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Lithium-ion batteries fault diagnostic for electric vehicles using sample entropy analysis method
عیب یابی باتری های لیتیوم یون برای وسایل نقلیه الکتریکی با استفاده از روش تجزیه و تحلیل آنتروپی نمونه-2020 Fault detection plays a vital role in the operation of lithium-ion batteries in electric vehicles. Typically, during
the operation of battery systems, voltage signals are susceptible to noise interference. In this paper, a novel fault
detection method based on the Empirical Mode Decomposition and Sample Entropy is proposed to identify
battery faults under various operating conditions. Firstly, effective fault features are extracted through the
proposed Empirical Mode Decomposition method by decomposing battery voltage signals and removing the
noise interference during the voltage sampling process. Experiments are conducted to quantitatively illustrate
the fault features extracted by the Empirical Mode Decomposition. Then, based on these extracted fault features,
the Sample Entropy values are calculated to help accurately detect and locate the battery faults. Moreover, an
evaluation strategy of the detected faults is designed to indicate the battery fault level. Finally, the effectiveness
of the proposed approach is verified against real-world data measured from electric vehicles in the presence of
regular and sudden faults. Keywords: Electric vehicles | Lithium-ion batteries | Fault detection | Sample entropy |
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