Study and modelling of lithium ion cell with accurate soc measurement algorithm using Kalman filter for electric vehicles

Lithium Ion cells are preferred over lead acid cells for electric vehicles due to their energy density, higher discharge current and size. The cost of lithium ion cells is scaling down compared to ten years earlier, but as their performance characteristics increase, the need for safety and accurate modelling also increases. The absence of a generic cell model is associated to the different makes of cells and different chemistries of Lithium ion cells behave differently under the testing conditions required for every unique application. The focus of this thesis will be on how to provide intelligence to the battery management system for calculating the state of charge of a cell so that the depth of discharge of the pack can be controlled, and to balance the voltage levels of all modules in a battery pack. This will involve cycling of the chosen type of cell, modelling it for its parameters, analyzing the cycling data and choosing the perfect depth of discharge required for the application from the energy or capacity vs open circuit voltage (OCV) graph. The lithium ion model will be evaluated from the transient response of the battery pack. This will then be made as a working prototype on an electric vehicle car and its behavior studied practically