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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Muhammed Zaharadeen Ahmed
Al-Ansar Universiy Maiduguri University of Technology and Arts of Byumba

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Emulation-based evaluation of dust-aware automated cleaning system for aggregated solar panels on electric vehicles Mohamed Abubakr Mahgoub Hassan; Belal Ahmed Hamida; El-Sayed Soliman A. Said; Muhammed Zaharadeen Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i3.pp637-648

Abstract

The integration of photovoltaic (PV) panels into electric vehicles (EVs) provides a complementary energy source capable of extending driving range and reducing reliance on grid-based charging. However, the practical contribution of vehicle-mounted PV systems is significantly constrained by dust accumulation, which can induce power losses exceeding 20% under prolonged urban and roadside exposure. This study presents a low-power; sensor-driven, automated dust detection and cleaning system specifically designed for aggregated EV-mounted solar panels. Hybrid series–parallel panel aggregation architecture is employed to mitigate mismatch and partial shading effects associated with non-uniform dust deposition. A MATLAB/Simulink-based emulation framework is developed to model dust-induced attenuation, capacitive sensor response, cleaning subsystem energy consumption, and net energy recovery under static parking, urban driving, and mixed-use operating conditions. Results demonstrate that the proposed system maintains panel performance within 95%–98% of clean baseline output and recovers approximately 12%–15% of the dust-induced lost energy per cleaning cycle, while sustaining a positive net energy balance with minimal operational overhead. The main contributions of this work include the development of a quantitative energy trade-off model linking dust density, sensor response, and cleaning cost, the design of an EV specific hybrid aggregation strategy for dust-resilient power extraction, and a reproducible emulation framework for evaluating autonomous cleaning systems under realistic vehicular conditions. These findings confirm the technical feasibility and energy efficiency of intelligent dust mitigation as an enabling mechanism for solar-assisted electric mobility.
Co-Authors Belal Ahmed Hamida El-Sayed Soliman A. Said Mohamed Abubakr Mahgoub Hassan