Fuzzy-based multi-objective optimization for subjection and diagnosis of hybrid energy storage system of an electric vehicle

Abstract

Hybrid vehicles are widely considered as the emerging solutions for green technology in the field of transportation due to their user and eco-friendly interface. Generally speaking the hybrid energy system is prone to multiple types of faults and an intelligent monitoring layer can ensure smooth operation and inform any maintenance issues. In this work, we present an interface which integrates multiple AI and signal processing techniques to control the functioning of hybrid vehicles and detect the different faults interrupting smooth performance in a very short span of time. We demonstrate the thought process, simulation, final software interface, and test results to confirm its effectiveness.