Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{201095,
author = {vijay kumar and Chirag Y. Wanare and Sujit R. Guratkar and Vansaj B. Raut and Tejas R. Gudadhe and Prof. Chhaya H. Farde},
title = {Design and Implementation of a Dual-Axis Solar Tracking System .Using Arduino Nano, DC Motors, and LDR Sensors},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {12},
pages = {2563-2567},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=201095},
abstract = {Solar energy is among the most abundant and clean sources of renewable energy available globally. However, conventional fixed-panel photovoltaic (PV) installations suffer from significant energy losses due to suboptimal panel orientation relative to the sun's position across the sky throughout the day. This paper presents the design, fabrication, and experimental evaluation of a dual-axis solar tracking system driven by an Arduino Nano microcontroller, four light-dependent resistor (LDR) sensors arranged in quadrant configuration, and two DC gear motors with L298N H-bridge driver module. The system continuously computes differential light intensity between paired LDR sensors and generates PWM correction signals to drive the solar panel in both azimuthal (horizontal) and elevational (vertical) axes. Experimental results demonstrate a measured energy gain of approximately 35.8% over a fixed-tilt panel under comparable meteorological conditions. The proposed system is cost-effective, low-power, and suitable for small to medium scale rural and off-grid solar deployment. Solar panels. The system is simple, cost-effective,},
keywords = {Dual-axis solar tracker, Arduino Nano, LDR sensor, DC motor, photovoltaic, renewable energy, embedded systems, L298N},
month = {May},
}
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