An automated battery management system to enable persistent missions with multiple aerial vehicles

N. Kemal Ure, Girish Chowdhary, Tuna Toksoz, Jonathan P. How, Matthew A. Vavrina, John Vian

Research output: Contribution to journalArticlepeer-review


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).

Original languageEnglish (US)
Article number6701199
Pages (from-to)275-286
Number of pages12
JournalIEEE/ASME Transactions on Mechatronics
Issue number1
StatePublished - Feb 2015
Externally publishedYes


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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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