Additives used in the cathode of a Lithium-ion (Li-ion) battery to improve electrical conductivity can negatively impact the ionic conductivity and specific capacity. Therefore, recent focus on the design of Li-ion battery is on the additive-free cathodes. This research work aims to provide a simple rule for the design of cathode microstructure using extensive study of the effect of particle size and volume fraction on effective electrical conductivity. Most design methods used to model the effective transport properties of lithium ion battery electrodes utilize the approximations based on Bruggeman’s formula. However, this formula does not consider the microstructure geometry and hence cannot accurately predict the effective transport properties of complicated microstructure like those of Li-ion battery electrodes. In this thesis, based on the principles of mathematical homogenization, an extensive analysis of randomly generated two-phase microstructures idealized for li-ion battery cells is carried out to obtain more accurate estimates of the effective electrical conductivity. To this end, a wide range of values of particle size, volume fraction and conductivity ratios are considered to evaluate the effective conductivity values. From these results, an explicit formulation based on these three parameters to predict the effective conductivity is provided to establish a framework for a simple design rule for additive-free cathode microstructures. Finally, the significance of the microstructural information is highlighted by studying the discharge characteristics of a battery for a theoretical battery model using the Brugemman’s formulation as well as the proposed formulation based on the mathematical homogenization technique. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/23029 |
| Date | January 2018 |
| Creators | Dhakal, Subash |
| Contributors | Srinivasan, Seshasai, Mechanical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0015 seconds