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Fault Detection for Lithium-Ion Battery Using Smooth Variable Structure Filters
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DOI：10.1109/ACCESS.2024.3482193.png)
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摘要
En 中文
Batteries are prone to faults that may arise because of vibrations, deformations, collisions, or improper usage. These faults can be sorted into two main categories: internal and external faults. In this study, external battery faults, particularly sensor faults that affect the measurement of current and voltage, are investigated. This paper proposes a fault-detection strategy that is built on different variants of the Smooth Variable Structure Filter (SVSF) for the detection of such faults in a battery cell. SVSF is applied to estimate the State of Charge (SoC) and terminal voltage of the battery. A modified decision signal is calculated using the residual signals of the filters to detect faults using the Cumulative Sum (CUSUM) strategy. The performance of the SVSF is compared with that of the Extended Kalman Filter (EKF). The effectiveness of the proposed method is demonstrated for detecting and isolating different external faults in a wide range of fault scenarios. The proposed SVSF-based methods not only improve fault-detection accuracy but also significantly decrease the fault-detection time in some scenarios compared to EKF, which is a critical factor for safety.
Keyword:
Circuit faults
Batteries
Fault detection
Filtering algorithms
Integrated circuit modeling
Voltage measurement
Noise measurement
Mathematical models
Fault diagnosis
Trajectory
Cumulative sum
fault detection
filtering
sensor fault
smooth variable structure filter
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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