Wireless passive sensor networks play an important role in solving the energy limitation of nodes in the Internet of Things, and node scheduling is a significant method used to improve the energy utilization of nodes. In this work, an unused energy model based on analyzing the energy consumption characteristics of passive nodes is proposed because no unified model of passive sensor nodes is reported in previous studies. A rapid square partition clustering method is proposed according to the analysis of the relation between the sensing and communication radii of nodes, and the secondary grouping and node scheduling in each cluster are implemented to ensure the coverage rate of networks. Experimental results show that the state distribution of nodes in the proposed algorithm is favorable. The performance of the proposed algorithm is significantly affected by the P ratio between the working and charging powers of nodes. When the value of P is less than 100, the network coverage and connectivity rate are maintained at more than 95% and 90%, respectively, and are both higher than the existing algorithm.