How battery capacities are correctly estimated considering latent short-circuit faults

Hongchang Cai, Xiaopeng Tang, Xin Lai, Yanan Wang, Xuebing Han, Minggao Ouyang and Yuejiu Zheng

Applied Energy, 2024, vol. 375, issue C, No S0306261924015733

Abstract: Capacity is a key factor in assessing battery health. Traditional capacity estimation methods assume by default the battery is in a normal state. When there is a latent short-circuit fault, the measured current deviates from the actual current flowing into or out of the battery unit, leading to errors in capacity estimation. To address this challenge, we have constructed an end-cloud collaborative framework to accurately estimate the module's capacity considering the latent short-circuit faults. The core scheme is to estimate the module's charging capacity and discharging capacity simultaneously, obtain the module's operating mode based on the historical relationship between the two, conduct quantitative diagnosis for the short-circuit fault, and feedback the accurate capacity value. This framework addresses the coupled issue of erroneous capacity estimation in the presence of latent short-circuit faults, and the inability to diagnose module external short-circuit faults due to the lack of a comparison. This has profound significance for achieving more reliable battery safety management.

Keywords: Capacity estimation; Short-circuit; Quantitative diagnosis; Battery module; End- cloud collaboration (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.124190

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