Sunday, November 8, 2015: 4:30 PM
355B (Salt Palace Convention Center)
Lithium ion batteries used in automobiles industries to produce electric vehicles and hybrid electric vehicles are mostly made of porous electrode composites. The transport processes occurring in the pores of a porous electrode affects battery performance therefore, the performance of batteries can be increase by optimizing the electrode morphology. In most cases the electrode morphology is of irregular structures which are often be simplified to ideal rectangular or cylindrical models. The present work utilized an irregular electrode pore geometry (diverging pore) to understanding the effect of the deviation to the regular pore geometry on Li ion diffusion process in the presence of electric field and electrochemical reaction in the pore of an electrode. The area-averaging upscaling approach of homogenization is used to convert the microscopic two dimensional Nernst-plank equation to the macroscopic level. A microscopic scale diffusion-reaction and electromigration model is derived for a pore domain of both rectangular and cylindrical geometries. Afterwards, the area-averaging approach is applied to this model in order to obtain a macroscopic level pore model in terms of area-averaged concentration and effective transport parameters. By solving this model one can demonstrate the effects of diverging angles on the concentration profile in the pore domain. This information is useful to understand a system-level behavior. The effect of electrochemical reaction on the concentration profile is analyzed for zero order electrochemical reaction. The limiting cases of the diverging geometries developed models are compared with the ideal cases in order to verify the up-scaled diverging geometries pore solutions. The results indicates the importance of potential deviations of the idealized geometry when used to predict system level performance. The findings of this work are important in modeling and simulation of the performance of the electrode-base systems since the current modeling efforts have not assessed these potential deviations. These deviations could lead to important system prediction errors.