Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles

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• 作者：Hongwen He ; ^{hwhebit@bit.edu.cn} ; ^{hwenhe@263.net} ; Xiaowei Zhang ; Rui Xiong ; Yongli Xu ; Hongqiang Guo
• 关键词：State-of-charge ; Open-circuit voltage ; Equivalent circuit model ; Online estimation ; Electric vehicles
• 刊名：Energy
• 出版年：2012
• 期刊代码：11_03605442
• 类别：pw
• 出版时间：March, 2012
• 卷：39
• 期：1
• 页码：310-318
• 文件大小：820 K

摘要

This paper presents a method to estimate the state-of-charge (SOC) of a lithium-ion battery, based on an online identification of its open-circuit voltage (OCV), according to the battery鈥檚 intrinsic relationship between the SOC and the OCV for application in electric vehicles. Firstly an equivalent circuit model with n RC networks is employed modeling the polarization characteristic and the dynamic behavior of the lithium-ion battery, the corresponding equations are built to describe its electric behavior and a recursive function is deduced for the online identification of the OCV, which is implemented by a recursive least squares (RLS) algorithm with an optimal forgetting factor. The models with different RC networks are evaluated based on the terminal voltage comparisons between the model-based simulation and the experiment. Then the OCV-SOC lookup table is built based on the experimental data performed by a linear interpolation of the battery voltages at the same SOC during two consecutive discharge and charge cycles. Finally a verifying experiment is carried out based on nine Urban Dynamometer Driving Schedules. It indicates that the proposed method can ensure an acceptable accuracy of SOC estimation for online application with a maximum error being less than 5.0%.