TY - GEN
T1 - Hysteresis Characteristics Analysis and SOC Estimation of Lithium Iron Phosphate Batteries Under Energy Storage Frequency Regulation Conditions and Automotive Dynamic Conditions
AU - Zhang, Zhihang
AU - Li, Yalun
AU - Chen, Siqi
AU - Han, Xuebing
AU - Lu, Languang
AU - Wang, Hewu
AU - Ouyang, Minggao
N1 - Publisher Copyright:
© 2023, Beijing Paike Culture Commu. Co., Ltd.
PY - 2023
Y1 - 2023
N2 - With the application of high-capacity lithium iron phosphate (LiFePO4) batteries in electric vehicles and energy storage stations, it is essential to estimate battery real-time state for management in real operations. LiFePO4 batteries demonstrate differences in open circuit voltage (OCV) under different charge and discharge paths, indicating the hysteresis phenomenon of OCV, which is more evident under energy storage frequency regulation conditions. Previous battery models ignored the hysteresis characteristics in the energy storage frequency regulation conditions, causing low accuracy in the state of charge (SOC) estimation. To accurately estimate the SOC of LiFePO4 batteries, a hysteresis voltage reconstruction model is developed to analyze the hysteresis characteristics of LiFePO4 batteries under automotive dynamic conditions and energy storage frequency regulation conditions. The accuracy of the hysteresis model is compared with the basic first-order RC equivalent circuit model. Furthermore, the SOC estimation based on the extended Kalman filter (EKF) method is achieved. Results indicate that the hysteresis model exhibits better accuracy for the hysteresis features, with an error of less than 1.5%, which is more appropriate for SOC estimation under energy storage conditions.
AB - With the application of high-capacity lithium iron phosphate (LiFePO4) batteries in electric vehicles and energy storage stations, it is essential to estimate battery real-time state for management in real operations. LiFePO4 batteries demonstrate differences in open circuit voltage (OCV) under different charge and discharge paths, indicating the hysteresis phenomenon of OCV, which is more evident under energy storage frequency regulation conditions. Previous battery models ignored the hysteresis characteristics in the energy storage frequency regulation conditions, causing low accuracy in the state of charge (SOC) estimation. To accurately estimate the SOC of LiFePO4 batteries, a hysteresis voltage reconstruction model is developed to analyze the hysteresis characteristics of LiFePO4 batteries under automotive dynamic conditions and energy storage frequency regulation conditions. The accuracy of the hysteresis model is compared with the basic first-order RC equivalent circuit model. Furthermore, the SOC estimation based on the extended Kalman filter (EKF) method is achieved. Results indicate that the hysteresis model exhibits better accuracy for the hysteresis features, with an error of less than 1.5%, which is more appropriate for SOC estimation under energy storage conditions.
KW - Frequency regulation working conditions
KW - Hysteresis characteristics
KW - Lithium iron phosphate battery
KW - State of charge
UR - https://www.scopus.com/pages/publications/85161204666
U2 - 10.1007/978-981-99-1027-4_132
DO - 10.1007/978-981-99-1027-4_132
M3 - 会议稿件
AN - SCOPUS:85161204666
SN - 9789819910267
T3 - Lecture Notes in Electrical Engineering
SP - 1266
EP - 1275
BT - The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022
A2 - Sun, Fengchun
A2 - Yang, Qingxin
A2 - Dahlquist, Erik
A2 - Xiong, Rui
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022
Y2 - 3 December 2022 through 4 December 2022
ER -