Dynamic Inductive Power Transfer Systems With Reflexive Tuning Networks Designed by Machine Learning

Abstract

This dissertation proposes a new way to make dynamic wireless charging systems more affordable. Instead of using one inverter for each transmitter coil, as is typically done, the proposed system uses a single inverter that is connected to multiple transmitter coils. This approach is made possible by reflexive tuning, which allows for high currents to be achieved only on the transmitter coil in use. The system was tested with a 50kW prototype, designed using a combination of neural networks and genetic algorithms. The prototype was tested on both automated rail and vehicle systems. The measured dc-dc efficiency with single and four transmitter coils are 90.0% and 87.9%, respectively