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Electric, Hybrid Electric and Fuel Cell Hybrid Electric Vehicles: Challenges and Research Trends

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Special Issue Editors

Prof. Dr. Abdesslem Djerdir

Energy department of FEMTO-ST laboratory and Fuel Cell Laboratory, Université de Technologie de Belfort Montbéliard (UTBM), 90000 Belfort, France
Interests: modeling and design of electric and fuel cell vehicle systems (electrical machines, energy storage devices, and power converters); availability and high efficiency of electric drive trains for transport applications; experimental prototyping

Dr. Djafar Chabane

E-Mail Website
Guest Editor

FEMTO-ST Institute, FCLAB, Univ. Bourgogne Franche-Comte, CNRS, Belfort, France
Interests: fuel cell and hydrogen storage in solid form by developing energy management strategies; smart control approaches for transportation and stationary applications

Special Issue Information

Dear Colleagues,

With the development of society, global warming, environmental pollution and exhaustion of petroleum, human attention has become increasingly focused on energies. The fossil fuel consumed by the transportation sector accounts for 55% of the world’s total energy consumption and leads to 30.9% of carbon dioxide gas emissions. Thus, reducing this pollution and saving energy are the main challenges of the current and future vehicle industry. Electric vehicles (EVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (P-HEVs) and fuel cell hybrid electric vehicles (FCHVs) are thought to be the best ways to solve these problems. The main power train components for these vehicles (batteries, fuel cells, hydrogen tanks, electric machines and power electronics) have to respond to challenging demands such as having low weight, small volume, high efficiency, high power density, low cost and low electromagnetic interference. Moreover, energy management strategies (EMSs) play a key role in making these vehicles competitive in the wide automotive market thanks to the improvement of their autonomy, reliability and cost. This Special Issue of Energies focuses on the latest scientific and technical research around these topics in both academic and industrial sectors. These topics include but are not limited to the following:

Innovative architectures of the power trains of EVs, HEVs, P-HEVs or FCHVs;
Design of the power trains of EVs, HEVs, P-HEVs or FCHVs, from components to systems;
Energy management strategies for EVs, HEVs, P-HEVs or FCHVs;
Reliability of the EVs, HEVs, P-HEVs or FCHVs (e.g., reliability analysis, fault-tolerant control, aging experimental tests, modeling, diagnosis, prognosis);
Real-time simulation, hardware in the loop (HIL);
Prototyping and ecosystems of EVs, HEVs, P-HEVs or FCHVs.

Prof. Dr. Abdesslem Djerdir
Dr. Djafar Chabane
Guest Editors

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Keywords

BMS
DC/DC converters
Electrical machines
Energy management strategies (EMSs)
Reliability analysis
Fault-tolerant control
Aging experimental tests and modeling
Diagnosis
Prognosis
Design
Costs and business plans

Published Papers (2 papers)

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Research

14 pages, 5119 KiB

Open AccessArticle

Evaluation of the Performance Degradation of a Metal Hydride Tank in a Real Fuel Cell Electric Vehicle

by Santiago Hernán Suárez, Djafar Chabane, Abdoul N’Diaye, Youcef Ait-Amirat, Omar Elkedim and Abdesslem Djerdir

Energies 2022, 15(10), 3484; https://0-doi-org.brum.beds.ac.uk/10.3390/en15103484 - 10 May 2022

Cited by 4 | Viewed by 1619

Abstract

In a fuel cell electric vehicle (FCEV) powered by a metal hydride tank, the performance of the tank is an indicator of the overall health status, which is used to predict its behaviour and make appropriate energy management decisions. The aim of this paper is to investigate how to evaluate the effects of charge/discharge cycles on the performance of a commercial automotive metal hydride hydrogen storage system applied to a real FCEV. For this purpose, a mathematical model is proposed based on uncertain physical parameters that are identified using the stochastic particle swarm optimisation (PSO) algorithm combined with experimental measurements. The variation of these parameters allows an assessment of the degradation level of the tank’s performance on both the quantitative and qualitative aspects. Simulated results derived from the proposed model and experimental measurements were in good agreement, with a maximum relative error of less than

2 %

. The validated model was used to establish the correlations between the observed degradations in a hydride tank recovered from a real FCEV. The results obtained show that it is possible to predict tank degradations by developing laws of variation of these parameters as a function of the real conditions of the use of the FCEV (number of charging/discharging cycles, pressures, mass flow rates, temperatures). Full article

(This article belongs to the Special Issue Electric, Hybrid Electric and Fuel Cell Hybrid Electric Vehicles: Challenges and Research Trends)

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21 pages, 3210 KiB

Open AccessArticle

Sizing and Energy Management of Parking Lots of Electric Vehicles Based on Battery Storage with Wind Resources in Distribution Network

by Saman Shahrokhi, Adel El-Shahat, Fatemeh Masoudinia, Foad H. Gandoman and Shady H. E. Abdel Aleem

Energies 2021, 14(20), 6755; https://0-doi-org.brum.beds.ac.uk/10.3390/en14206755 - 17 Oct 2021

Cited by 3 | Viewed by 1589

Abstract

In this paper, an optimal sizing and placement framework (OSPF) is performed for electric parking lots integrated with wind turbines in a 33-bus distribution network. The total objective function is defined as minimizing the total cost including the cost of grid power, cost of power losses, cost of charge and discharge of parking lots, cost of wind turbines as well as voltage deviations reduction. In the OSPF, optimization variables are selected as electric parking size and wind turbines, which have been determined optimally using an intelligent method named arithmetic optimization algorithm (AOA) inspired by arithmetic operators in mathematics. The load following strategy (LFS) is used for energy management in the OSPF. The OSPF is evaluated in three cases of the objective function such as minimizing the cost of power losses, minimizing the network voltage deviations, and minimizing the total objective function using the AOA. The capability of the AOA is compared with the well-known particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms for solving the OSPF in the last case. The findings show that the power loss, voltage deviations, and power purchased from the grid are reduced considerably based on the OSPF using the AOA. The results show the lowest total cost of energy and also minimum network voltage deviation (third case) by the AOA in comparison with the PSO and ABC with a higher convergence rate, which confirms the better capability of the proposed method. The results of the first and second cases show the high cost of power purchased from the main grid as well as the high total cost. Therefore, the comparison of different cases confirms that considering the cost index along with losses and voltage deviations causes a compromise between different objectives, and thus the cost of purchasing power from the main network is significantly reduced. Moreover, the voltage profile of the network improves, and also the minimum voltage of the network is also enhanced using the OSPF via the AOA. Full article

(This article belongs to the Special Issue Electric, Hybrid Electric and Fuel Cell Hybrid Electric Vehicles: Challenges and Research Trends)

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Electric, Hybrid Electric and Fuel Cell Hybrid Electric Vehicles: Challenges and Research Trends

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