Joint structural and electrochemical modeling: Impact of porosity on lithium-ion battery performance
Joint structural and electrochemical modeling: Impact of porosity on lithium-ion battery performance
复制标题
联合结构和电化学建模：孔隙率对锂离子电池性能的影响
DOI：
10.1016/j.electacta.2019.05.005
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发表时间：
2019
影响因子：
6.6
通讯作者：
U. Krewer
中科院分区：
文献类型：
--
作者：
V. Laue;F. Röder;U. Krewer
未来锂离子电池能量密度的提高需要对电极结构和相关生产工艺进行系统优化。这种优化是由预测电池性能具有良好的准确性的电化学模型促进。在这项工作中，经典的Doyle-Newman电极模型中的结构与模型参数的经典关系被取代，以提高电极结构效应模型的预测精度。因此，使用3D微结构模型来导出离子和电导率的有效电极性质关系，然后将其用于Doyle-Newman模型的计算高效的P2 D框架中。模拟清楚地显示了从电子传输限制的过渡到离子传输限制的电极性能，随着压缩比的增加。与经典的P2 D模型相比，将导出的代数结构-模型参数关系集成到电化学模型中可以更高的精度预测实验数据的最佳孔隙率。
Future increases of energy density of lithium-ion batteries require a systematic optimization of electrode structure and the related production process. Such optimization is facilitated by electrochemical models which predict cell performance with good accuracy. In this work, classic relations of structure to model parameters in the classical Doyle-Newman electrode model are replaced to improve the prediction accuracy of the model regarding electrode structure effects. Therefor, a 3D micro structure model is used to derive effective electrode property relations for ionic and electric conductivity, which are then used in the computationally efficient P2D framework of the Doyle-Newman model. Simulations show clearly the transition from an electron transport limited to an ion transport limited electrode performance with increasing compression ratio. Integrating the derived algebraic structure-model parameter relations into the electrochemical model allows a higher accuracy in predicting the optimal porosity of the experimental data compared to the classical P2D model.
影响因子：
6.6
作者：
Carraro, Thomas;Joos, Jochen;Ivers-Tiffee, Ellen
通讯作者：
Ivers-Tiffee, Ellen
影响因子：
9.2
作者：
Danner, Timo;Singh, Madhav;Latz, Arnulf
通讯作者：
Latz, Arnulf
通过 FIB/SEM 断层扫描重建 LiFePO4 阴极的定量表征
影响因子：
3.9
作者：
M. Ender;J. Joos;T. Carraro;E. Ivers-Tiffée
通讯作者：
E. Ivers-Tiffée