Gravimetric Power Density and Efficiency Optimization of an Inductive Power Transfer System for UAS Applications

Inductive Power Transfer (IPT) is emerging as the preferred technology for achieving seamless, contactless charging, thereby enabling the full autonomy of Unmanned Aerial Systems (UAS). Recent research has largely focused on specific aspects of these systems, such as lightweight and compact receiver pads, yet often overlooks the gravimetric power density γ (W/g) of the entire secondary assembly. Moreover, pushing power and operating frequency limits by leveraging GaN wide-bandgap semiconductor devices has not been sufficiently explored. This article presents a comprehensive Multi-Objective Genetic Algorithm (MOGA)-based dual-objective optimization procedure that considers 14 optimization variables to maximize DC-DC system efficiency η and gravimetric density γ of two- and single-stage LCC-S IPT systems. The optimization procedure generates optimum 4-kW designs for high-power charging of 45-V LiPo batteries of a drone. At 93% efficiency, an optimum two-stage reference design (passive rectifier + interleaved buck) achieves 3.1 W/g. Adopting a GaN-based synchronous rectifier boosts γ to 3.8 W/g (18% weight reduction). Integrating the buck converter into the rectifier further reduces its weight to 4.14 W/g, a 25.3% weight reduction compared to the reference design. The optimization procedure was validated by prototyping the 4-kW reference design, achieving 90.82% measured efficiency and a power-to-weight ratio γ of 2.96 W/g. The measured total power loss and secondary assembly weight deviated from their modeled values by only 0.1% and 5%, respectively.