AMRIT - Alternative Machine Reasoning and Integrative Techniques for prognostics model of electric vehicles

This study investigates multiple control mechanisms of battery management systems on identifying the state of charge (SOC) and state of health (SOH) using fuzzy logic, artificial intelligence, and machine learning methodologies. This research synthesize the vehicle demand and battery supply control methods with mix of both neural networks and fuzzy sets using an adaptive neuro-fuzzy inference system (ANFIS) and a new integrative technique. It arbitrates user empowered action plan for further sustainable decision making. The assessment between these methods are modeled in terms of input and output parameter range, test condition uncertainties, and battery types in order to avoid fatal incidents such as fire accidents and other significant constraints in post-production, consumer safety, and vehicle regulation metrics.