The optimization of Litz-wire gapped-core high-frequency transformer (LGHT) for LLC-converters is a challenging task owing to application requirements and complex relationship between multiple design-objectives and constraints. This necessitates the use… Click to show full abstract
The optimization of Litz-wire gapped-core high-frequency transformer (LGHT) for LLC-converters is a challenging task owing to application requirements and complex relationship between multiple design-objectives and constraints. This necessitates the use of multi-objective optimization-techniques to obtain trade-off design-solutions; however, these are cumbersome methods that require many iterations and resources. Therefore, this paper proposes an improved and efficient Pareto-optimization method for LGHT-design. It combines multi-objective whale-optimization algorithm (MOWOA) and analytical core-geometry factor model (OKGM)-based core and winding selection method while keeping in consideration the LLC-converter requirements. The proposed method utilizes benefits of both method-types; it obtains the best LGHT-design in shortest-time and minimum-iterations with optimized volume and losses, integrated magnetizing-inductance, and satisfied thermal-limit. The method is made resource-efficient by carefully selecting independent and necessary LGHT design-parameters as optimization variables keeping in view interdependency among the parameters and LLC-converter performance; these include peak-flux-density, LGHT design-frequency, core-window utilization-factor, core-material, and core-shape. For best design-selection, supplementary decision functions (total-loss and loss-&-volume-product) are used together with the objective functions (core-loss, winding-loss, and total-volume) to enhance the optimal Pareto-solutions diversity and to assist designers in decision-making. The method is proven via comparison with existing benchmark-methods and validated through performance demonstration of LHGT-prototype in 400VDC-to-12VDC LLC-converter.
               
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