Capacity fade analysis of commercial Li-ion batteries

There has been tremendous interest in using Li-ion batteries to power many devices in consumer electronics. One of the problems associated with the performance of Li-ion batteries is the capacity fade with cycling. This capacity fade is caused by various means, which depend on the electrode materials and also on the protocol adopted to charge the cell. Capacity fade in lithium-ion cells can be attributed to unwanted side reactions that occur during overcharge or over discharge, which causes electrolyte decomposition, resistive film formation, active material dissolution and other phenomena. Elucidating the capacity fade mechanisms will aid in prolonging the service life of these batteries. Thus understanding the capacity fade mechanisms in Li-ion systems is critical in choosing proper active materials and cell design to obtain an optimum performance under continuous cycling and storage. The objectives of this thesis were to analyze, to quantify and to model the capacity fade of commercial Li-ion batteries and use the model for the prediction of cycle life under several cycling conditions.; Performance studies have been carried out for two commercially available Li-ion batteries namely Prismatic Cellbatt cells and 18650 Sony cells with LiMn₂O₄ and LiCoO₂ as positive electrode materials respectively. Cycling conditions include operating temperature, charge rate and end of charge voltage (EOCV). This thesis includes destructive physical analysis of the cycled electrode materials to identify the critical parameters causing capacity fade and to quantify the cell capacity loss. A capacity fade balance has been developed through which the total capacity loss was accounted by three major factors namely rate capability loss, secondary (LiCoO₂/Carbon) and primary (Li+) active material losses.; The final part of this thesis focuses on developing mathematical models to explain capacity fade with cycling and storage. Semi-empirical models have been developed based on experimental results to explain the capacity fade of 18650 Li-ion cells under continuous cycling. An attempt has been made to explain the capacity fade of Li-ion cells through a first principles approach. This model could be used as a tool to predict the capacity fade of Li-ion cells when cycled under several end of charge voltage and depth of discharge. A solvent diffusion model was also developed to explain the aging of Li-ion battery cells that could predict the calendar life during storage.