RESEARCH ON SCREENING METHOD OF RETIRED POWER BATTERY MODULE BASED ON SOP DYNAMIC CONSISTENCY

Yan Ning; Zhong Yao; Li Xiangjun; Li Yang; Yao Qingye; Ma Shaohua

doi:10.19912/j.0254-0096.tynxb.2022-1653

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (2) : 274-282. DOI: 10.19912/j.0254-0096.tynxb.2022-1653

RESEARCH ON SCREENING METHOD OF RETIRED POWER BATTERY MODULE BASED ON SOP DYNAMIC CONSISTENCY

Yan Ning¹, Zhong Yao¹, Li Xiangjun², Li Yang³, Yao Qingye³, Ma Shaohua¹

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Abstract

Aiming at the problem of inconsistent initial characteristic parameters of retired batteries and poor screening effect of battery modules under multiple influencing factors, a method for condition evaluation and screening of battery modules based on SOP dynamic consistency is proposed. Firstly, in order to effectively characterize the initial characteristics of retired power batteries during echelon utilization screening, it selects the terminal voltage, capacity and internal resistance as static screening parameters, and an improved K-means clustering static screening method based on density is proposed. Secondly, single cells with good consistency are selected from the initial screening results, the characteristic relationships between voltage, state of charge （SOC）, state of health （SOH） and state of power （SOP）are established, and SOP characteristics of retired power batteries are estimated. Finally, the retired batteries with the same power state after static screening are connected in series into groups, the relationship between SOP and battery module life loss is established, and retired power battery modules based on SOP dynamic consistency is screened. The validity of the proposed screening method is verified by simulation analysis, which can effectively prolong the service life of decommissioned batteries.

Key words

battery modules / state of powe / battery / dynamic consistency / static and dynamic screening / life loss

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Yan Ning, Zhong Yao, Li Xiangjun, Li Yang, Yao Qingye, Ma Shaohua. RESEARCH ON SCREENING METHOD OF RETIRED POWER BATTERY MODULE BASED ON SOP DYNAMIC CONSISTENCY[J]. Acta Energiae Solaris Sinica. 2024, 45(2): 274-282 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1653

References

[1] 李建林, 李雅欣, 吕超, 等. 退役动力电池梯次利用关键技术及现状分析[J]. 电力系统自动化, 2020, 44(13): 172-183.
LI J L, LI Y X, LYU C, et al.Key technology and research status of cascaded utilization in decommissioned power battery[J]. Automation of electric power systems, 2020, 44(13): 172-183.
[2] 赵伟, 闵婕, 李章溢, 等. 基于一致性模型的梯次利用锂离子电池组能量利用率估计方法[J]. 电工技术学报, 2021, 36(10): 2190-2198.
ZHAO W, MIN J, LI Z Y, et al.Energy utilization efficiency estimation method for second-use lithium-ion battery packs based on a battery consistency model[J]. Transactions of China Electrotechnical Society, 2021, 36(10): 2190-2198.
[3] 李笑竹, 陈来军, 杜锡力, 等. 考虑退役动力电池衰减特性的新能源场站群共享储能长期规划配置[J]. 太阳能学报, 2022, 43(5): 499-509.
LI X Z, CHEN L J, DU X L, et al.Study on long-term planning of shared energy storage at power generation considering attenuation characteristics of retired power batteries[J]. Acta energiae solaris sinica, 2022, 43(5): 499-509.
[4] 李建林, 李雅欣, 吕超, 等. 碳中和目标下退役电池筛选聚类关键技术研究[J]. 电网技术, 2022, 46(2): 429-441.
LI J L, LI Y X, LYU C, et al.Key technology of retired batteries’ screening and clustering under target of carbon neutrality[J]. Power system technology, 2022, 46(2): 429-441.
[5] 郑焕坤, 曾凡斐, 傅钰, 等. 基于E-C-K-均值聚类和SOP优化的分布式电源双层规划[J]. 太阳能学报, 2022, 43(2): 127-135.
ZHENG H K, ZENG F F, FU Y, et al.Bi-level distributed power planning based on E-C-K-means clustering and SOP optimization[J]. Acta energiae solaris sinica, 2022, 43(2): 127-135.
[6] 马速良, 李建林, 李雅欣, 等. 面向电池梯次利用筛选需求的定制化聚类优化方法[J]. 中国电机工程学报, 2022, 42(17): 6208-6220.
MA S L, LI J L, LI Y X, et al.Customized clustering optimization method for battery reutilization screening requirements[J]. Proceedings of the CSEE, 2022, 42(17): 6208-6220.
[7] 颜宁, 李相俊, 钟瑶, 等. 基于静动态一致性的退役动力电池模组阶梯式筛选方法[J]. 中国电机工程学报, 2023, 43(5): 2060-2070.
YAN N, LI X J, ZHONG Y, et al.Stepwise screening method for retired power battery modules based on static-dynamic consistency[J]. Proceedings of the CSEE, 2023, 43(5): 2060-2070.
[8] 郑岳久, 李家琦, 朱志伟, 等. 基于快速充电曲线的退役锂电池模块快速分选技术[J]. 电网技术, 2020, 44(5): 1664-1673.
ZHENG Y J, LI J Q, ZHU Z W, et al.Rapid classification based on fast charging curves for reuse of retired lithium-ion battery modules[J]. Power system technology, 2020, 44(5): 1664-1673.
[9] 王帅, 尹忠东, 郑重, 等. 基于电压曲线的退役电池模组分选方法[J]. 中国电机工程学报, 2020, 40(8): 2691-2704.
WANG S, YIN Z D, ZHENG Z, et al.A sorting method for retired battery modules based on voltage curves[J]. Proceedings of the CSEE, 2020, 40(8): 2691-2704.
[10] 李晓宇, 徐佳宁, 胡泽徽, 等. 磷酸铁锂电池梯次利用健康特征参数提取方法[J]. 电工技术学报, 2018, 33(1): 9-16.
LI X Y, XU J N, HU Z H, et al.The health parameter estimation method for LiFePO₄ battery echelon use[J]. Transactions of China Electrotechnical Society, 2018, 33(1): 9-16.
[11] 姚宏民, 杜欣慧, 秦文萍. 基于密度峰值聚类及GRNN神经网络的光伏发电功率预测方法[J]. 太阳能学报, 2020, 41(9): 184-190.
YAO H M, DU X H, QIN W P.PV power forecasting approach based on density peaks clustering and general regression neural network[J]. Acta energiae solaris sinica, 2020, 41(9): 184-190.
[12] LAI X, QIAO D D, ZHENG Y J, et al.A rapid screening and regrouping approach based on neural networks for large-scale retired lithium-ion cells in second-use applications[J]. Journal of cleaner production, 2019, 213: 776-791.
[13] 相益萱, 姜合, 潘品臣, 等. 二次幂耦合的K-means聚类算法研究[J]. 计算机工程与应用, 2021, 57(14): 95-102.
XIANG Y X, JIANG H, PAN P C, et al.Study on K-means clustering algorithm of quadratic power coupling[J]. Computer engineering and applications, 2021, 57(14): 95-102.
[14] 孙舟, 田贺平, 王伟贤, 等. 梯次利用电池储能系统参与用户侧削峰填谷的经济性研究[J]. 太阳能学报, 2021, 42(4): 95-100.
SUN Z, TIAN H P, WANG W X, et al.Research on economy of echelon utilization battery energy storage system for user-side peak load shifting[J]. Acta energiae solaris sinica, 2021, 42(4): 95-100.