优化锂离子电池双层阴极速率性能的多层 Doyle-Fuller-Newman 模型

E. Tredenick, Samuel Wheeler, Ross Drummond, Yige Sun, Stephen R. Duncan, Patrick Grant
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摘要

研究人员探索了由两种活性材料组成的双层阴极改善锂离子电池充电性能的能力。电极的制造采用了锂镍锰钴氧化物 Li[Ni0.6Co0.2Mn0.2]O2 (NMC622) 和磷酸铁锂 LiFePO4 (LFP) 活性颗粒的不同排列方式,包括两种不同的离散子层。我们展示了电极 C 速率性能对电极设计敏感性的实验数据。为了了解复杂的双层电极性能,并确定快速充电的最佳设计,我们对电极动力学的 Doyle-Fuller-Newman (DFN) 模型进行了扩展,该模型可在任意数量的子层中容纳不同的活性材料,称为多层 DFN (M-DFN) 模型。我们展示了如何通过电极设计协同利用 NMC 和 LFP 不同的开路电势函数。我们展示了如何通过电极设计协同利用 NMC 和 LFP 不同的开路电势函数,通过调节锂电解液浓度提高可实现的容量。最后,我们利用 M-DFN 模型,通过调整 LFP 和 NMC 子层厚度的比例,进一步优化了性能最佳的双层电极排列。
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A Multilayer Doyle-Fuller-Newman Model to Optimise the Rate Performance of Bilayer Cathodes in Li Ion Batteries
Bilayer cathodes comprising two active materials are explored for their ability to improve lithium-ion battery charging performance. Electrodes are manufactured with various arrangements of lithium nickel manganese cobalt oxide Li[Ni0.6Co0.2Mn0.2]O2 (NMC622) and lithium iron phosphate LiFePO4 (LFP) active particles, including in two different discrete sub-layers. We present experimental data on the sensitivity of the electrode C rate performance to the electrode design. To understand the complex bilayer electrode performance, and to identify an optimal design for fast charging, we develop an extension to the Doyle-Fuller-Newman (DFN) model of electrode dynamics that accommodates different active materials in any number of sub-layers, termed the multilayer DFN (M-DFN) model. The M-DFN model is validated against experimental data and then used to explain the performance differences between the electrode arrangements.We show how the different open circuit potential functions of NMC and LFP can be exploited synergistically through electrode design. Manipulating the Li electrolyte concentration increases achievable capacity. Finally the M-DFN model is used to further optimise the best performing bilayer electrode arrangement by adjusting the ratio of the LFP and NMC sub-layer thickness.
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