State of charge-dependent aging mechanisms in graphite/Li(NiCoAl)O2 cells: Capacity loss modeling and remaining useful life prediction

State of charge-dependent aging mechanisms in graphite/Li(NiCoAl)O2 cells: Capacity loss modeling and remaining useful life prediction
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石墨/Li(NiCoAl)O2 电池中电荷依赖性老化机制的状态:容量损失建模和剩余使用寿命预测

DOI:
10.1016/j.apenergy.2019.113818
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发表时间:
2019-12
期刊:
影响因子:
11.2
通讯作者:
Michael Pecht
Michael Pecht
中科院分区:
工程技术1区
文献类型:
--
作者:
Yongzhi Zhang;Rui Xiong;Hongwen He;Xiaobo Qu;Michael Pecht

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容量损失建模是准确可靠地评估锂离子电池寿命所必需的。当前容量损失模型参数无法在线识别。为了解决这个问题,本文已经开发了一个容量损失模型的基础上,老化机制的固体电解质界面层的生长和活性材料的损失。实验结果表明,由于固体电解质界面生长的容量损失是独立的充电状态的范围在循环过程中,而由于活性材料损失的容量损失取决于充电状态的范围。建立了综合老化模型,并结合递推最小二乘法实时辨识模型参数。在我们的案例研究中,容量损失模型的估计误差在1%以内,在不同的荷电状态范围。为了避免电池特性不一致引起的建模误差,模型参数进一步基于在线数据自适应地更新,以预测特定电池的准确寿命。
Capacity loss modeling is required for accurate and reliable lifetime evaluation of lithium-ion batteries. The current capacity loss model parameters cannot be identified online. To address this problem, this paper has developed a capacity loss model based on the aging mechanisms of solid electrolyte interface layer growth and active material loss. Experimental results show that capacity loss due to solid electrolyte interface growth is independent of state of charge ranges during cycling, whereas capacity loss due to active material loss depends on the state of charge ranges. A comprehensive aging model is thus developed, combined with the recursive least squares method to identify the model parameters in realtime. In our case studies, the estimation errors of the capacity loss model are within 1% under different state of charge ranges. To avoid the modeling error caused by cell characteristic inconsistencies, model parameters are further updated adaptively based on online data for predicting the accurate lifetime of the specific cell.
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