| dc.description.abstract | Application of lithium-ion batteries have increased in recent years due to their high energy density, low weight and smaller form factor. Machine learning algorithms are used in lithium-ion battery management systems due to the fact that they require less computational power. However, machine learning algorithms are a ‘black box’ in nature thus, for development and optimization of batteries a physical based model is required which facilitates to understand physical-chemical behaviors that govern the operation of battery. In this thesis, pseudo two dimensional (P2D) electrochemical model was selected and numerical solutions were computed by using MATLAB. Principles of lithium transport in anode, cathode, electrolyte and principles of chemical kinetics are used in this model. The model presents good agreement between simulated results and experimental data which are extracted from the literature. Simulations were conducted in order to investigate initial operation, lithium distribution in electrodes, power delivery, voltage response against current pulses and aging effect. The mathematical model enables to significantly minimize the development and optimization time for batteries because actual testing of batteries demands long time periods. | |
