Battery Backup Estimation and Depletion Sensing System (BBEDSS)

Abstract

Battery Backup Estimation and Depletion Sensing System (BBEDSS) for batteries is briefly elaborated, that consist of various parameters control such as flow of current & Voltage, charging and discharging techniques, state of charge estimation, protection, safety equalization and temperature control. During project three different kind of batteries will be used to gathered experimental data by applying different combination of loads. Simplified VI time series Method is used for the estimation of SOC & SOH estimation with accuracy. Different charging and discharging conditions have investigated and after that we comes to know that by collecting data from battery terminal on runtime and after plotting, we will estimate SOC and SOH so, with the help of forecasting techniques (i.e. ARIMA, ARMA etc.). This report covers required mathematical background, identification requirements, and solution for the problems regarding to the state-of-charge of battery The battery SOC reflects the overall performance and health conditions, and this method can be very useful for increasing the battery performance and protecting its life span. Design system is an IOT based System. Raspberry Pie is used for plotting graphs of different parameters of battery like voltage, current, SOC and DOD. LCD display will be used to notify the user about the health of a battery in real time. As the previously available system are based on mathematical models and methods. Our system will be sensing current & voltage from battery terminals via using a sensor for this purpose with variation of set time instance and the sensor fetched data set values will be inserted to microcontroller, the microcontroller will check the sensor sensed values and will insert the values to algorithm developed on microcontroller which takes V-I-time values and predict via simplified V-I time series and tell user about battery. The algorithm developed and embedded on it the algorithm will be forecasting the values which will be telling the user about future predicted values (lifespan estimation).