An Automated Battery Management System to Enable Persistent Missions With Multiple Aerial Vehicles

作者：Ure N Kemal^*; Chowdhary Girish; Toksoz Tuna; How Jonathan P; Vavrina Matthew A; Vian John

来源：IEEE/ASME Transactions on Mechatronics, 2015, 20(1): 275-286.

DOI：10.1109/TMECH.2013.2294805

• Battery management systems
• learning (artificial intelligence)
• Markov processes
• multiagent systems
• unmanned aerial vehicles (UAVs)

This paper presents the development and hardware implementation of an autonomous battery maintenance mechatronic system that significantly extends the operational time of battery powered small-scaled unmanned aerial vehicles (UAVs). A simultaneous change and charge approach is used to overcome the significant downtime experienced by existing charge-only approaches. The automated system quickly swaps a depleted battery of a UAV with a replenished one while simultaneously recharging several other batteries. This results in a battery maintenance system with low UAV downtime, arbitrarily extensible operation time, and a compact footprint. Hence, the system can enable multi-agent UAV missions that require persistent presence. This capability is illustrated by developing and testing in flight a centralized autonomous planning and learning algorithm that incorporates a probabilistic health model dependent on vehicle battery health that is updated during the mission, and replans to improve the performance based on the improved model. Flight test results are presented for a 3-h-long persistent mission with three UAVs that each has an endurance of 8-10 min on a single battery charge (more than 100 battery swaps).

• 出版日期2015-2
• 单位MIT