Fault diagnosis technology overview for lithium-ion battery energy storage station

被引：1
作者：
Li, Bin [1 ]
Chen, Peiyu [1 ,2 ]
Li, Guanzheng [1 ]
Li, Chao [1 ]
Zeng, Kaidi [1 ]
Liu, Bin [1 ,3 ]
Li, Xuebin [4 ]
Huo, Qidi [1 ,5 ]
Jiao, Kui [1 ]
Wang, Chengshan [1 ]
机构：
[1] Tianjin Univ, Natl Ind Educ Platform Energy Storage, Tianjin, Peoples R China
[2] State Grid Tianjin Elect Power Co, Elect Power Res Inst, Tianjin, Peoples R China
[3] Beijing Sifang Automat Co Ltd, Beijing, Peoples R China
[4] China Energy Engn Grp, Tianjin Elect Power Design Inst, Tianjin, Peoples R China
[5] China Elect Power Res Inst, State Key Lab Grid Secur & Energy Conservat, Beijing, Peoples R China
来源：
IET ENERGY SYSTEMS INTEGRATION | 2024年 / 6卷
关键词：
battery storage plants; fault diagnosis; INTERNAL TEMPERATURE ESTIMATION; EXTERNAL SHORT-CIRCUIT; PACKS; IMPEDANCE;
D O I：
10.1049/esi2.12166
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：
With an increasing number of lithium-ion battery (LIB) energy storage station being built globally, safety accidents occur frequently. Diagnosing faults accurately and quickly can effectively avoid safe accidents. However, few studies have provided a detailed summary of lithium-ion battery energy storage station fault diagnosis methods. In this paper, an overview of topologies, protection equipment, data acquisition and data transmission systems is firstly presented, which is related to the safety of the LIB energy storage power station. Then, existing fault diagnosis technologies are reviewed in detail. Finally, the future developing trends of fault diagnosis technology are discussed.
引用
收藏
页码：684 / 701
页数：18
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[61]   Online Fault Diagnosis of External Short Circuit for Lithium-Ion Battery Pack [J].
Xiong, Rui ;
Yang, Ruixin ;
Chen, Zeyu ;
Shen, Weixiang ;
Sun, Fengchun .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (02) :1081-1091
[62]   A fast diagnosis method for accelerated degradation fault induced by overcharging of LiFePO4 batteries [J].
Xu, Jianing ;
Ni, Yulong ;
Cao, Tianao ;
Wu, Chao ;
Song, Kai ;
Jiang, Jinhai .
JOURNAL OF ENERGY STORAGE, 2022, 46
[63]   A Soft Short-Circuit Diagnosis Method for Lithium-Ion Battery Packs in Electric Vehicles [J].
Xu, Yiming ;
Ge, Xiaohua ;
Shen, Weixiang ;
Yang, Ruixin .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2022, 37 (07) :8572-8581
[64]   Fault diagnosis and abnormality detection of lithium-ion battery packs based on statistical distribution [J].
Xue, Qiao ;
Li, Guang ;
Zhang, Yuanjian ;
Shen, Shiquan ;
Chen, Zheng ;
Liu, Yonggang .
JOURNAL OF POWER SOURCES, 2021, 482
[65]   On-board Diagnosis of Soft Short Circuit Fault in Lithium-ion Battery Packs for Electric Vehicles Using an Extended Kalman Filter [J].
Yang, Ruixin ;
Xiong, Rui ;
Shen, Weixiang .
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2022, 8 (01) :258-270
[66]   Extreme Learning Machine-Based Thermal Model for Lithium-Ion Batteries of Electric Vehicles under External Short Circuit [J].
Yang, Ruixin ;
Xiong, Rui ;
Shen, Weixiang ;
Lin, Xinfan .
ENGINEERING, 2021, 7 (03) :395-405
[67]   Characterization of external short circuit faults in electric vehicle Li-ion battery packs and prediction using artificial neural networks [J].
Yang, Ruixin ;
Xiong, Rui ;
Ma, Suxiao ;
Lin, Xinfan .
APPLIED ENERGY, 2020, 260
[68]   A fractional-order model-based battery external short circuit fault diagnosis approach for all-climate electric vehicles application [J].
Yang, Ruixin ;
Xiong, Rui ;
He, Hongwen ;
Chen, Zeyu .
JOURNAL OF CLEANER PRODUCTION, 2018, 187 :950-959
[69]   Multi-fault diagnosis for battery pack based on adaptive correlation sequence and sparse classification model [J].
Yang, Yipin ;
Lun, Shuxian ;
Xie, Jiale .
JOURNAL OF ENERGY STORAGE, 2022, 46
[70]   Sensing as the key to the safety and sustainability of new energy storage devices [J].
Yi, Zhenxiao ;
Chen, Zhaoliang ;
Yin, Kai ;
Wang, Licheng ;
Wang, Kai .
PROTECTION AND CONTROL OF MODERN POWER SYSTEMS, 2023, 8 (01)
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