# Power Sources for Unmanned Aerial Vehicles: A State-of-the Art
## 2 Unmanned Aerial Vehicle (UAV)
### Battery-Based Supply Techniques
#### 2.2.2 Swapping Method Algorithm
A Petri net model is a mathematical tool used to model and analyze systems with concurrent processes, making it relevant in designing efficient battery management systems. The authors also discussed in detail the design options for autonomous swapping stations, aiming to achieve precise UAV positioning for swapping regardless of landing errors. However, it is worth noting that the estimated swap time in their study was approximately one minute, which is relatively long compared to other studies researches. Moreover, the system was not fully operational, as certain modules were not prototyped or tested. In a separate study [57], a ground recharge station was designed for battery-powered quadrotor helicopters, and an algorithm was implemented to reduce the battery recharge duration. It can significantly reduce downtime and enhance the efficiency of quadrotor helicopters in applications like search and rescue, surveillance, delivery services, agriculture, infrastructure inspection, environmental monitoring, film production, and security. The proposed autonomous charging process utilized safer electrical contacts and a balancer specifically designed for swarm applications. It is important to mention that similar to the majority of the conducted studies, no experiments or flight tests were performed, and the study did not consider battery lifetime as a factor. An automated refueling station for small-scale UAVs was designed and implemented in a study [80] to enable long-duration autonomous missions with multi-agent UAV systems. The study developed a planning and learning algorithm and tested it in a 3 h persistent flight involving 3 UAVs and over 100 battery swaps. The battery recharger mechanism used a linear sweeping motion, resulting in a simple and robust design. However, the cost of the system was not taken into account, and it should be noted that increasing the number of batteries and UAVs could potentially lead to a more expensive and complex system to manage. In a study [81], a swapping system based on online algorithms for energy management, UAV health monitoring, and accurate landing was proposed. The system utilized a servo-based lift for battery swaps and placed the batteries onto a horizontally mounted hexagonal mat for charging. However, this swap mechanism introduced power losses in the UAVs. While individual tests were conducted for all the components, the entire system was not tested as a whole. In another study [82], an autonomous docking platform was designed using active infrared imaging. The system operated during both day and night and incorporated a camera and an infrared filter to achieve high-precision landing. In a study [73], a hardware platform was introduced featuring a dual-drum structure for efficient hot swapping of batteries. The platform included a buffer of eight batteries, and experimental work provided insights into the average time required for battery swapping. A flight test was conducted, focusing on a search and track mission with communication constraints. However, the maximum operational time achieved for this mission using the developed station with three quadrotors was approximately 70 min. In a recent paper [83], the focus was on cyclically repeated missions, such as aerial delivery services. Theyproposed the use of mobile battery swapping stations (MBS) that would move to designated swapping points according to a preset timetable. UAVs could then join the appropriate station for battery replacement and cargo loading/unloading. The study addressed the optimization of the number of UAVs and the distance traveled by proposing a declarative model for routing UAVs and MBS. However, it should be noted that this approach is applicable to only a limited range of missions, and the feasibility of mobile swapping stations may vary. The study primarily focused on the routing task, and no specific experiments related to swapping were conducted. Table 2 provides a critical analysis of the various swapping approaches discussed in the literature.