RFID-Enabled Modeling and Simulation of Sodium-Ion Batteries for Smart City Energy Systems

Abstract

The concept of smart cities revolves around integrating advanced technologies to improve urban living standards. Therefore, smart cities require efficient energy systems to satisfy the growing needs for sustainability and resilience. Moreover, Radio Frequency Identification (RFID) technology has emerged as a pivotal enabler in the realization of smart cities. For energy storage applications, sodium-ion batteries (SIBs), with their cost-effectiveness and abundant raw materials, are emerging as a viable alternative to lithium-ion batteries (LIBs). In order to maximize energy storage and management within smart city frameworks, this study investigates the incorporation of RFID technology with SIB mathematical modeling. This paper also explores the diverse applications of RFID in smart cities, highlighting the synergy between RFID and SIB technologies. The preliminary framework for co-simulating SIB parameters with placeholder identifiers proved the possibility to develop a system capable of real-time monitoring and data management of a SIB system with RFID technology. In this study, a Python implementation that models the charge/discharge characteristics of SIBs programmatically using parameters extracted from literature was formulated to monitor battery parameters with RFID simulation. The output file contained battery parameters for each cycle, including RFID tags for traceability.