TY - JOUR
T1 - Online Fault Diagnosis of External Short Circuit for Lithium-Ion Battery Pack
AU - Xiong, Rui
AU - Yang, Ruixin
AU - Chen, Zeyu
AU - Shen, Weixiang
AU - Sun, Fengchun
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - Battery safety is one of the most crucial issues in the utilization of lithium-ion batteries (LiBs) for all-climate electric vehicles. Short circuit, overcharge, and overheat are three common field failures of LiBs. In this paper, online fault diagnosis for external short circuit (ESC) of LiB packs is investigated. The experiments are carried out to obtain and compare ESC characteristics of 18650-type NMC battery pack and single cell. Based on the analysis of experimental results, a two-step equivalent circuit model is established to describe the ESC process and an online model-based scheme is proposed to diagnose ESC faults of battery packs. The proposed scheme is evaluated by experimental data. The results show that it can effectively diagnose ESC faults in 3.5 s after their occurrences with the terminal voltage error less than 25 mV. The proposed scheme has shown great generalization ability. ESC faults of battery packs under different number of cells connected in series and unavailable current information can also be diagnosed at the terminal voltage error less than 48 and 60 mV, respectively.
AB - Battery safety is one of the most crucial issues in the utilization of lithium-ion batteries (LiBs) for all-climate electric vehicles. Short circuit, overcharge, and overheat are three common field failures of LiBs. In this paper, online fault diagnosis for external short circuit (ESC) of LiB packs is investigated. The experiments are carried out to obtain and compare ESC characteristics of 18650-type NMC battery pack and single cell. Based on the analysis of experimental results, a two-step equivalent circuit model is established to describe the ESC process and an online model-based scheme is proposed to diagnose ESC faults of battery packs. The proposed scheme is evaluated by experimental data. The results show that it can effectively diagnose ESC faults in 3.5 s after their occurrences with the terminal voltage error less than 25 mV. The proposed scheme has shown great generalization ability. ESC faults of battery packs under different number of cells connected in series and unavailable current information can also be diagnosed at the terminal voltage error less than 48 and 60 mV, respectively.
KW - All-climate electric vehicles
KW - battery safety
KW - external short circuit (ESC)
KW - fault diagnosis
KW - genetic algorithm (GA)
KW - lithium-ion battery (LiB)
UR - http://www.scopus.com/inward/record.url?scp=85073051712&partnerID=8YFLogxK
U2 - 10.1109/TIE.2019.2899565
DO - 10.1109/TIE.2019.2899565
M3 - Article
AN - SCOPUS:85073051712
SN - 0278-0046
VL - 67
SP - 1081
EP - 1091
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 2
M1 - 8648476
ER -
