Comparative Study of Energy Management Strategies for Hybrid Electric Vehicle with Hybrid Energy Storage System

Abstract

This analysis focus on the enhancement of Artificial Neural Networks (ANN) and Fuzzy Logic Controller (FLC) based Energy Management System (EMS) for Hybrid Electric Vehicle (HEV) with hybrid energy storage system (HESS). The EMS plays a vital role in HEVs by enhancing driving range and reducing operational costs. This article explores energy management and optimization strategy for HEV using HESS consisting of a lithium-ion battery pack and an ultracapacitor (UC) pack. The proposed approach employs FLC and ANN to enhance key battery performance metrics, including state of charge, driving range and lifespan. A parametric comparison with a conventional PID controller is also provided. While battery powered HEV offer high energy density, low environmental impact and dependable operation, the addition of UC’s further improves their ability to manage rapid power demands. Simulink is used to simulate the system's performance and evaluate the effectiveness of each intelligent control method. The results of the comparative analysis highlight the optimal strategy for efficient energy management in HEV.