scholarly journals For the Automotive Gas Turbine Hybrid-Electric Vehicles A Challenge to the Virtually Zero-Emission Concepts

2010 ◽  
Vol 4 (3) ◽  
pp. 575-586
Author(s):  
Bogdan Thaddeus Fijalkowski
Keyword(s):  
Gas Turbine ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Zero Emission ◽  
Hybrid Electric

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

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 474 ◽  
Author(s):  
Benslama Sami ◽  
Nasri Sihem ◽  
Salsabil Gherairi ◽  
Cherif Adnane
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Electric Vehicles ◽  
Energy Demand ◽  
Hybrid Electric Vehicles ◽  
Multi Agent System ◽  
Electric System ◽  
Multi Agent ◽  
Zero Emission ◽  
Hybrid Electric

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.

EV – Challenges In Going Electric

2018 ◽  
Author(s):  
Umanand L
Keyword(s):  
Mass Transport ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Research Activity ◽  
Considerable Research ◽  
Hybrid Electric

This article presents a frank and open opinion on the challenges that will be faced in moving towards an electric mass transport ecosystem. World over there is considerable research activity on electric vehicles and hybrid electric vehicles. There seems to be a global effort to move from an ICE driven ecosystem to electric vehicle ecosystem. There is no simple means to make this transition. This road is filled with hurdles and challenges. This paper poses and discusses these challenges and possible solutions for enabling EVs.

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

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