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This paper introduces MagBridge-Battery, a synthetic dataset of 6,760 magnetic-field signatures for Li-ion battery state-of-health diagnostics, combining real magnetic morphology with real degradation labels to bridge the gap in public magnetic-sensing battery data.
This paper introduces C2L-Net, a data-driven model for efficient and accurate state-of-charge estimation of lithium-ion batteries using short historical windows.