The scaling of charging rate and cycle number of commercial batteries  

商业锂电池充电倍率与循环寿命的标度律

作　　者：Jici Wen Qingrong Zou Zehui Zhang Jian Shi Yujie Wei 温济慈;邹庆荣;张泽卉;石坚;魏宇杰(State Key Laboratory of Nonlinear Mechanics,Institute of Mechanics,Chinese Academy of Sciences,Beijing 100190,China;School of Applied Science,Beijing Information Science and Technology University,Beijing 100192,China;Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China;School of Engineering Sciences,University of Chinese Academy of Sciences,Beijing 100049,China;School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]State Key Laboratory of Nonlinear Mechanics,Institute of Mechanics,Chinese Academy of Sciences,Beijing 100190,China [2]School of Applied Science,Beijing Information Science and Technology University,Beijing 100192,China [3]Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China [4]School of Engineering Sciences,University of Chinese Academy of Sciences,Beijing 100049,China [5]School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China

出　　处：《Acta Mechanica Sinica》2022年第5期1-10,I0001,共11页力学学报（英文版）

基　　金：support from the National Natural Science Foundation of China(NSFC)Basic Science Center for“Multiscale Problems in Nonlinear Mechanics”(Grant No.11988102);Jici Wen thanks for support from NSFC(Grant No.12002343).

摘　　要：Health management for commercial batteries is crowded with a variety of great issues,among which reliable cycle-life prediction tops.By identifying the cycle life of commercial batteries with different charging histories in fast-charging mode,we reveal that the average charging rate c and the resulted cycle life N of batteries obey c=c_(0)N^(b),where c_(0) is a limiting charging rate and b is an electrode-dependent constant.This c-N law,resembling the classic stress versus cycle number relationship(the S-N curve or Wohler curve)of solids subject to cyclic loading,could be applicable to most batteries.Such a scaling law,in combination with a physics-augmented machine-learning algorithm,could foster the predictability of battery life with high fidelity.The scaling of charging rate and cycle number may pave the way for cycle-life prediction and the directions of optimization of advanced batteries.商用锂电池的健康管理目前存在大量亟待解决的问题,其中循环寿命的有效预测是电池管理系统的核心目标.本文通过利用商业锂电池不同快充倍率下循环寿命的实验结果,发现并提出了锂电池等效快充倍率c与循环寿命N之间的标度律关系,c=c_(0)N^(b)(即c-N准则),其中c_(0)表示电极材料极限充电倍率,b是与电池材料相关的常数.这一c-N准则,类似于固体材料疲劳中所周知的S-N曲线,适用于不同类型的商业锂电池,并通过已有的文献数据获得了验证.结合c-N准则和机器学习方法,我们发展了一种物理增强的机器学习模型,基于前面提出的c-N准则,使用首圈的充放电测试即可实现对电池循环寿命的高精度预测.这一工作为锂电池循环寿命预测、健康管理和锂电池的优化提供了基于力学原理的新思路.

关 键 词：Cycle-life law c-N fatigue Charging rate Lithium-ion battery Electro-chemo-mechanical coupling 

分 类 号：O35[理学—流体力学]