Open AccessModeling of Dynamic Hysteresis Characters for the Lithium-Ion Battery
Author(s) -
Yang He,
Rong He,
Bin Guo,
Zhengjie Zhang,
Shichun Yang,
Xinhua Liu,
Xichang Zhao,
Yuwei Pan,
Xiaoyu Yan,
Li Shen
Publication year - 2020
Publication title -
journal of the electrochemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.258
H-Index - 271
eISSN - 1945-7111
pISSN - 0013-4651
DOI - 10.1149/1945-7111/ab8b96
Subject(s) - voltage , hysteresis , estimator , robustness (evolution) , battery (electricity) , control theory (sociology) , lithium ion battery , state of charge , computer science , materials science , electrical engineering , engineering , chemistry , physics , mathematics , thermodynamics , biochemistry , statistics , power (physics) , control (management) , quantum mechanics , artificial intelligence , gene
The strategies of battery management system (BMS) rely heavily on sets of models to represent the lithium-ion batteries. However, the hysteresis voltage response of the batteries, which is mainly caused by the polarization of the electrodes, will inevitably have influence on the accuracy and real-time performance of the model’s SOC-OCV curve, more or less. In this work, a dynamic Prandtl–Ishlinskii model is established to present a certain magnitude of hysteresis regarding not only the major OCV boundaries but also the different minor loops of partial charge and discharge. The relationship between SOC and hysteresis behavior of the battery’s voltage is investigated through a self-designed pulsed-current test over a range of operating temperatures. Finally, the dynamic performance of the model is verified by the results obtained from the electric vehicle under dynamic driving cycle. The proposed model can significantly improve the accuracy of the model based SOC estimator as well as the robustness in terms of initial voltage error and current error.