A Charging Strategy for Mining Unmanned Aerial Vehicle Based on Multi-objective Optimization

The flexibility and adaptability of unmanned aerial vehicles (UAVs) have led to their widespread application across various fields, including the mining industry. However, the unique constraints of underground mining environments, such as strict explosion-proof standards and power limitations, pose significant challenges for UAV charging strategies. Given the inability to conduct real-time battery characteristic measurements required by complex battery models in underground mining environments, this paper proposes a simplified battery modeling approach. To overcome the inadequacies of existing optimization-based charging strategies for underground mining scenarios, a novel charging control strategy is introduced. This strategy reformulates the UAV charging problem as a multi-objective optimization problem and solves it using a genetic algorithm and main objective method. Comparative simulation experiments validate that this strategy provides a rapid, safe, and efficient charging solution for mining UAVs, achieving an optimal balance between charging time and flight efficiency while reducing energy consumption.