In recent years, wireless charging technology (WCT) has gained huge popularity among the researchers for charging the sensors in wireless rechargeable sensor networks (WRSN). In most of the existing literatures, the MC does not work perfectly and increases the chance of improper energy utilization and further responsible for early death of sensors. In this paper, we proposed a fuzzy logic-based on-demand charge scheduling algorithm using multiple MCs to address the above-mentioned issues. In our scheme, we first propose a network partitioning approach in order to balance the workload of the MCs in a dense WRSN so that they can work with minimal interference of other MCs. Next, we introduce a fuzzy-based on-demand charging model by incorporating different network parameters influencing the charging process. The scheme prevents the sensors from being starved for charge and enhance the lifetime of the network. Furthermore, the performance of the proposed scheme is tested by conducting extensive simulations. Finally, we compare our scheme with some state-of-the-art schemes on the basis of average charging latency, energy usage efficiency, and survival rate and realized the significant improvements over existing schemes.