Published September 1, 2021
| Version v1
Conference paper
Modeling Battery SoC Predictions for Smart Connected Glasses Simulations
- Others:
- Laboratoire d'Electronique, Antennes et Télécommunications (LEAT) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- IEEE
Description
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.
Abstract
International audience
Additional details
- URL
- https://hal.archives-ouvertes.fr/hal-03538645
- URN
- urn:oai:HAL:hal-03538645v1
- Origin repository
- UNICA