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.

The sensor networks raise fundamental problems for the scientific community. These problems are due to the wireless communications, the density of nodes distribution, the resources constraints (energy, processor and memory), the low nodes reliability and the strongly distributed nature of the supported application. The specific particularities of the sensor networks make it difficult the guarantee of the real-time quality of service which remains currently an important challenge. This paper presents novel protocol solutions for sensor networks in hard real-time environments. We try to get the optimisation of both constraints at the same time: real-time communication delay guarantee and the energy consumption. Our routing and medium access strategy allows the load balancing, the interferences reduction and the real-time guarantee, for being based on a dynamic generation of real-time communication trees. The simulation results show that our routing and medium access protocols help the traffic load balancing to increase the system lifetime and the guarantee of real-time traffics.

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.

One of the most interesting problems due to its ability to integrate hydrogen as a fuel is HES, supported by PEMFC and Super-capacitors. The fuel cell was chosen to replace traditional energy sources such as batteries and diesel as an attractive technology. PEMFC has not been able to meet the demand for loading and responding to continuous power requirements. To do this, the Supercapacitor (SC) was chosen as an effective means of compensating for transient energy. For this purpose, a precise energy management system (EMS) has been proposed and evaluated using a Fuzzy Logic Controller (FLC) to coordinate the required power between the proposed design and the power source. Depending on Supercapacitor State of Charge (SOCsc), energy demand, vehicle speed, and road traffic data (such as map and GPS), the proposed power management system tends to correct the energy demand.

In order to eliminate the interferences between neighbors and reduce the delay, with the respect of the real time constraint, we focus our work on the multi-frequency scheduling access protocols. In this paper, we review the most multi-frequency MAC protocols which deploy more than one frequency to transmit data to neighbors. After that, we propose an optimized TDMA multi-frequency scheduling access contribution for sensor networks which is based on three phases. In the first phase, we assign frequencies based on parent node reception in communication tree structure. The reduction of the number of frequencies is provided, in phase two, based on the principle of the graph coloring. Finally, in the last phase, we reduce frequencies to the maximum number of allowed frequencies with TDMA (Time Division) clustering principle. Our results are compared with the other works and have showed that our strategy can remove more interference between neighbors, optimize communication delay and adapt with the maximum number of frequencies in WSN (Wireless Sensor Networks).