Temperature-Compensated Model for Lithium-Ion Polymer Batteries With Extended Kalman Filter State-of-Charge Estimation for an Implantable Charger

As implantable devices become more sophisticated and their extended functionalities impact their energy requirements, they not only rely on charging for the extra energy but also become ever more sensitive to battery deep discharge or overcharge. Accurate state-of-charge (SOC) estimation plays a fundamental role in ensuring the operation safety of implantable medical devices. Temperature variation can impact the battery model parameters and directly affect the accuracy of SOC estimation. This study investigates a temperature-compensated model for lithiumion polymer batteries that incorporates an extended Kalman filter method to estimate the state of the dynamic nonlinear system and its parameters, from 37 degrees C to 40 degrees C at intervals of 1 degrees C. Both simulation and experimental results indicate that the estimation error can be effectively limited to within +/- 3%. Through the accurate SOC estimation, the conventional constant current to constant voltage charging strategy is guided in order to reduce the charging time and increase the charging capacity.