A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature

Ruifeng Zhang, Bizhong Xia, Baohua Li, Libo Cao, Yongzhi Lai, Weiwei Zheng, Huawen Wang, Wei Wang and Mingwang Wang
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Ruifeng Zhang: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Bizhong Xia: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Baohua Li: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Libo Cao: College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Yongzhi Lai: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Weiwei Zheng: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Huawen Wang: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Wei Wang: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Mingwang Wang: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China

Energies, 2018, vol. 11, issue 9, 1-17

Abstract: Open circuit voltage (OCV) is an important characteristic parameter of lithium-ion batteries, which is used to analyze the changes of electronic energy in electrode materials, and to estimate battery state of charge (SOC) and manage the battery pack. Therefore, accurate OCV modeling is a great significance for lithium-ion battery management. In this paper, the characteristics of high-capacity lithium-ion batteries at different temperatures were considered, and the OCV-SOC characteristic curves at different temperatures were studied by modeling, exponential, polynomial, sum of sin functions, and Gaussian model fitting method with pulse test data. The parameters of fitting OCV-SOC curves by exponential model (n = 2), polynomial model (n = 3~7), sum of sin functions model (n = 3), and Gaussian model (n = 4) at temperatures of 45 °C, 25 °C, 0 °C, and −20°C are obtained, and the errors are analyzed. The experimental results show that the operating temperature of the battery influences the OCV-SOC characteristic significantly. Therefore, these factors need to be considered in order to increase the accuracy of the model and improve the accuracy of battery state estimation.

Keywords: lithium-ion battery; high capacity; polynomial fitting; OCV-SOC characteristics; sate of charge estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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