الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
The fast increase in Electric Vehicles (EVs) such as Easy Bikes, Auto-Rickshaws, and
Electric Bikes is a major contributor to the global energy issue. Egypt, a growing nation,
is likewise having issues because of excessive energy use. Although cheaper modes of
transportation and lower greenhouse gas (GHG) emissions are two of the advantages of
electric vehicles, it is difficult to generate the enormous amounts of energy needed to
charge the batteries daily. Additionally, the lack of charging stations in Egypt makes it
more difficult and expensive for EV owners. For these reasons, this research is focused on
the utilization of renewable energy resources for EV charging stations. Egypt has a large
potential for solar and wind energy resources, therefore electric vehicle charging station
(EVCS) powered by solar and wind would extend their useful operating hours.
By using HOMER Pro software, this study examines the viability of solar-wind-batteriesbased EVCS. Also, MATLAB Simulink examines the effects of current EVCS on the
power system network are also simulated and examined.
Moreover, regarding the sector of electric vehicle upgrades, in this research, a fuel cell
(FC) hybrid emergency system is presented. It contains power sources such as fuel cells,
batteries, and supercapacitors which are effective for different conveyance applications.
Abbreviating the hydrogen consumption and incrementing the lifetime of power sources
are the key factors of each energy management strategy (EMS). Proportional-integral (PI)
controller considers one of the simplest and most common control types, an incipient
proposed EMS depending on an optimized PI controller is presented considering FC
efficiency to ensure the operation of the FC stack within its maximum efficiency region
and reduce the stress on it which in turn leads to reducing its hydrogen consumption.
Regarding tunning the PI controller gains (𝐾𝑝,𝐾𝑖
), a proposed hybrid metaheuristic
optimization technique named JSPSOBAT has been presented which merges jellyfish (JS)
optimizer, particle swarm optimizer (PSO), and BAT optimizer to achieve the balance
between exploration and exploitation phases. To validate the effectiveness of the
JSPSOBAT technique, a comparative study with other single and hybrid metaheuristic
optimization techniques is presented by testing the proposed JSPSOBAT on fifty large-scale benchmark functions. Then, the JSPSOBAT is used to select the controller gains of
the proposed PI controller.
A 30 min load profile of a More Electric Aircraft and an Urban Dynamometer Driving
Schedule load profile for an electric vehicle are used for experimental validation of the
proposed technique. The performance of the proposed EMS using the proposed
optimization technique is compared with other EMS such as state machine control
strategy, classical PI control strategy, equivalent consumption minimization strategy, and external energy maximization strategy, and the results show that the proposed technique produces the best performance.