Fault diagnosis of lithium-ion batteries based on voltage dip behavior

ABSTRACT

In recent years, the safety accidents of new energy electric vehicles have been increasing due to the failure of lithium-ion batteries. The lithium-ion battery fault diagnosis technology is critical to ensure the safe operation of electric vehicles. In this paper, we proposes a lithium-ion battery fault diagnosis method based on voltage dip behavior. The method first uses the Sparrow Search Algorithm(SSA) to optimize the Variational Modal Decomposition(VMD), then reconstructs multiple dynamic components and extracts the multi-feature parameters of the reconstructed components, and finally uses SSA to optimize Density Based Spatial Clustering of Applications with Noise(DBSCAN) for fault diagnosis. Through verification with real vehicle data and experimental data at different temperatures, this method can be applied to the operating environment of real vehicles at different temperatures, and can quickly and accurately identify abnormal cells.

KEYWORDS:

• Lithium-ion battery
• voltage dip
• fault diagnosis
• real vehicle data
• different temperatures

Acknowledgements

This work is supported by Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System (HBSEES202204).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributors

Jiuchun Jiang was born in Jilin, China. He received the B.S. degree in electrical engineering and the Ph.D. degree in power system automation from Northern Jiaotong University, Beijing, China, in 1993 and 1999, respectively. He was a Professor with the School of Electrical Engineering, Beijing Jiaotong University, Beijing, until 2018. He is currently a professor at Hubei University of technology, Wuhan. His research interests include battery application technology, electric car charging stations, and microgrid technology. He was the recipient of the National Science and Technology Progress 2nd Award for his work on electric vehicle (EV) bus systems, and the Beijing Science and Technology Progress 2ndAward for his work on EV charging systems.

Additional information

Funding

The work was supported by the Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System [HBSEES202004].