This paper presents a trajectory control model using finite state machines for a single-stage soft-switching grid-tied inverter designed with a fast dynamic response. The targeted application is a module-integrated inverter for a single photovoltaic (PV) panel which interfaces distributed energy sources with the grid. To minimize switching lossd provide advanced grid-connected functionality, the soft-switching operation is achieved through a resonant filter using a trajectory control scheme. In recent years, controllers based on digital signal processing platforms have been able to handle complex and high-speed control algorithms with precision for real-time control. In real-time control applications, the finite state machine (FSM) approach enhances responsiveness by minimizing latency with limited memory resources by executing rapid state transitions. The proposed model effectively manages the switching states of the single-stage soft-switching inverters during complex DC/AC bidirectional operations. By directly controlling the energy within the series resonant circuit, the model delivers a fast transient response while minimizing switching actions across all quadrants of operation. The control scheme has been digitally implemented on a Texas Instruments (TI) digital signal processor and validated through Hardware-In-the-Loop (HIL) testing.

Litz wires are extensively employed in contemporary high-frequency switching power electronics to mitigate conductor losses. Minimizing additional winding losses caused by high-frequency phenomena, such as skin and proximity effects, is a critical design consideration for achieving high power density in modern power electronics. However, accurately predicting losses in structures composed of numerous twisted and insulated strands remains a challenge. With the increasing accessibility of commercial numerical tools, such as finite element method (FEM) solvers, simulation-based approaches have become indispensable tools for analyzing electromagnetic phenomena in complex magnetic device structures under high-frequency conditions. In parallel, data-driven modeling has emerged as a powerful method, enabling pattern identification based on datasets; however, such approaches rely on the availability of large amounts of reliable high-quality data. Generating such large-scale FEM datasets, however, is often constrained by long computation times and high memory consumption. Despite the remarkable advancements in computing power, full three-dimensional (3D) FEM analysis at the strand level for Litz wire windings often remains infeasible within personal computing environments. To address these challenges, this study presents a computationally efficient two-dimensional FEM-based framework that integrates a data-driven fitting model with optimized geometric discretization and meshing strategies, enabling accurate analysis with reduced computational load. The proposed approach, which incorporates optimal meshing conditions into commercially available 2D FEM tools and a simple data-driven fitting model, enables accurate prediction of the frequency-dependent AC resistance of multi-turn Litz windings using a typical personal computer. Its feasibility is further demonstrated through experimental frequency response measurements on both 12-turn and 21-turn windings fabricated with 150-strand Litz wire, which show strong agreement with the corrected simulation results, confirming the model’s accuracy and practical applicability.