Abstract:
Our project “Development of Test bed of battery health monitoring and management for aerospace applications” aims at battery backup estimation and health monitoring at run time. The techniques of data logging, Switching and Future predictions are involved in this project. Firstly, we have to log the data of battery and measure future prediction from its curves which are generated through machine learning and python techniques. After that, we have taken references curve from the battery and compare these curves with the curve of new battery. This will tell us about the performance of battery and backup time of the battery. Through current and voltages graphs of battery is estimated at real time. We have implemented different machine learning and python techniques for the logging and pre-processing of the data in order to predict battery backup time. At last, we have implemented GUI technique which tells us real time dis-charging curve and also tells us about the references curves and fnally tells us about the backup time of battery at a fxed load through curve comparison technique.
