DBSCAN-Based Thermal Runaway Diagnosis of Battery Systems for Electric Vehicles

Da Li, Zhaosheng Zhang, Peng Liu and Zhenpo Wang
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Da Li: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
Zhaosheng Zhang: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
Peng Liu: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
Zhenpo Wang: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China

Energies, 2019, vol. 12, issue 15, 1-15

Abstract: Battery system diagnosis and prognosis are essential for ensuring the safe operation of electric vehicles (EVs). This paper proposes a diagnosis method of thermal runaway for ternary lithium-ion battery systems based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering. Two-dimensional fault characteristics are first extracted according to battery voltage, and DBSCAN clustering is used to diagnose the potential thermal runaway cells (PTRC). The periodic risk assessing strategy is put forward to evaluate the fault risk of battery cells. The feasibility, reliability, stability, necessity, and robustness of the proposed algorithm are analyzed, and its effectiveness is verified based on datasets collected from real-world operating electric vehicles. The results show that the proposed method can accurately predict the locations of PTRC in the battery pack a few days before the thermal runaway occurrence.

Keywords: thermal runaway; lithium-ion batteries; electric vehicles; DBSCAN clustering; fault diagnosis; National Monitoring and Management Center for New Energy Vehicles (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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