Energies 2017, Vol. 133, pp. 572-583, August 15, 2017

State of charge estimation based on a simplified electrochemical model for a single LiCoO2 battery and battery pack

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.

[Home Page] [Articles Page]
Copyright © 2017 by CALCE and the University of Maryland, All Rights Reserved