2026-10-11T15:10:09Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33866771 2026-09-16T17:42:30Z category_21 category_272 category_873 category_734 portal_5 item_type_3 month_year_09_2026

<p>Core modules of the MATLAB code.</p> Huajun Chen (29940) Xiaoye Wang (3633976) Lina Yuan (2489206) Jing Gong (105828) Biotechnology Environmental Sciences not elsewhere classified Chemical Sciences not elsewhere classified Biological Sciences not elsewhere classified urban china )- stage trickle charging stage solution framework saving research paradigm regulatory eirp ceiling real geographical topology practical deployment assumptions particle swarm hybrid networking technology enables mode supply node information ” dual grid electricity reduction generation mobile communication dynamic sleep strategy cumulative carbon reduction carbon emissions caused achieve carbon neutrality 5 ghz band 38 kg co 22 kg co 2025 &# 8211 evtol per flight evtol mission profiles evtol fuselage curvature intelligent sleep state graph neural network emergency power supplementation conservative uncertainty range integration base station div >< p annual operation scale microwave energy beam 3 db cable 6g integrated perception evtol task “ power green operation entire network dormant state conservative 11 annual sequestration base stations 3 db traditional single strict constraint sight conditions pointing angle opportunistic hovering measured millimeter <div><p>In response to the bottleneck issues of energy consumption and carbon emissions caused by the explosive growth of the low-altitude economy, we break away from the traditional single-machine energy-saving research paradigm and innovatively reconfigure the sixth-generation mobile communication (6G) perception-integration base station into a “power-information” dual-mode supply node that can enter a dormant state. The time-energy-carbon ternary coupling model (TEC-6G) was constructed, and the collaborative trade-off mechanism of the base station sleep ratio, the pointing angle of the microwave energy beam and the quality of service (QoS) of the eVTOL task was quantified for the first time. Based on the real geographical topology of 5G-A base stations in the Yangtze River Delta region and the dataset of 12,000 eVTOL flight paths. A 3.5 GHz phased array wireless energy transmission link was built on the MATLAB platform, specifically designed for opportunistic hovering-stage trickle charging and emergency power supplementation during eVTOL mission profiles, rather than sustained cruising power delivery. By integrating the measured millimeter-wave channel impulse responses, a two-stage solution framework of graph neural network-Particle swarm hybrid (GNN-PSO) was designed. Experiments show that under the strict constraint of task delay loss %, 38% of the base stations in the entire network can enter the intelligent sleep state. The opportunistic wireless charging reduces the average grid electricity consumption of eVTOL per flight by 27.4% under idealized line-of-sight conditions (equivalent to 0.92 kg carbon reduction at the theoretical upper bound), achieved through 8–15 minute hovering windows at designated vertiports where RF beam power transfer supplements battery reserves. Under practical deployment assumptions-accounting for 3 dB cable/feed loss, 2 dB impedance mismatch, 40% effective aperture utilization due to eVTOL fuselage curvature and attitude variation, and a regulatory EIRP ceiling of 47 dBm (3 dB below the theoretical 50 dBm limit for the 3.5 GHz band in urban China)-the net DC power drops to 0.68 kW at 10 m, yielding a conservative 11.2% grid electricity reduction (0.38 kg CO₂e per flight). The 27.4% figure is retained as the Pareto-optimal theoretical upper bound for algorithm benchmarking. The system-level energy utilization rate has jumped from the benchmark 31.2% to 48.6%. Under an annual operation scale of 100,000 flights, the cumulative carbon reduction of 92 tCO₂e is equivalent to the annual sequestration of 4,200 mature broadleaf trees (22 kg CO₂e/tree/year, IPCC central estimate), with a conservative uncertainty range of [3,100, 6,100] trees accounting for species and climate variability. The research results provide deployable parametric decision-making tools and a phased carbon peak roadmap for 2025–2030 for the green operation of the low-altitude economy.</p></div> 2026-09-16T17:42:11Z Dataset Dataset 10.1371/journal.pone.0347398.t006 https://figshare.com/articles/dataset/_p_Core_modules_of_the_MATLAB_code_p_/33866771 CC BY 4.0