This paper presents a finite element-based dynamic modeling framework for magnetically controlled transformers. The model relies on pre-solving multiple static finite element simulations and storing the resulting windings flux linkages as functions of primary, secondary, and DC biasing currents in lookup-tables. Material non-linearities and geometry 3-D effects are inherently captured within the model. This flexible modeling approach allows to model transformers with different pre-magnetization methods. Additionally, a parameterized magnetic equivalent circuit model is developed. It is shown that the model of the control winding supply affects the simulation results. Both models are validated against the results from a dual active bridge converter, showing a good agreement with the experimental measurements.

Dual active bridge (DAB) converters play a crucial role in high-power applications such as electric vehicles, renewable energy systems, and grid-tied converters due to their ability to provide bidirectional power transfer, high efficiency, and galvanic isolation. However, the pursuit of higher power density in these converters often necessitates increased operating frequencies, creating challenges in magnetic component design due to semiconductor thermal limitations. Traditional approaches, such as detailed thermal modeling and experimental methods, are time-intensive and impractical during the initial design stages. This paper presents a rapid analytical method to establish feasible operating frequencies and inductance ranges for DAB converters based on semiconductor thermal constraints, utilizing readily available device datasheet parameters and application-specific data. The proposed method omits complex thermal models and experimental procedures, streamlining the early-stage design process for magnetic components while maintaining thermal compliance. A real-time hardware-in-the-loop model was developed to validate the proposed method across power levels from 10 kW to 30 kW, demonstrating safe operation within thermal limits. The findings underscore the potential of this method to provide timely, practical guidance for magnetic designers, reducing iteration cycles and associated costs while setting the stage for further optimization and control refinement in DAB converter systems.

Inductive wireless power transfer has become one of the most important emerging technologies in electric-vehicle applications. Important parameters in such technology are the variable coupling coefficient and equivalent load resistance that depend on the relative position of the coils and the load power, respectively. These parameter values are needed to optimize the system performance. This work proposes a novel method to accurately estimate the values of coupling coefficient and load resistance dynamically without any receiver side measurements. The method is based on measuring the system input impedance seen from the transmitter side. A set of perturbation voltages with different frequencies are injected into the system, and the magnitude of the impedance obtained from measured voltage and current responses is then utilized to estimate the parameter values. The proposed method does not require communication between the transmitter and receiver subsystems, and therefore, the technique is well suited for applications in which the dynamics of the charged object are unknown. The effectiveness of the method is validated by experimental results.