Experimental study investigates aging impacts on lithium-ion cell performance, indicating implications for battery management systems.
High-nickel NCA/Si–C 21700 cells exhibit strongly condition-dependent degradation, but the coupled influence of temperature and rate on electrochemical, thermal, and structural evolution remains insufficiently resolved. Here, Samsung INR21700-50E cells were aged under a 3 × 3 matrix of ambient temperatures (0, 23, and 40 °C) and C-rates (0.5C, 1C, and 2C). Periodic reference performance tests were used to track capacity, 10 s direct-current internal resistance, electrochemical impedance, pseudo-open-circuit voltage, differential voltage/incremental capacity behavior, heat generation, and post-mortem morphology. Guided by the hypothesis that temperature and rate history change not only the speed but also the dominant pathway of aging, the results show that both ambient temperature and the charge/discharge rate program govern the aging trajectory. Low-temperature cycling accelerates capacity loss and resistance growth through severe polarization and lithium plating, indicating dominant loss of lithium inventory. High-temperature operation promotes interfacial side reactions, impedance rise, and cathode structural degradation, leading to stronger loss of active material at later stages. An increasing C-rate amplifies these effects by raising overpotential and thermal load. Heat generation power increases markedly with aging and depends strongly on temperature–rate history. Scanning electron microscopy confirms cathode cracking, anode surface film thickening, and separator degradation under severe conditions. These experimental indicators are integrated into a mechanism-aware diagnostic framework that maps capacity retention, DCIR/EIS parameters, ICA/DVA indices, and heat generation metrics to dominant aging modes, supporting BMS state-of-health estimation, lifetime prediction, thermal management, and second-life screening of high-nickel NCA cells. The condition-averaged trajectories are further converted into a semi-empirical aging law that links capacity loss, resistance growth, and heat generation increase for BMS-oriented lifetime prediction.
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Huang et al. (2026) studied this question.
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