Efficiency Enhancement of Electric Vehicles with ANFIS-Based Energy Management

The burgeoning expansion of electric vehicles (EVs) has accentuated the imperative for sophisticated energy management systems, aimed at augmenting their efficacy while mitigating range constraints. This abstract delineates a proposition for an Energy Management System, underpinned by a Neuro-Fuzzy System controller, meticulously devised to augment the efficiency of electrical energy utilization within EVs. The paramount aim is to ameliorate overall energy proficiency, elongate driving range, and fortify the reliability of EVs. The contemplated system exploits the adaptive and self-learning characteristics of ANFIS to dynamically regulate power distribution among various components within the electric vehicle, encompassing, though not restricted to, the battery, fuel cell, and motor. The incorporation of ANFIS into the energy management system facilitates the model's adaptation to diverse driving patterns. Simulation results and comparative analyses confirm the effectiveness of the proposed ANFIS controller-based energy management system in improving the overall performance of electric vehicles. Through this innovative approach, EVs can achieve greater efficiency, longer driving ranges, and enhanced reliability, driving forward the adoption of sustainable transportation solutions.