Optimal design of high-frequency Fe-based amorphous transformer based on genetic algorithm

Autor: Yang Xu, Lixia Chen, J. X. Zuo, K. W. He, Wei Guo
Rok vydání: 2017
Předmět:
Zdroj: 2017 IEEE 21st International Conference on Pulsed Power (PPC).
Popis: The development of power electronic transformer (PET) and high power pulse technology raises urgent need for high power high frequency (HPHF) transformers. High-frequency (HF) Fe-based amorphous transformer is a promising solution. This paper proposes an optimal design method of HF Fe-based amorphous transformer based on post-decision multiobjective genetic algorithm (GA). The optimization targets at transformer volume (expressed in terms of area product Ap) and its loss. Taking the transformer operating frequency f operating magnetic flux density B m and current density J as the design variables whereas the temperature rise and efficiency are chosen as constraints. This design method helps to solve the traditional transformer design's problem that performs repeated calculation which takes long time and cannot achieve multiobjective optimization. Moreover, it proposes to the designer a series of optimized transformer, rather than a single solution. So the designer can choose the best transformer design result according to the application needs. Finally, the simulation and experimental results are present to validate the effectiveness and feasibility of the theoretical analysis.
Databáze: OpenAIRE