<p>Presently, internal combustion engines provide power to move the majority of vehicles on the roadway. While battery-powered electric vehicles provide an alternative, their widespread acceptance is hindered by range anxiety and longer charging/refueling times. Dynamic wireless power transfer (DWPT) has been proposed as a means to reduce both range anxiety and charging/refueling times. In DWPT, power is provided to a vehicle in motion using electromagnetic fields transmitted by a transmitter embedded within the roadway to a receiver at the underside of the vehicle. For commercial vehicles, DWPT often requires transferring hundreds of kW through a relatively large airgap (> 20 cm). This requires a high-power DC-AC converter at the transmitting end and a DC-AC converter within the vehicle. </p> In this research, a focus is on the development of models that can be used to support the design of DWPT systems. These include finite element-based models of the transmitter/receiver that are used to predict power transfer, coil loss, and core loss in DWPT systems. The transmitter/receiver models are coupled to behavioral models of power electronic converters to predict converter efficiency, mass, and volume based upon switching frequency, transmitter/receiver currents, and source voltage. To date, these models have been used to explore alternative designs for a DWPT intended to power Class 8-9 vehicles on IN interstates. Specifically, the models have been embedded within a genetic algorithm-based multi-objective optimization in which the objectives include minimizing system mass and minimizing loss. Several designs from the optimization are evaluated to consider practicality of the proposed designs.