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eBook - ePub
Artificial Intelligence of Things in Smart Environments
Applications in Transportation and Logistics
Mariyam Ouaissa, Zakaria Boulouard, Mariya Ouaissa, Yassine Maleh, Mariyam Ouaissa, Zakaria Boulouard, Mariya Ouaissa, Yassine Maleh
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eBook - ePub
Artificial Intelligence of Things in Smart Environments
Applications in Transportation and Logistics
Mariyam Ouaissa, Zakaria Boulouard, Mariya Ouaissa, Yassine Maleh, Mariyam Ouaissa, Zakaria Boulouard, Mariya Ouaissa, Yassine Maleh
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Inhaltsverzeichnis
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Über dieses Buch
This book focuses on the use of AI/ML-based techniques to solve issues related to IoT-based environments, as well as their applications. It addresses, among others, signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction, software-defi ned networking, congestion control, communication network optimization, security, and anomaly detection.
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Information
General parametric of four hybrid microconcentrator photovoltaic systems for electric car charging station
Sarah El Himer
Sidi Mohammed Ben Abdellah University FEZ, Morocco
Mariyam Ouaissa
Moulay Ismail University, Meknes, Morocco
Mariya Ouaissa
Moulay Ismail University, Meknes, Morocco
Abstract
This chapter covers a general, parametric, and performance analysis of four optical elements to be used in microconcentrator photovoltaic systems for electric car charging station using the same primary optic (PO): the Fresnel lens (FL). It concerns two nonimaging optics which are pyramid and hyperbola; and two imaging optics such as circular and square dome.
The study starts from optical modeling of the FL and considers several sizes and geometric needs of secondary optics (SOs). The performance of all concentrator systems is compared in terms of actual concentrations achieved, angles of acceptance, output light power distribution, and tolerances in placement of the secondary element relative to the FL. Results are compared with the same types of SOs but are designed for car roof applications.
For the first simulation results, we found that the FL with 28 prisms and a focal length of 14 mm is the optimal PO, and the pyramid is the most suitable optical element as an SO placed at focal. By adding the silicon solar cell to multijunction solar cell, the efficiency of the optical system is increased by 20%.
By checking if this power can charge an electric car at any power, and by exploiting the roof area of the car, we need 350 silicon cells under 600 multijunction cells. Therefore, the power generated is 50.6 kw. Then, the total surface of our charging station will take 3.5 m2. By comparing this surface with that of the stations found in Morocco, our station does not take a large surface and with a high power.
Keywords: primary optic, secondary optic, micro-CPV, Fresnel lens, flux uniformity acceptance angle, optical efficiency, pyramid, dome,
:Nomenclature.
A | Exit radius of the SOs | MCPV | Microconcentrator photovoltaic |
aN | Half difference between the input and the output area of the pyramid | n1 | Index of the entrance medium |
Ain | Entrance aperture area | n2 | Index of the exit medium |
Aout | Exit or receiver area | ||
C | Whole concentration ratio | ns | Index of the secondary optic |
Cg | Geometric concentration ratio | N | Number of reflection inside the cone |
Copt | Optical concentration ratio | Pin | Power at the entrance of the system |
Pout | Power at the exit of the system | ||
CPV | Concentrated photovoltaic | PMMA | Poly(methyl methacrylate) |
D | Fresnel lens diameter | r’ | Solar angle |
f | Focal length of Fresnel lens | R | Entrance radius of the Pyramid |
FL | Fresnel lens | SO | Secondary optic |
H | Length of the SOs | θi | SO entrance angle |
θout | Exit angle | θf | θf |
α | Pyramid angle | β | β |
1 Introduction
The electric vehicle is the key element of green and ecological transport. It partially solves problems related to energy and the environment [1]. An electric vehicle is a vehicle powered by an electric motor. This motor is powered by a rechargeable battery or by a fuel cell, or even by a thermal generator engine. In fully electric vehicles (battery electric vehicle), the energy sources for this type of vehicle are batteries that can be recharged by the electricity grid or by other renewable energies (solar, wind turbines, etc.), and the photovoltaic shade house (Figure 1) is an autonomous and mobile energy recharging station, for electric vehicles made available to users by l...
Inhaltsverzeichnis
- Title Page
- Copyright
- Contents
- Preface
- About the editors
- Toward the Internet of vehicles: challenges and solutions
- AI-enabled communication protocols for vehicular ad hoc networks (VANETs): fundamentals and future challenges
- Applying machine learning algorithms to improve intrusion detection system in IoV
- Auto steering control in a self-driving car using deep learning model
- Semantic segmentation with transfer learning for self-driving cars
- An improved anomaly detection process in smart vehicle using a supervised ensemble-learning framework
- Survey on AI-based IoT and drone-equipped smart agriculture
- General parametric of four hybrid microconcentrator photovoltaic systems for electric car charging station
- The influence of social media in improving supply chain intelligence using deep learning
- Index
Zitierstile für Artificial Intelligence of Things in Smart Environments
APA 6 Citation
[author missing]. (2022). Artificial Intelligence of Things in Smart Environments (1st ed.). De Gruyter. Retrieved from https://www.perlego.com/book/3250196/artificial-intelligence-of-things-in-smart-environments-applications-in-transportation-and-logistics-pdf (Original work published 2022)
Chicago Citation
[author missing]. (2022) 2022. Artificial Intelligence of Things in Smart Environments. 1st ed. De Gruyter. https://www.perlego.com/book/3250196/artificial-intelligence-of-things-in-smart-environments-applications-in-transportation-and-logistics-pdf.
Harvard Citation
[author missing] (2022) Artificial Intelligence of Things in Smart Environments. 1st edn. De Gruyter. Available at: https://www.perlego.com/book/3250196/artificial-intelligence-of-things-in-smart-environments-applications-in-transportation-and-logistics-pdf (Accessed: 15 October 2022).
MLA 7 Citation
[author missing]. Artificial Intelligence of Things in Smart Environments. 1st ed. De Gruyter, 2022. Web. 15 Oct. 2022.