In wireless rechargeable sensor network (WRSN), how to efficiently collect data from sensor nodes and reduce the system energy cost is very challenging. However, most recent data collection works either cannot adapt to the large-scale rechargeable sensor network or do not take into account the sensors' energy recharging problem. They will lead to the decrease of network traffic and lifetime. Thus, aiming at the problem of data collection and network cost in WRSN, this study proposes to use the data collection vehicle (DCV) and wireless charging vehicle (WCV) to be responsible for data collection and wireless charging respectively. It can optimize data collection and ensure network continuity at the same time. Firstly, in order to improve the data collection and charging efficiency to divide the large network into several parts, this study proposes a network partition scheme based on the neighborhood similarity of sensor nodes and the distance between nodes. Then, to each part, an anchor selection scheme based on tradeoff between neighbor amount and residual energy within k hops is proposed. Next, a network cost optimization function is designed by analyzing the relationship between sensor energy consumption and network cost. The optimal sensor nodes sensing data rate and link rate are obtained by dual decomposition and sub-gradient the cost function. The results demonstrate the network can not only reduce the overall network cost but also reduce the amount of dead sensor nodes.