一种预测和优化电池倍率性能的定量分析模型
A Quantitative Analytical Model for Predicting and Optimizing the Rate Performance of Battery Cells
摘要：
设计锂离子可再充电电池单元的一个重要目标是在不损害能量密度的情况下最大化它们的速率性能，这目前主要通过计算上昂贵的数值模拟来实现。在这里，我们提出了一个简单的分析模型，用于预测由电解质传输限制的电池组电池的倍率性能，没有任何拟合参数。它表现出非常好的协议与模拟在很宽的范围内的放电速率和电极厚度，并提供了>10 $^5$倍的加速比。该模型预测的最佳电极性能与模拟结果的差异小于10%，表明它是一个有吸引力的计算工具，为电池级电池结构设计。该模型还提供了关于改善厚电极的倍率性能的实用方法的重要见解，包括避免电极材料，如LiFePO $_4$和Li $_4$ Ti $_5$ O $_{12}$，其开路电位对充电状态不敏感，以及利用锂金属阳极协同加速厚阴极内的电解质传输。
英文摘要：
An important objective of designing lithium-ion rechargeable battery cells is to maximize their rate performance without compromising the energy density, which is mainly achieved through computationally expensive numerical simulations at present. Here we present a simple analytical model for predicting the rate performance of battery cells limited by electrolyte transport without any fitting parameters. It exhibits very good agreement with simulations over a wide range of discharge rate and electrode thickness and offers a speedup of >10$^5$ times. The optimal electrode properties predicted by the model are of less than 10% difference from simulation results, suggesting it as an attractive computational tool for the cell-level battery architecture design. The model also offers important insights on practical ways to improve the rate performance of thick electrodes, including avoiding electrode materials such as LiFePO$_4$ and Li$_4$Ti$_5$O$_{12}$ whose open-circuit potentials are insensitive to the state of charge and utilizing lithium metal anode to synergistically accelerate electrolyte transport within thick cathodes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
