In this paper, we characterize the performance of and develop thermal management solutions for a DC motor-driven resonant actuator developed for flapping wing micro air vehicles. The actuator, a DC micro-gearmotor connected in parallel with a torsional spring, drives reciprocal wing motion. Compared to the gearmotor alone, this design increased torque and power density by 161.1% and 666.8%, respectively, while decreasing the drawn current by 25.8%. Characterization of the actuator, isolated from nonlinear aerodynamic loading, results in standard metrics directly comparable to other actuators. The micro-motor, selected for low weight considerations, operates at high power for limited duration due to thermal effects. To predict system performance, a lumped parameter thermal circuit model was developed. Critical model parameters for this micro-motor, two orders of magnitude smaller than those previously characterized, were identified experimentally. This included the effects of variable winding resistance, bushing friction, speed-dependent forced convection, and the addition of a heatsink. The model was then used to determine a safe operation envelope for the vehicle and to design a weight-optimal heatsink. This actuator design and thermal modeling approach could be applied more generally to improve the performance of any miniature mobile robot or device with motor-driven oscillating limbs or loads.
We investigate the effect of wing twist flexibility on lift and efficiency of a flapping-wing micro air vehicle capable of
liftoff. Wings used previously were chosen to be fully rigid due to modeling and fabrication constraints. However,
biological wings are highly flexible and other micro air vehicles have successfully utilized flexible wing structures for
specialized tasks. The goal of our study is to determine if dynamic twisting of flexible wings can increase overall
aerodynamic lift and efficiency. A flexible twisting wing design was found to increase aerodynamic efficiency by
41.3%, translational lift production by 35.3%, and the effective lift coefficient by 63.7% compared to the rigid-wing
design. These results exceed the predictions of quasi-steady blade element models, indicating the need for unsteady
computational fluid dynamics simulations of twisted flapping wings.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems