Open AccessCOMPARATIVE ANALYSIS ON STATE OF CHARGE ESTIMATION TECHNIQUE FOR A BATTERY
Author(s) -
Arun Arun,
D Seshachalam
Publication year - 2020
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2020.v05i04.095
Subject(s) - state of charge , battery (electricity) , state (computer science) , estimation , charge (physics) , computer science , engineering , physics , algorithm , systems engineering , power (physics) , quantum mechanics
In present day, Battery technology is a major demanding and in almost all applications useful. Electric car and various applications of Battery are so dependent. Batteries require special handling with the performance and its parameters need to be monitored to prevent situations that could result in damage or unexpected burst. This is incorporated by Battery Management System. Battery Management System consists of many blocks like Sensors, Battery pack, Control Circuit, Signal lines. To provide accurate information to the Control Circuit in management system it is essential to perform various operations like SOH, SOP and SOL. This project report describes the research in detail, and analysis of the SOC estimation method using two techniques which CC Method and EKF Method. The proposed model depicts accurate estimation method, by comparing to give the best State-of-charge. MATLAB/Simulink software is used for simulation and analysis, results show that the approach of State-ofcharge estimation using Extended Kalman Filter considering Thevenin model, provides less error compared to Coulomb Counting Method. And the report finally concludes accurate estimation technique for Battery Parameter Estimation.