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Research on parameter identification and state of charge estimation of improved equivalent circuit model of Li-ion battery based on temperature effects for battery thermal management
Authors:YuTao Huo  Wen Hu  Zhe Li  Zhonghao Rao
Affiliation:1. Laboratory of Energy Storage and Heat Transfer, School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China

Jiangsu Province Engineering Laboratory of High Efficient Energy Storage Technology and Equipments, China University of Mining and Technology, Xuzhou, China

State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China;2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China;3. Laboratory of Energy Storage and Heat Transfer, School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, China

Abstract:The performance and parameters of Li-ion battery are greatly affected by temperature. As a significant battery parameter, state of charge (SOC) is affected by temperature during the estimation process. In this paper, an improved equivalent circuit model (IECM) considering the influence of ambient temperatures and battery surface temperature (BST) on battery parameters based on second-order RC model have been proposed. The exponential function fitting (EFF) method was used to identify battery model parameters at 5 ambient temperatures including ?10°C, 0°C, 10°C, 25°C and 40°C, fitting the relationship between internal resistance and BST. Then, the SOC of the IECM was estimated based on the extended Kalman filter (EKF) algorithm. Using the result calculated by the Ampere-hour integration method as the standard, the data of battery under open circuit voltage (OCV) test profile and dynamic stress test (DST) profile at different ambient temperatures has been compared with the ordinary second-order RC model, and the advantages of the SOC estimation accuracy with IECM was verified. The numerical results showed that the IECM can improve the estimation accuracy of battery SOC under different operating conditions.
Keywords:Li-ion battery  parameter identification  state of charge  temperature
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