An efficient techniques for scheduling the hybrid electric vehicles energy management

The problems of energy management in the power systems of electric vehicles (EVs) are among the difficulties facing the transportation world, especially with the hybridization of systems based renewable sources. The hybrid system in this work is an HEV containing a fuel cell (FC) as primary source, energy storage unit that is lithium battery, direct current (DC) generators, and second energy storage unit that is supercapacitors, each source connected with special power converters. This work studies a proposition for HEV, by integrating a DC generators as additional sources, and a deep neural network (DNN) in the energy management strategy (EMS).The proposed technique was responsible for reducing 30 % and 5% using DC generators and DNN-EMS respectively compared to state machine (SM), with improving the efficiency to 98.3%. The study’s objective is to show the impact of authors contributions based hard and soft techniques.