Open AccessFuture Challenges in State of Charge Estimation for Lithium-Ion Batteries
Author(s) -
M. Surendar,
P. Pradeepa
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1789.1010120
Subject(s) - state of charge , battery (electricity) , probabilistic logic , computer science , lithium (medication) , charge control , energy management , automotive engineering , embedded system , control engineering , engineering , real time computing , energy (signal processing) , artificial intelligence , power (physics) , medicine , statistics , physics , mathematics , quantum mechanics , endocrinology
Energy storage system is an Emerging technology in past few decades. The Energy storage system is an important technology for Electric Vehicles, Hybrid Electric Vehicles (EV) and (HVE) and Micro grid system. The Battery Management System (BMS) is need to be control and monitor the various parameter of the battery such as SOC , SOH, C-Rate, E-Rate ,Temperature , RVL , EOL and so on. However, the (SOC) State of Charge is an important estimation for the online control and BMS monitoring. The SOC is the challenging task when online control and BMS monitoring. This various technique or methods available to estimate the SOC and alsoits represents the Elaboration for various methods of SOC estimation and its drawback. Past five years, where the tendency of the Estimation technique has been oriented towards a mixture of probabilistic techniques and some Artificial Intelligence.