Lithium-ion battery state of health monitoring based on an adaptive variable fractional order multivariate grey model

Zhicun Xu, Naiming Xie and Huakang Diao

Energy, 2023, vol. 283, issue C

Abstract: Accurate assessment of the state of health of lithium-ion batteries using relevant factors is crucial for the maintenance of lithium-ion batteries in electric vehicles. Firstly, data features are extracted from University of Maryland public dataset and dataset is pre-processed. Secondly, the extracted features were analysed using a grey relational analysis model to identify the most significant factors affecting the state of health. Thirdly, this paper proposed an adaptive variable fractional order multivariate grey prediction model to accurately estimate the state of health of lithium-ion batteries. The comparative results demonstrate the overall superiority of the proposed model.

Keywords: Lithium-ion batteries; State of health; Grey model; Multiple variables (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:283:y:2023:i:c:s0360544223025616

DOI: 10.1016/j.energy.2023.129167

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