Range-Extending Power Management Algorithms for Army Applications

Certain types of rechargeable batteries provide quick power but store less energy, while others hold more energy but release it slowly, similar to sugars and fats in biology. In this D2P2 effort, Haylon Technologies proposes to develop machine learning algorithms that allow a power management system to strategically leverage complementary battery types, dramatically extending device runtime for critical Army electronic devices. By developing algorithms to run on a "battery hybridizer" circuit, Haylon's system will allow battery packs to predictively toggle between two different types of battery cells, one to deliver power during moments of peak demand like takeoff and moments with baseline demand like hovering. This approach can significantly extend the run-time of electronic devices with variable power loads, as well as pack reliability and longevity.