Understanding battery degradation is essential for accurate health diagnostics and long-term performance prediction. Degradation mode analysis (DMA), a non-destructive technique, leverages the voltage response, which reflects the cell’s thermodynamic equilibrium, to dissect aging mechanisms . Since DMA relies on accurate thermodynamic data, open circuit voltage (OCV) measurements provide the most suitable starting point for this analysis. However, obtaining true OCV requires extended rest periods or low charge rates, conditions that are achievable in controlled laboratory environments, but remain impractical in real-world applications. There are two challenges addressed by this study, Firstly, to approximate OCV under practical constraints, pseudo-OCV measurements taken at slightly higher C-rates are often used, though these introduce a resistance component that can distort the interpretation of degradation mechanisms . Secondly, hysteresis due to the SiOx component in the anode causes disparities between charge and discharge profiles that evolve differently with aging . Ideally, a cell without hysteresis would exhibit identical charge and discharge potentials under OCV, yielding consistent DMA results. However, hysteresis introduces deviations, particularly in cells with prolonged cycling.
This study addresses these challenges by quantifying the influence of resistance on DMA using cycle-aging experimental data from two commercially significant lithium-ion cells, LG M50T 21700 (an energy cell) and Molicel P45B (a power cell), both with NMC811 cathode and C/SiOx composite anode (notably higher silicon percentage in the Molicel). Cells are cycled across the full state-of-charge (SoC) window, with reference performance tests (including C/10 pseudo-OCV and resistance measurements) at defined charge throughput intervals.
Firstly, we explore how resistance affects voltage-based indicators of degradation in energy versus power cells. By performing DMA on the C/10 pseudo-OCV both with and without resistance correction, we isolate resistance’s impact on observed degradation modes. Secondly, we quantify the evolution of hysteresis with aging and assess its impact by separately analyzing charge- and discharge-based DMAs, a focus not explicitly addressed in prior research.
To identify diagnostic metrics minimally impacted by resistance and hysteresis, this analysis includes differential voltage and capacity diagnostics. Through rigorous quantification of these effects, the study establishes robust DMA procedures and provides recommendations tailored to both power and energy cells exhibiting hysteresis, enhancing the reliability of degradation assessments and extending the applicability of DMA to real-world battery health monitoring.

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