Deciphering the Degradation Mechanisms of Cycle Life in Ternary Lithium-Ion Batteries from the Electrode State Perspective
Yang Sijia1,2, Zhang Caiping3, Yuan Zhaolin1,2, Zhang Linjing3, Zhang Weige3
1. School of Artifical Intelligence University of Science and Technology Beijing Beijing 100083 China; 2. Shunde Innovation School University of Science and Technology Beijing Foshan 528399 China; 3. National Active Distribution Network Technology Research Center Beijing Jiaotong University Beijing 100044 China
Abstract：Lithium-ion (Li-ion) batteries are the core components in electrical energy storage systems (ESSs), yet their inevitable performance degradation directly impacts system lifespan and safety. During the operation of ESSs, the state of charge (SOC) of Li-ion batteries often operates over fragmented intervals that fluctuate frequently in response to frequency regulation, peak shaving, and renewable energy accommodation. This gives rise to cell-to-cell inconsistencies, triggering divergent degradation modes and accelerating the deterioration of pack-level performance—making it challenging to accurately predict service life or optimize operating strategies. To address these issues, two representative nickel-cobalt-manganese (NCM) cells—an energy-type 114 A·h cell and a power-type 8 A·h cell—were selected for degradation experiments, as they encompass the typical application requirements of ESSs. To decipher the degradation mechanisms of any part of the SOC range within the 0%~100% SOC interval on battery aging, the full SOC interval (0%~100%) was divided into five non-overlapping subintervals (0%~20%, 20%~40%, 40%~60%, 60%~80%, and 80%~100%), each corresponding to a 20% depth of discharge, with the full SOC interval serving as a reference. Room-temperature cycling experiments were conducted under these defined SOC intervals, with periodic performance calibration tests to monitor changes in key electrochemical parameters such as capacity, open circuit voltage and internal resistance. The evolution of capacity and resistance of two NCM batteries was first analyzed. Both battery types exhibited more pronounced increases in polarization resistance when cycled within the 0%~20% SOC interval and the 0%~100% SOC interval relative to other subintervals. Specifically, the energy cell showed a more substantial increase than the power cell, indicating that cycling in low SOC exacerbates kinetic loss. On the other hand, thermodynamic loss, characterized by a decline in maximum available capacity, emerged as the dominant factor governing overall state of health (SOH) degradation, accounting for over 80% of total SOH degradation across all SOC intervals. Notably, the two battery types displayed distinct degradation patterns: the energy cell underwent accelerated capacity loss in the 0%~20% SOC interval after 400 equivalent cycles, even exceeding the degradation rate in the full 0%~100% SOC interval; in contrast, the power cell exhibited the most severe degradation in the 80%~100% SOC interval, with the 0%~20% interval showing the least degradation. To untangle the intricate interplay between external characteristics and internal degradation physics, the root causes of these behaviors were further elucidated from an electrode-state-centric perspective. Quantitative diagnosis of aging modes combined with electrode material expansion analysis was performed. The results revealed that lithium inventory loss dominated in linearly degrading cells, whereas the dominant aging mode transitioned to negative electrode active material loss once the negative electrode became the limiting electrode—precipitating an abrupt acceleration in capacity fade. More importantly, due to differences in negative-to-positive ratios, the same SOC interval translated into markedly different graphite lithiation ranges for the two cell designs, inducing varying extents of phase transitions and mechanical stress. This explains why the most significant fade in linear degradation was observed in the 60%~80% SOC interval for the energy cell and in the 80%~100% SOC interval for the power cell. In summary, this study underscores the inadequacy of traditional degradation evaluation metrics that overlook electrode-level states. Electrode-state diagnostics enables the optimization of operating SOC windows tailored to specific cell chemistries and designs. The aging mode of the full cell, the electrode state reflected by the cycling range, and the degree of electrode expansion together determine the thermodynamic degradation characteristics under SOC range stress. When optimizing the battery operating range, a specific analysis should be conducted in combination with the electrode state to avoid having the full cell work for a long time in the SOC range where the graphite has a low potential and a high degree of expansion. These findings contribute to a more precise and proactive approach to smart battery management, ultimately supporting the reliable and efficient operation of ESSs. Future work will extend electrode-state diagnostics to other operating conditions and high-nickel ternary chemistries.
杨思嘉, 张彩萍, 袁兆麟, 张琳静, 张维戈. 基于电极状态的三元锂离子电池循环寿命衰退机制解析[J]. 电工技术学报, 2026, 41(15): 5345-5358.
Yang Sijia, Zhang Caiping, Yuan Zhaolin, Zhang Linjing, Zhang Weige. Deciphering the Degradation Mechanisms of Cycle Life in Ternary Lithium-Ion Batteries from the Electrode State Perspective. Transactions of China Electrotechnical Society, 2026, 41(15): 5345-5358.
