Physical, on the fly, capacity degradation prediction of LiNiMnCoO2-graphite cells
Physical, on the fly, capacity degradation prediction of LiNiMnCoO2-graphite cells
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DOI：
10.1016/j.jpowsour.2019.02.073
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发表时间：
2019-05
影响因子：
9.2
通讯作者：
Aniruddha Jana;Gregory M. Shaver;R. Edwin García
中科院分区：
文献类型：
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作者：
Aniruddha Jana;Gregory M. Shaver;R. Edwin García
开发了一种基于物理的降阶模型来描述 LiNiMnCoO2-石墨电池的容量退化。从基本原理出发，该模型捕捉了四种降解机制的影响：(i) 阳极上的 SEI 生长，(ii) 阴极上的电解液氧化，(iii) 阳极活性材料损失，以及 (iv) 阴极活性材料损失，后两种损失是由于化学机械断裂造成的。该模型计算效率高（∼1ms/周期），并且能够为汽车应用进行物理、实时的容量损失计算。结果表明，在储存条件下，SEI 生长和电解质氧化是主要的降解机制，与实验一致。相比之下，当电池受到接近上限截止电压的宽幅电流时，电解质氧化占所有降解机制的约 50%，这与文献中最近的实验一致。化学机械引起的活性材料损失在高充电状态下阳极中最大，在低充电状态下阴极中最大。结果量化了每个单独机制对退化的贡献，首次强调需要超越传统库仑计数方法的基于物理的动态描述。最后，识别各个退化贡献使得可以定制充电/放电顺序以延长电池寿命。
A physics-based, reduced order model was developed to describe the capacity degradation in LiNiMnCoO2-graphite cells. By starting from fundamental principles, the model captures the effects of four degradation mechanisms: (i) SEI growth on the anode, (ii) electrolyte oxidation on the cathode, (iii) anode active material loss, and (iv) cathode active material loss, the last two due to chemomechanical fracture. The model is computationally efficient (∼1 ms/cycle) and enables physical, real-time, capacity loss calculations for automotive applications. Results demonstrate that under storage conditions, SEI growth and electrolyte oxidation are the major degradation mechanisms, in agreement with experiments. In contrast, batteries subjected to electric currents of a wide amplitude, close to the upper cutoff voltage, electrolyte oxidation contributes ∼50% of all the degradation mechanisms, consistent with recent experiments in the literature. Chemomechanically induced active material losses are maximal in the anode at high states of charge and maximal in the cathode at low states of charge. Results quantify the contribution to degradation from each individual mechanism, highlighting, for the first time, the need of physics-based, on-the-fly descriptions that go beyond traditional coulomb counting approaches. Finally, the identification of the individual degradation contributions enables the possibility of tailoring the charge/discharge sequence to extend battery life.