WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Comparative Analysis of Modulation Shapes on Laser Diode Performance with a High-Efficiency LLC Resonant Converter Driver(Wiley, 2026-02-06) Yigit, Hayri; Rifat boynuegri, Ali; Tekgun, Burak; Rifat Boynuegri, AliHigh-power laser diodes (LDs) are key components in laser-based wireless power transfer (WPT) systems, where end-to-end efficiency is one of the most critical performance metrics. This study investigates the driving performance of an LD powered by a high-efficiency LLC resonant converter under three distinct excitation waveforms-sinusoidal, triangular, and rectified-sine-using a MATLAB/SIMULINK model and an experimental setup designed to reproduce real-world operating conditions. Each waveform is synthesized through frequency modulation of a full-bridge inverter stage and filtered at the output. The analysis examines the impact of modulation shape on output current ripple, converter efficiency, and overall LD efficiency. Experimental validation confirms the simulation trends, underscoring the trade-offs between waveform smoothness, implementation complexity, and efficiency. Beyond confirming that constant-current operation yields the highest LD efficiency, this study explicitly quantifies how low-frequency current ripple induced by different modulation waveforms propagates through the LLC resonant converter, alters RMS current stress, and translates into measurable efficiency degradation at both the driver and LD levels. By experimentally correlating waveform symmetry, ripple magnitude, and loss mechanisms, the work establishes practical design boundaries for waveform-modulated laser drivers in WPT systems.Article Citation - WoS: 10Citation - Scopus: 10FEA Based Fast Topology Optimization Method for Switched Reluctance Machines(Springer, 2022-01-04) Tekgun, Didem; Tekgun, Burak; Alan, IrfanIn this paper, a finite element analysis (FEA) based fast optimization method to optimize a lightweight in-wheel switched reluctance machine is presented. This method speeds up the switched reluctance machine optimization procedure by running the FEA simulations with single-phase constant current excitations for half electrical cycle and estimating the machine performance metrics using the gathered FEA data. Hence, the machine`s dynamic performance estimation process takes shorter for each design candidate. The optimization algorithm employs designs of experiments (DOE), response surface (RS) analysis method, and differential evolution algorithm (DE). Here, the DOE method is used to reduce the search space by narrowing down the upper and lower boundaries of each design variable based on the RS analysis. Although this process does not guarantee getting the Pareto front, it places the search space close to the actual one. Hence, the multi-objective DE optimization finds the Pareto optimal solution set without requiring a large number of iterations as well as a large number of candidate designs for each iteration. The method is applied to a 24/16 SRM that is intended to be used in a lightweight race car as a hub motor. Six dimensionless geometric variables are optimized to satisfy three objective functions, namely torque ripple, motor mass, and copper loss. While the conventional DE takes at least 3000 candidate designs, the proposed method considers only 559 designs to reach a similar Pareto front. It is observed that the proposed method takes about 6 h 30 min compared to the conventional method that takes 32 h 50 min using the same computer. Therefore, the computation time is reduced almost five times with the proposed method.