Unmanned aerial vehicles (UAVs) have a wide range of uses, including surveillance, military, disaster relief, communications, smart agriculture, and delivery. They can also be equipped with various sensors to act as sensor nodes in a sensor network to perform data collection tasks. The battery level of a UAV is of utmost importance when the trajectory of the UAV is planned. The probability distribution of the battery level of a UAV after a certain time in a stochastic setting, possibly involving solar energy harvesting, can be used in trajectory optimization. In this chapter, we present a Markov fluid queue-based analytical model for the transient distribution of the battery level. We demonstrate that the proposed method is accurate in comparison to simulations, and we present a gallery of numerical results illustrating various scenarios.