Online Cell Screening Algorithm for Maximum Peak Current Estimation of a Lithium-Ion Battery Pack for Electric Vehicles

Tae-Won Noh, Junghoon Ahn and Byoung Kuk Lee
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Tae-Won Noh: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea
Junghoon Ahn: Energy Convergence Research Center, Korea Electronics Technology Institute (KETI), Gwangju 61011, Korea
Byoung Kuk Lee: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea

Energies, 2022, vol. 15, issue 4, 1-14

Abstract: In this study, an online cell screening algorithm is proposed to estimate the maximum peak current considering the cell inconsistencies in battery packs for electric vehicles. Based on the equivalent circuit model, the maximum peak current is mathematically defined, and the inconsistency parameters affecting the maximum peak current are analyzed. The proposed algorithm compares the inconsistency parameters of each cell and subsequently selects a cell or a group of cells whose voltage can exceed the allowable voltage range. The maximum peak current is determined based on the selected cells, while ensuring that all the cells are charged and discharged within the allowable voltage range. The feasibility and superiority of the proposed algorithm are verified through an experiment conducted on a commercially manufactured battery pack for electric vehicles.

Keywords: battery management system; maximum peak current estimation; cell inconsistency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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