Switching transient-based state of Ampere-hour prediction of lithium-ion, nickel-cadmium, nickel-metal-hydride and lead acid batteries used in vehicles

The state of the ampere-hour capacity of the battery depends on the condition of materials used in it. Large reduction of capacity ends with maintenance or replacement of the battery. Modern battery materials include application of nanomaterials and nanotechnology in various stages of production. This article attempts to monitor the capacity of battery used for vehicles which are made of different types of materials using switching transients. The analytical part was done using wavelet-based decompositions. Data sets of large number of coefficients have been developed for learning. Their statistical behaviour has been studied, and monitoring was initially carried out by some selective parameters. Then the artificial neural network-based algorithm was developed which includes all features of statistical variation for better monitoring. Case studies have been carried out followed by comparison. The study ends with a satisfactory monitoring.