Multi-scale short circuit resistance estimation method for series connected battery strings

Jun Xu, Haitao Wang, Hu Shi and Xuesong Mei

Energy, 2020, vol. 202, issue C

Abstract: Short circuit (SC) fault in battery systems is considered as one of the most severe problems, which may result in thermal runaway and fire. This paper tries to utilize the multi-scale technology to estimate the short circuit resistance to give a quantitative analysis of short circuit fault. With the value of the short circuit resistance, it is able to determine to light a warning or stop using the battery immediately. To solve this problem, the multi-scale short circuit resistance estimation method is proposed. Not only the hard short circuit with small resistance but also the soft short circuit with large resistance can be estimated accurately. Additionally, to reduce the computation complexity, only two battery cells in the battery string are needed for the estimation. The experimental test platform is established and different short circuit resistance is applied to the battery string. The results show that the fast estimation of hard short circuit resistance can be realized. Moreover, the soft short circuit resistance is able to be estimated accurately. The hard short circuit resistance can be estimated in 3 s and the estimation error standard deviation for the soft one is less than 4%.

Keywords: Short circuit; Multi-scale; Battery model; Hard short circuit; Soft short circuit; Model based (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:202:y:2020:i:c:s0360544220307544

DOI: 10.1016/j.energy.2020.117647

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