An Advance and Hybrid State-of-Charge Measurement Technique for Battery Management System

Battery Management System is a vital component in any battery driven device or facility. It is used to measure and control all the major battery parameters for better efficiency and performances. In today’s world each and every powered system is focused to get powered from electric supply. So, electric driven systems are the trending topic of research. In this paper, a proper discussion and analysis have been done on how the proposed solution is providing the State of Charge (SOC) measurement. The technique consists of a Non-linear Regression Model that is capable of analysing the dynamic behavior of the system and predict the SOC over time. The Coulomb Counting Method Model is to provide the initial value of SOC. Without initial value, the system cannot predict the current status of the system and cannot predict the SOC. Though the coulomb counting is used widely but there are some errors of measurement due to noise and other unnecessary signals. So, to remove those noises the measured values are passed through a modified Kalman filter to filter the prediction, leads to a better result that meets the dynamic behavior of the system accurately. This discussion also consists the overall testing and analysis of the system with a real time sample data to show it real time performance.