The State-of-the-art Energy Management Strategy in Hybrid Electric Vehicles for Real-time Optimization

Abstract

Oil consumption is rising faster in India than in any other major economy. There appears to be a need for 9.8 million barrels of oil per day by the year 2040. In light of rising pollution levels, many countries are advocating for Gridable Electric Vehicles (GEVs). This study focuses on the role that GEVs can play in aiding the MGCS by controlling an Intelligent Energy Management System (IEMS) while in transit. Additionally, the energy consumption rate (ECR) of the battery and battery stress of vehicle are of greater significance in the analysis of Hybrid Electric Vehicles (HEVs) with the goal of enhancing driving range and battery life span. New developments in automotive technology aim to lower emissions and stress on the vehicle's battery. The overarching goal of this work is to create optimization and prediction models for examining the impact of control elements like EMCS, vehicle model, and SoC of ESSs on vehicle performance like energy consumption rate (ERR) and battery stress. It also discusses howto decide which car controls to use to optimise performance. Design of experiment (DoE) methods are used to examine the cumulative effect of control factors on vehicle performances.