@ARTICLE{Kossowski_Tomasz_Improvement_Early,
 author={Kossowski, Tomasz and Mazur, Damian and Kwiatkowski, Bogdan and Hawro, Przemysław and Imiełowski, Andrzej},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={15323},
 howpublished={online},
 year={Early Access},
 abstract={Unmanned aerial vehicles (drones) are increasingly used in a growing number of applications, both civil and military. Their design is based on low weight, making the presence of shielding a difficult decision between safety and weight. Currently, there are no mathematical models to determine the safety of drones operating near a storm front. Lightning causes an electromagnetic wave of an impulse nature, which may pose a real threat to electronic systems. This work attempts to develop a mathematical model for simulating drones safety in terms of electromagnetic pulses using artificial intelligence-based tools. Actual measurement results collected from four drones were used as training data. They were tested in laboratory conditions using specialized measuring equipment used to test avionics in accordance with international standards such as DO-160. A repeatable surge pulse generator and a data acquisition system allowed us to collect information on how overvoltages propagate inside the drone’s systems. Systems that directly influence its operation were selected for this purpose, such as the power supply system, engine controllers, GPS system, camera and data bus lines. Other works show that most overvoltages are induced in motor coils and antennas. On this basis, a number of formulas and equations were developed to describe the most important elements of the drone, without which its correct operation will not be possible. The results of the analyzes and the mathematical model of the drone based on the examined cases are presented in this work as a complement to real experiments.},
 type={Article},
 title={Improvement of Unmanned Aerial Vehicles model under surge of Lightning Electromagnetic Pulse developed using Artificial Intelligence based on laboratory measurements in reference to classical regression methods},
 URL={http://czasopisma.pan.pl/Content/133857/PDF-MASTER/BPASTS-04634-EA.pdf},
 doi={10.24425/bpasts.2025.153423},
 keywords={machine learning, lightning discharges, mathematical model, transmittance of drone circuits},
}