[1] 马敬轩, 赖铱麟, 吕娜伟, 等. 锂离子电池智能传感监测及预警技术[J]. 电工技术学报, 2025, 40(3): 941-963. Ma Jingxuan, Lai Yilin, Lü Nawei, et al.Lithium-ion battery intelligent sensing monitoring and early warning technology[J]. Transactions of China Electrotechnical Society, 2025, 40(3): 941-963. [2] 国务院. 2030年前碳达峰行动方案[R]. 2021. [3] 张彩萍, 乔波, 张琳静, 等. 宽温域无钴锂离子电池电化学建模及参数灵敏度研究[J]. 电工技术学报, 2025, 40(17): 5652-5666. Zhang Caiping, Qiao Bo, Zhang Linjing, et al.Research on electrochemical modeling and parameter sensitivity of cobalt-free lithium-ion battery with wide temperature range[J]. Transactions of China Electrotechnical Society, 2025, 40(17): 5652-5666. [4] 柳杨, 张彩萍, 姜久春, 等. 锂离子电池组容量差异辨识方法研究[J]. 中国电机工程学报, 2021, 41(4): 1422-1430. Liu Yang, Zhang Caiping, Jiang Jiuchun, et al.Research on capacity difference identification method of lithium-ion battery pack[J]. Proceedings of the CSEE, 2021, 41(4): 1422-1430. [5] Yang Sijia, Zhang Caiping, Jiang Jiuchun, et al.Review on state-of-health of lithium-ion batteries: characterizations, estimations and applications[J]. Journal of Cleaner Production, 2021, 314: 128015. [6] 张广续, 魏学哲, 陈思琦, 等. 高温循环老化对锂离子电池安全性影响研究[J]. 机械工程学报, 2023, 59(22): 33-45. Zhang Guangxu, Wei Xuezhe, Chen Siqi, et al.Research on the impact of high-temperature cyclic aging on the safety of lithium-ion batteries[J]. Journal of Mechanical Engineering, 2023, 59(22): 33-45. [7] Zhang Linjing, Zhang Caiping, Li Ning, et al.Influence of charge cutoff voltage on the cycling behavior of LiNi0.5Mn0.3Co0.2O2Cathode[J]. Journal of the Electrochemical Society, 2020, 167(12): 120509. [8] 王绥军, 胡晨, 孙召琴, 等. 电流过载工况下三元锂离子电池性能衰退机制[J]. 中国电机工程学报, 2023, 43(20): 7940-7947. Wang Suijun, Hu Chen, Sun Zhaoqin, et al.Performance degradation mechanism of ternary lithium batteries under current overload[J]. Proceedings of the CSEE, 2023, 43(20): 7940-7947. [9] Zhu Jiangong, Wang Yixiu, Huang Yuan, et al.Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation[J]. Nature Comm-unications, 2022, 13: 2261. [10] Ecker M, Nieto N, Käbitz S, et al.Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries[J]. Journal of Power Sources, 2014, 248: 839-851. [11] Heyer G, D'Arpino M, Rizzoni G. Performance metrics for the comparison of lithium ion cell aging experiments[J]. Energy Reviews, 2023, 2(2): 100025. [12] 高洋. 三元材料锂离子电池老化诊断、评估与建模方法[D]. 北京: 北京交通大学, 2019. Gao Yang.Aging diagnosis, evaluation and modeling of lithium ion batteries with Li(NiMnCo)O2 cathode[D]. Beijing: Beijing Jiaotong University, 2019. [13] Saxena S, Hendricks C, Pecht M.Cycle life testing and modeling of graphite/LiCoO2 cells under different state of charge ranges[J]. Journal of Power Sources, 2016, 327: 394-400. [14] de Hoog J, Timmermans J M, Ioan-Stroe D, et al. Combined cycling and calendar capacity fade modeling of a Nickel-manganese-cobalt oxide cell with real-life profile validation[J]. Applied Energy, 2017, 200: 47-61. [15] Preger Y, Barkholtz H M, Fresquez A, et al.Degradation of commercial lithium-ion cells as a function of chemistry and cycling conditions[J]. Journal of the Electrochemical Society, 2020, 167(12): 120532. [16] Zhu Jiangong, Knapp M, Sørensen D R, et al.Investigation of capacity fade for 18650-type lithium-ion batteries cycled in different state of charge (SoC) ranges[J]. Journal of Power Sources, 2021, 489: 229422. [17] 李守涛. 三元电池在储能应用下衰退机理分析[D]. 北京: 北京化工大学, 2020. Li Shoutao.Study on fading mechanismsfor lithium-ion batteries at energy storage systems[D]. Beijing: Beijing University of Chemical Technology, 2020. [18] 郭飞, 雍培, 刘欣宇, 等. 考虑状态相依老化特性的电池储能参与调峰投资效益评估[J]. 