The Truck-Drone Hybrid Delivery Problem (TDHP), a critical derivative scenario of the Vehicle Routing Problem (VRP), centers its research on optimizing spatiotemporal coupling dynamics within logistics systems. However, energy constraints, particularly drone endurance limitations, persist as the principal bottleneck for TDHP performance. Despite rapid advancements in wireless charging technology, existing studies predominantly emphasize battery replacement strategies while overlooking the operational implications of dynamic charging scenarios. To bridge this research gap, this paper proposes a collaborative delivery model integrating real-time charging strategies. By incorporating dynamic energy constraints, the model integrates the dual functions of the truck as a mobile launch/recovery platform and an energy replenishment node, enabling real-time synergy between energy supply and route planning. The study develops a TDHP framework tailored to real-time charging operations, deriving optimal solutions across diverse operational scenarios. Through comprehensive parameter sensitivity analysis, it elucidates the impacts of charging rates, battery capacities, and other critical variables on system optimization, thereby providing theoretical foundations for technological refinement.