Improvement of Energy Management Control Strategy of Fuel Cell Hybrid Electric Vehicles Based on Artificial Intelligence Techniques

Abstract

In this paper, we present a new approach for the optimization of energy management of the hybridization of three sources battery/Fuel Cell/Photovoltaic (B/FC/PV) vehicles configurations in order to reduce hydrogen consumption. An advanced control optimization strategy is proposed using an artificial intelligence (AI) algorithm carried out in a Matlab/Simulink environment. The power control of the fuel cell is obtained by regulating the powers of the two other sources as well as the state of charge (SOC) of the battery with hybridization via a parameter PH (parameter of hybridization). The regulation of the power of both battery and the solar PV system is achieved to the regulation of the DC bus voltage according to the reference current of the fuel cell during the optimization of the output value via a parameter PO (parameter of optimization). The activation outputs of the three sources are generated by the AI algorithm developed while including the dynamics and the profile/condition of the road as well as the demand of the vehicle. An optimization is proposed via the introduction of two parameters PH and PO, during phases of high energy demands. The results show that the proposed strategy will provide a new approach for the advanced energy management system for hybrid vehicles.