January 27, 2021
Designing safe and workable autonomous, electric-powered flight is a complex engineering problem.
To use electric power instead of fossil fuels to fly requires systems that are light, use a minimum amount of energy, make proper flying decisions, and are safe. Even a relatively simple UAV can have hundreds of thousands of design possibilities for its power system, only a few of which are the best for maximizing safety and efficiency.
A WSU research team recently developed and used a machine learning algorithm to find the five optimal designs out of about 250,000 possible designs for an electric power system for an autonomous unmanned aerial vehicle by evaluating less than 0.05% of the designs. The work could mean time and cost savings for engineers who are seeking to solve complex engineering problems to maximize safety and sustainability. The researchers presented their work at the IEEE Energy Conversion Congress and Exposition.