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Differential Voltage Analysis and Patterns in Parallel-Connected Pairs of Imbalanced Cells

Authors :
Wong, Clement
Weng, Andrew
Pannala, Sravan
Choi, Jeesoon
Siegel, Jason B.
Stefanopoulou, Anna
Publication Year :
2024

Abstract

Diagnosing imbalances in capacity and resistance within parallel-connected cells in battery packs is critical for battery management and fault detection, but it is challenging given that individual currents flowing into each cell are often unmeasured. This work introduces a novel method useful for identifying imbalances in capacity and resistance within a pair of parallel-connected cells using only voltage and current measurements from the pair. Our method utilizes differential voltage analysis (DVA) when the pair is under constant current discharge and demonstrates that features of the pair's differential voltage curve (dV/dQ), namely its mid-to-high SOC dV/dQ peak's height and skewness, are sensitive to imbalances in capacity and resistance. We analyze and explain how and why these dV/dQ peak shape features change in response to these imbalances, highlighting that the underlying current imbalance dynamics resulting from these imbalances contribute to these changes. Ultimately, we demonstrate that dV/dQ peak shape features can identify the product of capacity imbalance and resistance imbalance, but cannot uniquely identify the imbalances. This work lays the groundwork for identifying imbalances in capacity and resistance in parallel-connected cell groups in battery packs, where commonly only a single current sensor is placed for each parallel cell group.<br />Comment: Accepted to American Control Conference (ACC), Toronto, Canada, July 2024

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2405.17754
Document Type :
Working Paper