Multi-Variable Optimization Framework for Converters: Enhancing Single-Point and CEC-Weighted Efficiency

This paper presents a comprehensive optimization framework for enhancing the efficiency of a power converter through the simultaneous tuning of key design variables, including dead time, snubber capacitance, gate resistances, and gate drive voltages. Detailed loss modeling is performed for Silicon (Si) and Gallium-Nitride (GaN) devices, incorporating hard and soft switching behaviors, reverse conduction losses, gate drive losses, and core losses. Unlike conventional approaches that only focus on conduction and/or switching loss minimization, the proposed method targets single-point efficiency as the optimization objective function under varying load conditions. The optimization ensures thermal constraints are satisfied by integrating iterative thermal modeling within the loss calculation loop. Simulation and experimental results validate the proposed methodology across multiple power levels, including Single point 1 kW, 4 kW, and California Energy Commission (CEC)-weighted efficiency targets. The results demonstrate that dynamic dead time adjustment and coordinated snubber-gate optimization significantly improve efficiency and reduce switching losses. The optimized converter achieved a peak efficiency of 98.88% at 4 kW and maintained high performance across the full load range, confirming its applicability for high-frequency power conversion in electric vehicle chargers and energy storage systems.