With the expansion of Wireless Rechargeable Sensor Networks (WRSNs), the charging demand for sensor nodes has increased exponentially, making it challenging for a single Wireless Charging Vehicle (WCV) to meet these requirements. This paper proposes a twin-archive interval many-objective optimization algorithm (TA-I-SPEA2) for multi-WCV scheduling problems. The model aims to optimize high-dimension objectives, including minimizing WCV travel distance, reducing communication delay, lowering node death rate, improving energy utilization efficiency, and minimizing total operational cost. To address the complexities of high-dimensional and uncertain environments, we introduce a dynamic priority evaluation mechanism that dynamically assigns new charging tasks to nearby WCVs based on the energy levels and distances of sensor nodes to the base station. A dynamic partition allocation strategy is also implemented to reassign nodes to WCVs based on their current energy levels and distances, ensuring a balanced workload distribution. The Twin-Archive mechanism enhances the diversity and convergence of the population, thereby improving the solution space exploration. Results show that our method significantly reduces node death rates, improves energy utilization, and optimizes overall network performance, outperforming traditional methods.