The US Army is looking to build an autonomous charging system that can support hundreds of drones. It has funded a four-year research project with the ultimate aim of kitting out ground-based vehicles with charging stations that swarms of drones can fly to by themselves.
The University of Illinois Chicago landed an $8 million contract from the Combat Capabilities Development Command’s Army Research Laboratory. Researchers will work on a system that will enable small drones to determine the location of the closest charging station, travel there and juice up before returning to their mission. The university is working on algorithms to help the drones determine the best route to a charging port.
“Imagine in the future, the Army deploying a swarm of hundreds or thousands of unmanned aerial systems,” Dr. Mike Kweon, program manager for the Army Research Laboratory’s Versatile Tactical Power and Propulsion Essential Research Program, said in a press release. “Each of these systems has only roughly 26 minutes with the current battery technologies to conduct a flight mission and return to their home before they lose battery power, which means all of them could conceivably return at the same time to have their batteries replaced.”
Without the charging stations, soldiers would need to carry thousands of batteries on missions, which really isn’t a viable option. Using an autonomous recharging system would also mean soldiers wouldn’t have to swap out batteries manually, freeing them up for other tasks.
Army-funded researchers will also develop mini fuel-level sensors for larger drones. This would allow future drones that could partially run on petrol to detect when they’re running low on fuel, according to DroneDJ. The devices could then return to base to refuel or recharge before they run out of juice.
“This research is critical not only for air vehicles but also ground vehicles, especially for the Army missions,” Kweon said. “The fuel sensor is telling the operator what type of fuel is being delivered from the fuel tank to the engine. This input signal can be used to intelligently tell the engine to adjust engine control parameters according to the fuel type to avoid any failures. This data can also be used to find root-cause failures if any engine component prematurely failed.”