Modeling Battery SoC Predictions for Smart Connected Glasses Simulations

Alexis Arcaya-Jordan, Alain Pegatoquet, Andrea Castagnetti

Abstract: In this paper we propose an analytical Lithium Polymer (LiPo) rechargeable battery modeling approach to accurately predict battery SoC during simulations. This approach is based on a data-driven method for modeling the aging phenomenon present in rechargeable batteries. The proposed battery model is integrated into a system-level modeling methodology intended to simulate the discharge process of smart connected glasses powered by a 95mAh LiPo battery. Obtained results show that the proposed analytical battery modeling approach helps predicting battery SoC with less than 3% error. Moreover, this battery model allows simulating, in a few minutes, smart glasses scenarios that can last for days.