ANALYSIS OF POWER SUPPLY SYSTEMS FOR ROBOTIC MACHINERY AND DRONES IN SMART MINES

Abstract

The rapid digital transformation of the global mining industry has accelerated the integration of robotic machinery, autonomous vehicles, and unmanned aerial systems (UAS/drones) into underground and open-pit mining operations. These systems significantly enhance safety, precision, and productivity by enabling remote task execution, real-time monitoring, and automated decision-making. However, one of the most critical factors influencing the reliability and operational continuity of smart mining technologies is the stability, adaptability, and fault tolerance of their electrical power supply systems. This paper presents a comprehensive analysis of power supply architectures for robotic equipment and drones deployed in smart mines, focusing on the performance characteristics, energy distribution methods, charging infrastructure, and safety considerations required in hazardous mining environments.

The study evaluates modern power supply strategies such as high-density lithium-ion and solid-state battery systems, wireless inductive charging platforms, tethered power solutions, and hybrid energy systems integrating renewable sources. Additionally, the reliability of underground microgrids, real-time power monitoring, and AI-based energy optimization is examined. Results from recent international research indicate that advanced battery management systems (BMS), predictive maintenance powered by AI algorithms, and ruggedized charging stations can extend operational uptime of mining robots and drones by 30–45%. Furthermore, the use of autonomous charging docks and energy-efficient motion planning reduces overall energy consumption by up to 25%.