Increasing Electric Vehicle Autonomy Using a Photovoltaic System Controlled by Particle Swarm Optimization

A photovoltaic-powered electric vehicle is a complex system that necessitates the use of a high-performance control algorithm. This paper aims to boost the performance of a photovoltaic system by employing a suitable algorithm to control the power interface. The main goal is to find an effective and optimal control law that will enable the photovoltaic generator (GPV) to generate the maximum amount of power possible. The main facts dealt with in this article are the mathematical simulation of the photovoltaic system, its function, and its characteristics, considering the synthesis of the step-up converter and the analysis of the maximum power point tracking algorithm. This study examines and compares two control techniques for extracting full power from the solar energy system. These two techniques are the classical “perturbation and observation” (P&O) method and the intelligent solution “particle swarm optimization (PSO) method.” The PSO solution is tested for two versions: the online PSO version and the table PSO version. The Simulink/MATLAB tool is used for simulation and comparative experiments based on the performance metrics provided. The study revealed that smart technology delivers improved efficiency than the classic edition..

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

IEEE Access - 9(2021), Seite 72040-72054

Sprache:

Englisch

Beteiligte Personen:

Habib Kraiem [VerfasserIn]
Aymen Flah [VerfasserIn]
Naoui Mohamed [VerfasserIn]
Majed Alowaidi [VerfasserIn]
Mohit Bajaj [VerfasserIn]
Shailendra Mishra [VerfasserIn]
Naveen Kumar Sharma [VerfasserIn]
Sunil Kumar Sharma [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
ieeexplore.ieee.org [kostenfrei]
Journal toc [kostenfrei]

Themen:

Battery state of charge
Electric vehicle
Electrical engineering. Electronics. Nuclear engineering
Maximum power point tracking
Particle swarm optimization
Perturb & observe
Photovoltaic system

doi:

10.1109/ACCESS.2021.3077531

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ062348620