Adaptive state-of-charge indication system for a Li-ion battery-powered devices

Accurate State-of-Charge (SoC) and remammg run-time indication for portable devices is important for the user convenience and to prolong the lifetime of batteries. So far, no one succeeded in coming up with a SoC system that is accurate enough under all realistic user conditions. An algorithm that combines adaptive system with Electro-Motive-Force (EMF) measurements during equilibrium and current measurement and integration during charge and discharge states has been developed and implemented in a real-time SoC evaluation system. During the discharge state, apart from simple coulomb counting, also the effect of the overpotential is considered. Mathematical models describing the EMF and the overpotential functions for a Li-ion battery have been developed. The overpotential model includes a variety of parameters that are changing during cycling of the battery. Adaptive methods for the battery maximum capacity and for the overpotential model parameters used in the system with the aging effects are presented in this paper. The final aim is to predict the SoC and the remaining run-time of aLi-ion battery within 1% inaccuracy under all realistic user conditions. As mobile phones are most challenging with respect to a wide variety of load currents and a wide temperature range, the developed system will focus on this application. The achieved results show the effectiveness of the novel approach for improving the SoC indication accuracy and the system capability to cope with the aging effects.