Due to its high efficiency and reduced emissions, new zero-emission hybrid electric vehicles have been selected as an attractive challenge for future transport applications. New zero -emission hybrid electric, on the other hand, has some major drawbacks from the complicated charging process. The hybrid electrical fuel cell system is introduced as the main source to intelligently control multi-source activities. An ultra-capacitor system is selected as the energy recovery assistance to monitor the fuel cell’s fast transient and peak power during critical periods. To regulate energy demand and supply, an intelligent energy management system is proposed and tested through several constraints. The proposed approach system aims to act quickly against sudden circumstances related to hydrogen depletion in the prediction of the required fuel consumption basis. The proposed strategy tends to define the proper operating system according to energy demand and supply. The obtained results show that the designed system meets the targets set for the energy management unit by referring to an experimental velocity database.

Real-time simulation test beds for new zero-emission hybrid electric vehicles are considered as an attractive challenge for future transport applications that are fully recommended in the laboratory environment. In contrast, new zero-emission hybrid electric vehicles have a more complicated charging procedure. For this reason, an efficient simulation tools development for hydrogen consumption control becomes critical. In this vein, a New Zero Emission Hybrid Electric Vehicle Simulation (NZE-HEVSim) tool for the dynamic Fuel Cell Hybrid-Electric System is proposed to smartly control multisource activities. The designed system consists of a proton-exchange membrane fuel cell used to provide the required energy demand and a Supercapacitor system for energy recovery assistance in load peak or in fast transient. To regulate the supplied power, an efficient Real-Time Embedded Intelligent Energy Management (RT-EM-IEM) is implemented and tested through various constraints. The proposed intelligent energy management system aims to act quickly against sudden circumstances related to hydrogen depletion in the basis required fuel consumption prediction using multi-agent system (MAS). The proposed MAS strategy aims to define the proper operating agent according to energy demand and supply. The obtained results prove that the designed system meets the objectives set for RT-EM-IEM by referring to an experimental velocity database.

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