On Generalized Auto-Spectral Coherence Function and Its Applications to Signal Detection

Zheng, Chengshi; Yang, Hefei; Li, Xiaodong

doi:10.1109/lsp.2014.2310772

Cited by 11 publications

(1 citation statement)

References 15 publications

(33 reference statements)

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“…Such approach is widely used in system identification or in determining the cause-effect relationship of a system with its applications [32], [33]. In this work, a function based on magnitude of squared coherence spectrum was employed to determine the fault status of a battery system at its outputs.…”

Section: Residual Evaluationmentioning

confidence: 99%

Health Monitoring of Li-Ion Battery Systems: A Median Expectation Diagnosis Approach (MEDA)

Khalid¹,

Ahmed

Peng³

2015

IEEE Trans. Transp. Electrific.

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The operations of Li-ion battery management system (BMS) are highly dependent on installed sensors. Malfunctions in sensors could lead to a deterioration in battery performance. This paper proposed an effective health monitoring scheme using a median expectation-based diagnosis approach (MEDA). MEDA calculates the median of a possible set of values, rather than taking their weighted average as in the case of a standard expected mean operator. Furthermore, a smoother was developed to capture important patterns in the estimation. The resulting filter was first derived using an one-dimensional (1-D) system example, where the iterative convergence of median-based proposed filter was proved. Performance evaluations were subsequently conducted by analyzing real-time measurements collected from Li-ion battery cells used in hybrid electric vehicles (HEV) and plug-in HEVs (PHEV) duty cycles. Results showed that the proposed filter was more effective and less sensitive to small sample size and curves with outliers.

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Section: Residual Evaluationmentioning

confidence: 99%