Phantom LAM and LLI: Resistance and Hysteresis Bias in Voltage-Curve Degradation Mode Analysis
Mohammed Asheruddin N, Matheus Leal De Souza, Thomas Holland, Catherine Folkson, Gregory Offer, Monica Marinescu

TL;DR
This paper investigates how voltage measurement artifacts, such as hysteresis and ohmic drops, can lead to false identification of material loss in battery degradation analysis, proposing correction methods for more accurate diagnostics.
Contribution
It introduces a correction protocol for voltage curves that accounts for ohmic drops and hysteresis, improving the accuracy of degradation mode attribution in lithium-ion batteries.
Findings
IR correction improves LAM and LLI estimation accuracy
Voltage window adjustments affect degradation component detection
Correcting ohmic drops reduces false attribution of material loss
Abstract
Degradation mode analysis (DMA) is widely used to decompose capacity fade into loss of lithium inventory (LLI) and loss of active material (LAM) from low-rate voltage-capacity data. Yet the measured trace is a pseudo-OCV (pOCV) that includes two non-degradation contributions: an SOC-dependent ohmic drop and intrinsic charge-discharge hysteresis, especially in graphite--silicon oxide (C/SiOx) negative electrodes. We show these can dominate attribution and generate Phantom LAM/LLI --apparent material loss created by curve registration, branch choice and voltage-windowing rather than true degradation. Using two commercial 21700 cells (LG M50T: higher resistance; Molicel P45B: lower resistance), we extract an SOC-dependent instantaneous resistance from the first 50,ms pulse step and apply an IR correction to pOCV before fitting. In LG M50T, IR correction lifts…
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Taxonomy
TopicsAdvancements in Battery Materials · Advanced Battery Technologies Research · Advanced Battery Materials and Technologies
