Modelling of photovoltaic production and electrochemical storage in an autonomous solar drone

Cosson Mickael; David Benjamin; Arzel Ludovic; Poizot Philippe; Rhallabi Ahmed

doi:10.1016/j.esci.2022.02.004

Volume 2 Issue 2

Mar. 2022

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Cosson Mickael, David Benjamin, Arzel Ludovic, Poizot Philippe, Rhallabi Ahmed. Modelling of photovoltaic production and electrochemical storage in an autonomous solar drone[J]. eScience, 2022, 2(2): 235-241. doi: 10.1016/j.esci.2022.02.004

Citation:

Cosson Mickael, David Benjamin, Arzel Ludovic, Poizot Philippe, Rhallabi Ahmed. Modelling of photovoltaic production and electrochemical storage in an autonomous solar drone[J]. eScience, 2022, 2(2): 235-241. doi: 10.1016/j.esci.2022.02.004

Citation:

Cosson Mickael, David Benjamin, Arzel Ludovic, Poizot Philippe, Rhallabi Ahmed. Modelling of photovoltaic production and electrochemical storage in an autonomous solar drone[J]. eScience, 2022, 2(2): 235-241. doi: 10.1016/j.esci.2022.02.004

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Modelling of photovoltaic production and electrochemical storage in an autonomous solar drone

doi: 10.1016/j.esci.2022.02.004

a.
Nantes Université, CNRS, Institut des Matériaux de Nantes Jean Rouxel, 2 rue de la Houssinière, 44322, Nantes, France
b.
XSun, 1 Route de la Croix Moriau, 44350, Guérande, France

More Information

Corresponding author: Philippe Poizot philippe.poizot@cnrs-imn.fr; Ahmed Rhallabi ahmed.rhallabi@cnrs-imn.fr
Received Date: 2021-08-30
Revised Date: 2022-01-04
Accepted Date: 2022-02-14

Available Online: 2022-02-18

Abstract

Abstract

A simple, efficient simulator has been developed to predict the generation of photovoltaic energy and its storage in Li-ion batteries, for an autonomous drone with four wings covered by solar panels based on thin-film gallium arsenide photovoltaic cells (III–V). This simulator allows prediction of the effective photovoltaic power produced by the solar panels as well as the battery pack voltage when the drone is flying. Flight parameters such as irradiance, sun inclination angles, and drone Euler angles are considered as input parameters. The measured photovoltaic power and battery pack voltage are in good agreement with the simulated values, making practical use by the XSun company possible. This parametric study shows the effects of climatic and geographic conditions on drone autonomy. In optimal weather conditions on a sunny day, drone flight can last 12 h.
- Unmanned aerial vehicle,
- Drone flight simulator,
- Simulation,
- Energy storage,
- Photovoltaic energy

● The simulator was built using the Matlab© environment
● The simulator has been validated in real-flight conditions
● A simulator has been developed to predict the generation of photovoltaic energy and its storage in Li-ion batteries for an autonomous drone
● The simulator is composed of three main modules: the photovoltaic production, the energy storage unit and the energy management system
● A parametric study was performed to show the performance of the drone regarding the weather and geographical conditions

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