Enhancing Electric Vehicle Efficiency through an ANFIS Controller-Driven Energy Management System

The exponential expansion of electric-vehicles (EVs) has emphasized the necessity for effective energy management systems to optimize their performance and overcome range constraints. This abstract delineates a proposition for an Energy Management System, founded upon a Neuro-Fuzzy System controller, meticulously crafted to enhance the efficacy of electrical energy utilization within electric vehicles. The primary objective is to improve overall energy efficiency, extend the driving range, and enhance the reliability of EVs. The suggested system harnesses the adaptive and self-learning attributes of ANFIS to dynamically regulate the power allocation among diverse components within the electric vehicle, including but not limited to the battery, fuel cell, and motor. The integration of ANFIS into the energy management system enables the model to adapt to diverse driving patterns. Simulation outcomes and comparative analyses manifest the efficacy of the proposed ANFIS controller-based energy management system in enhancing the comprehensive performance metrics of electric vehicles.