Grey Wolf Optimization Based Energy Management Strategy for Hybrid Electrical Vehicles

Abstract

Electric vehicles (EVs) are seen as a necessary component of transportation's future growth. However, the performance of batteries related to power density and energy density restricts the adoption of electric vehicles. To make the transition from a conventional car to a pure electric vehicle (PEV), a Hybrid Electric Vehicle's (HEV) Energy Management System (EMS) is crucial. The HEVs are often powered with hybrid electrical sources, therefore it is important to select the optimal power source to improve the HEV performance, minimize the fuel cost and minimize hydrocarbon and nitrogen oxides emission. This paper presents the Grey Wolf Optimization (GWO) algorithm for the control of the power sources in the HEVs based on power requirement and economy. The proposed GWO-based EMS provides optimized switching of the power sources and economical and pollution free control of HEV.