Akademik Veri Yönetim Sistemi
IEEE Access, cilt.14, ss.79640-79661, 2026 (SCI-Expanded, Scopus)
In hot desert regions such as Qatar, planning electric vehicle (EV) charging infrastructure requires methodologies that account for local driving patterns and extreme climate conditions. This study presents a pioneering exploratory simulation-based framework to evaluate the feasibility of residential EV charging in Qatar, using high-resolution (ten-second) GPS traces from seven conventional petrol vehicles used as surrogates for local EV driving behavior. This framing reflects the Qatari context: the country is resource rich and carbon intensive, private mobility remains petrol dominated, and private EV penetration is still extremely low, partly because petrol prices are highly subsidised. The statistical analysis of telematics data collected over four months (September-December), capturing seasonal variations in travel and climate, is presented. A clustering and labeling methodology, based on a Bayesian-optimized composite of Silhouette, Davies-Bouldin, and Calinski-Harabasz indices, is presented to characterize representative spatio-temporal mobility profiles. By employing the open-source emobpy platform, EV operations are simulated for two extreme driver profiles (high- and low-usage), three EV types (small sedan, mid-size SUV, and truck), and four charging strategies. Hourly local climate variables (temperature, dew point, and pressure) are further integrated into simulation study to quantify climatic impacts on energy use. Electric mobility time series are statistically validated against observed travel patterns. Results indicate that home charging can satisfy daily energy requirements in most simulated cases, while hot-weather operation significantly increases specific energy use. For the low-usage driver profile, average consumption increases from 0.193, 0.280, and 0.366 kWh/km in December to 0.282, 0.366, and 0.449 kWh/km in September for the Nissan Leaf, KIA EV9, and Ford F-150, respectively. Across the simulated combinations of two driver profiles, three EV types, four charging strategies, and two representative seasonal months, the results further show that charging strategies can offset part of the battery-size requirement by enabling more frequent home-based replenishment. The findings are therefore interpreted as an initial data-driven basis for EV charging planning in Qatar and neighbouring hot-climate regions, rather than as a comprehensive national mobility survey.