and to CALCE Consortium Members for personal review.