Sliding Mode Observer for State-of-Charge Estimation Using Hysteresis-Based Li-Ion Battery Model

被引:14
作者
Chen, Mengying [1 ]
Han, Fengling [1 ]
Shi, Long [2 ]
Feng, Yong [3 ]
Xue, Chen [3 ]
Gao, Weijie [4 ]
Xu, Jinzheng [5 ]
机构
[1] RMIT Univ, Sch Comp Technol, Melbourne, Vic 3000, Australia
[2] RMIT Univ, Sch Engn, Melbourne, Vic 3000, Australia
[3] Harbin Inst Technol, Sch Elect Engn, Harbin 150001, Peoples R China
[4] Beijing Intell Sun Technol Ltd, Beijing 100012, Peoples R China
[5] Anhui Huasun Energy Co Ltd, Res & Dev Ctr, Xuancheng 242000, Peoples R China
关键词
Lithium-ion battery; hysteresis; state-of-charge (SoC) estimation; terminal sliding mode observer; automatic monitoring system; Internet of Things (IoT); OPEN-CIRCUIT VOLTAGE; UNSCENTED KALMAN FILTER; PACK;
D O I
10.3390/en15072658
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion batteries is difficult to observe after batteries are manufactured. The hysteresis phenomenon influences the existing battery modeling and SoC estimation accuracy. This research applies a terminal sliding mode observer (TSMO) algorithm based on a hysteresis resistor-capacitor (RC) equivalent circuit model to enable accurate SoC estimation. The proposed method is evaluated using two dynamic battery tests: the dynamic street test (DST) and the federal urban driving schedule (FUDS) test. The simulation results show that the proposed method achieved high estimation accuracy and fast response speed. Additionally, real-time battery information, including battery output voltage and SoC, was acquired and displayed by an automatic monitoring system. The designed system is valuable for all battery application cases.
引用
收藏
页数:14
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