Online State Estimators for Lithium Ion Batteries: Development of a multi-physics based online State of health estimator for Lithium Ion batteries.

MSc defense of Palash Gaikwad

The thesis discusses development of a physics based reduced order performance model of a lithium ion cell which includes major aging mechanisms ( SEI layer formation, Lithium Plating Active material loss) and a lumped thermal model. The model is then transformed into state space using control techniques which is then used to build an online state estimator.  The estimator is able to estimate in real time , battery state of charge (SOC), instantaneous available  power,  and  parameters  indicative  of  the  battery state of health (SOH) such as power fade and capacity fade, and  is  able  to  adapt  to  changing  cell  characteristics  overtime as the cells in the battery pack age.