Alaaeldin M. Abdelshafy

Dr. Alaaeldin M. Abdelshafy

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Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2026 in IEEE Access
Verified
Journal Article
Open access
IHIbrahem M. Hassan
Ibrahem M. Hassan
EAEssam Ali
Essam Ali
Mohamed AbdelrahemMohamed Abdelrahem
Mohamed Abdelrahem
Alaaeldin M. AbdelshafyAlaaeldin M. Abdelshafy
Alaaeldin M. Abdelshafy

22 June 2026 in Technologies
Verified
Journal Article
Open access
PDF file
EAEssam Ali
Essam Ali
Mohamed AbdelrahemMohamed Abdelrahem
Mohamed Abdelrahem
Jose RodriguezJose Rodriguez
Jose Rodriguez
AMAbdelfatah M. Mohamed
Abdelfatah M. Mohamed
Alaaeldin M. AbdelshafyAlaaeldin M. Abdelshafy
Alaaeldin M. Abdelshafy
Continouous unmanned aerial vehicle (UAV) missions are fundamentally limited by Lithium-Polymer (LiPo) battery endurance under intermittent and power-constrained renewable energy conditions. This paper proposes an integrated energy management and charging framework for a photovoltaic (PV)-powered mobile station equipped with a hybrid energy storage system (HESS) and an automated battery replacement (ABR) mechanism. A lexicographic priority-based allocator sequentially serves ABR actuation, multi-slot LiPo charging, and Brushless DC (BLDC) propulsion, while the HESS compensates for PV intermittency. At the charging level, a constraint-aware constant current–constant voltage (CC–CV) strategy is enhanced by an adaptive neuro-fuzzy inference system (ANFIS) trained on optimization-derived labels using battery temperature and its rate of change, thus enabling anticipatory thermal current derating with smooth, discontinuity-free control action. Anti-windup proportional–integral (PI) regulation and bumpless mode transfer ensure stable CC-to-CV transitions. An event-triggered emergency mode accelerates battery readiness via a max-first selection policy. Comparative simulations against a PSO/DE-optimized PID benchmark over a full diurnal PV cycle demonstrate that the ANFIS controller reduces the CC-mode current tracking root-mean-square error (RMSE) by up to 96.9%, delivers higher charge throughput, and lowers battery degradation proxies, including SOC-weighted thermal dose and equivalent full cycles (EFC). The proposed framework reliably sustains continuous charge–swap–recharge logistics under fluctuating renewable generation.

1 July 2026 in Ain Shams Engineering Journal
Verified
Journal Article
Open access
Talal AlharbiTalal Alharbi
Talal Alharbi
Alaaeldin M. AbdelshafyAlaaeldin M. Abdelshafy
Alaaeldin M. Abdelshafy
Farag K. Abo-ElyousrFarag K. Abo-Elyousr
Farag K. Abo-Elyousr