电工技术学报, 2025, 40(13): 4330-4342. Guo Fei, Yong Pei, Liu Xinyu, et al.Evaluating the investment benefits of battery energy storage participating in peak shaving considering the state-dependent aging characteristics[J]. Transactions of China Electrotechnical Society, 2025, 40(13): 4330-4342. [19] Barelli L, Bidini G, Ciupageanu D A, et al.Integrating hybrid energy storage system on a wind generator to enhance grid safety and stability: a levelized cost of electricity analysis[J]. Journal of Energy Storage, 2021, 34: 102050. [20] Xu Wanwan, Cao Huiying, Lin Xingyu, et al.Data-driven semi-empirical model approximation method for capacity degradation of retired lithium-ion battery considering SOC range[J]. Applied Sciences, 2023, 13(21): 11943. [21] Wei Yifan, Yao Yuan, Pang Kang, et al.A comprehensive study of degradation characteristics and mechanisms of commercial Li(NiMnCo)O2 EV batteries under vehicle-to-grid (V2G) services[J]. Batteries, 2022, 8(10): 188. [22] Geslin A, Xu Le, Ganapathi D, et al.Dynamic cycling enhances battery lifetime[J]. Nature Energy, 2025, 10(2): 172-180. [23] Dubarry M, Truchot C, Liaw B Y.Synthesize battery degradation modes via a diagnostic and prognostic model[J]. Journal of Power Sources, 2012, 219: 204-216. [24] 韩雪冰. 车用锂离子电池机理模型与状态估计研究[D]. 北京: 清华大学, 2014. Han Xuebing.Study on Li-ion battery mechanism model and state estimation for electric vehicles[D]. Beijing: Tsinghua University, 2014. [25] Gao Yang, Yang Sijia, Jiang Jiuchun, et al.The mechanism and characterization of accelerated capacity deterioration for lithium-ion battery with Li(NiMnCo) O2 cathode[J]. Journal of the Electro-chemical Society, 2019, 166(8): A1623-A1635. [26] Yang Sijia, Zhang Caiping, Jiang Jiuchun, et al.A voltage reconstruction model based on partial charging curve for state-of-health estimation of lithium-ion batteries[J]. Journal of Energy Storage, 2021, 35: 102271. [27] 王睿茜, 周星, 王羽, 等. 基于微分曲线的锂离子电池老化诊断研究综述[J]. 中国电机工程学报, 2024, 44(22): 8920-8935. Wang Ruiqian, Zhou Xing, Wang Yu, et al.A review of degradation diagnosis of lithium-ion batteries based on differential curves[J]. Proceedings of the CSEE, 2024, 44(22): 8920-8935. [28] Ohzuku T, Iwakoshi Y, Sawai K.Formation of lithium-graphite intercalation compounds in nonaqueous electrolytes and their application as a negative electrode for a lithium ion (shuttlecock) cell[J]. Journal of the Electrochemical Society, 1993, 140(9): 2490-2498. [29] Lewerenz M, Münnix J, Schmalstieg J, et al.Systematic aging of commercial LiFePO4|Graphite cylindrical cells including a theory explaining rise of capacity during aging[J]. Journal of Power Sources, 2017, 345: 254-263. [30] Edge J S, O'Kane S, Prosser R, et al. Lithium ion battery degradation: what you need to know[J]. Physical Chemistry Chemical Physics, 2021, 23(14): 8200-8221. [31] Reniers J M, Mulder G, Howey D A.Review and performance comparison of mechanical-chemical degradation models for lithium-ion batteries[J]. Journal of the Electrochemical Society, 2019, 166(14): A3189-A3200. [32] Hahn M, Buqa H, Ruch P W, et al.A dilatometric study of lithium intercalation into powder-type graphite electrodes[J]. Electrochemical and Solid-State Letters, 2008, 11(9): A151. [33] Jeon D H, Kim S, Hempelmann R.State-of-the-art review of degradation mechanisms of commercial lithium-ion batteries[J]. Journal of Power Sources, 2025, 646: 237242. [34] Han Xuebing, Lu Languang, Zheng Yuejiu, et al.A review on the key issues of the lithium ion battery degradation among the whole life cycle[J]. eTransportation, 2019, 1: 100005. [35] Han Xuebing, Ouyang Minggao, Lu Languang, et al.A comparative study of commercial lithium ion battery cycle life in electrical vehicle: aging mechanism identification[J]. Journal of Power Sources, 2014, 251: 38-54. [36] 孔纯, 朱国荣, 魏学良, 等. 考虑固相扩散诱导应力的锂离子电池电极颗粒破裂机理研究[J]. 电工技术学报, 2025, 40(5): 1672-1684. Kong Chun, Zhu Guorong, Wei Xueliang, et al.Research on lithium-ion battery electrode particles cracking mechanism considering solid-phase diffusion-induced stress[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1672-1684. [37] 孙丙香, 任鹏博, 陈育哲, 等. 锂离子电池在不同区间下的衰退影响因素分析及任意区间的老化趋势预测[J]. 电工技术学报, 2021, 36(3): 666-674. Sun Bingxiang, Ren Pengbo, Chen Yuzhe, et al.Analysis of influencing factors of degradation under different interval stress and prediction of aging trend in any interval for lithium-ion battery[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 666-674.
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