Optimization Design of Electromagnetic Structure of High Frequency Transformer Based on Intelligent Optimization Algorithm
Zhao Zhigang1,2, Bai Ruonan1,2, Chen Tianyuan1,2, Jia Huijie1,2, Liu Zhaoyang1,2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300401 China; 2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300401 China
Abstract：As a core component in power conversion fields such as power electronic transformers (PET), the optimal design of high-frequency transformers (HFT) has become essential to achieving high power density, high efficiency, and high reliability. However, the significant eddy current effect and complex and compact structure under high-frequency conditions make it challenging to accurately calculate transformers’ losses and insufficient insulation design margins. Meanwhile, the multiple optimization objectives of HFT are mutually constrained yet difficult to balance, which brings severe challenges to electromagnetic design. Therefore, an electrical and magnetic field modeling method based on the analysis of high-frequency and structure effects is proposed, and a design scheme for multi-objective collaborative optimization of HFT is constructed. A core loss calculation model with low cost and high efficiency is established by fitting the complex integral function in IGSE under high-frequency non-sinusoidal excitation waveform. The calculation results of the magnetic core loss are consistent with the finite element simulation results. To achieve high-precision calculation of winding losses, an approximate Dowell model, which takes account of the structure effect and eddy current effect of windings, is derived according to the equivalence principle of area, and the impact of winding structure on winding losses is weakened. Compared with the finite element simulation results, the errors in the calculation and measurement results of winding losses of this model are all within acceptable ranges. A leakage inductance calculation model is presented considering the winding edge effect and frequency effect to reduce the dependence of leakage inductance on structure and frequency. Detailed electromagnetic finite element analysis, derivation, and experimental verification are conducted on this model, indicating that this model can accurately calculate the total leakage inductance of high-frequency transformers. To reduce the risk of insulation reliability degradation caused by thermal aging and other issues during the operation of high-frequency transformers, a novel multiple dielectric structure upgrades the insulation to withstand voltage levels between windings, considering long-term and short-term dielectric strength. At the same time, the maximum electric field strength is verified to be within a reliable safety margin through finite element simulation. The algorithm of NSGA-Ⅱ is improved by introducing dynamic clustering distance and arithmetic crossover operator, which is tested using ZDT1 and ZDT3 functions. The effectiveness of the improved scheme is verified using a mathematical model for high-frequency transformer optimization design. Finally, combined with the INSGA-Ⅱ with the free parameter scanning method, the optimization design process of HFT is established, and an HFT prototype is manufactured based on the selected optimal design. Under no-load conditions, the magnetic core loss and temperature rise of the prototype are measured. The experimental results show that the error between the measurement and simulation results of the magnetic core loss is small, and the temperature rise meets the expected design requirements without thermal operation problems.
赵志刚, 白若南, 陈天缘, 贾慧杰, 刘朝阳. 基于智能优化算法的高频变压器电磁结构优化设计[J]. 电工技术学报, 2024, 39(18): 5610-5625.
Zhao Zhigang, Bai Ruonan, Chen Tianyuan, Jia Huijie, Liu Zhaoyang. Optimization Design of Electromagnetic Structure of High Frequency Transformer Based on Intelligent Optimization Algorithm. Transactions of China Electrotechnical Society, 2024, 39(18): 5610-5625.
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2024, Vol. 39 
