Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

Peng Liu, Zhenyu Sun, Zhenpo Wang and Jin Zhang
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Peng Liu: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
Zhenyu Sun: 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
Jin Zhang: National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China

Energies, 2018, vol. 11, issue 1, 1-15

Abstract: The battery is a key component and the major fault source in electric vehicles (EVs). Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV) in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.

Keywords: over-voltage; fault diagnosis; Li-ion batteries; entropy method (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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