A Multi-Agent System for Smart Energy Management Devoted to Vehicle Applications: Realistic Dynamic Hybrid Electric System Using Hydrogen as a Fuel

Benslama Sami, Nasri Sihem, Salsabil Gherairi and Cherif Adnane
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Benslama Sami: Jeddah Community College, JCC, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Nasri Sihem: Analysis and Processing of Electrical and Energy Systems Unit, Faculty of Sciences of Tunis El Manar, PB 2092 Belvedere, Tunisia
Salsabil Gherairi: Jeddah Community College, JCC, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Cherif Adnane: Analysis and Processing of Electrical and Energy Systems Unit, Faculty of Sciences of Tunis El Manar, PB 2092 Belvedere, Tunisia

Energies, 2019, vol. 12, issue 3, 1-20

Abstract: 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.

Keywords: real-time; Proton Membrane Exchange fuel cell; supercapacitor; intelligent energy management; multi-agent; simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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