Future Challenges in State of Charge Estimation for Lithium-Ion Batteries
M. Surendar1, P. Pradeepa2

1M.Surendar*, Assistant Professor, Department of Electrical and Electronics Engineering, CSI College of Engineering, Nilgiris, Tamil Nadu, India.
2Dr. P.Pradeepa, Associate Professor, Department of Electrical and Electronics Engineering, JAIN Deemed to be University, Bangalore, Karnataka, India.
Manuscript received on September 10, 2020. | Revised Manuscript received on September 20, 2020. | Manuscript published on October 30, 2020. | PP: 215-223 | Volume-10 Issue-1, October 2020. | Retrieval Number: 100.1/ijeat.A17891010120 | DOI: 10.35940/ijeat.A1789.1010120
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Abstract: 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. 
Keywords: Battery Management System BMS, Battery Model, Energy Storage, Lithium-ion Battery