PSO-Algorithm-Based Optimal Design of LCLC Resonant Converters for Space Travelling-Wave Tube Amplifiers Applications
Bin Zhao and
Gang Wang
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Bin Zhao: Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
Gang Wang: Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
Energies, 2019, vol. 12, issue 12, 1-16
Abstract:
Due to the advantages of zero-voltage-switching (ZVS) and zero-current-switching (ZCS), LCLC resonant converters are universally applied in two-stage electronic power conditioners (EPCs) of space travelling-wave tube amplifiers (TWTAs). In two-stage EPCs, as the output voltage is regulated by the first stage, the main functions of LCLC resonant converters are to boost the input voltage, provide galvanic isolation, and maintain high efficiency. However, the total power loss of an LCLC resonant converter is very challenging because of the multiple resonant components and their mutual couplings. In order to solve this problem, in this paper, a PSO (Particle Swarm Optimization)-algorithm-based, efficiency-oriented optimal design method of an LCLC resonant converter is proposed. Based on an analysis of working principles, the total power loss (with consideration of all the power losses, including the driving loss and the conduction loss of the main switches), transformer loss, and power loss of the rectifiers is calculated. After that, the total power loss is appointed as the objective function of the PSO algorithm, where the optimal circuit parameters are derived to minimize the total power loss. After the optimal circuit parameters are obtained, an LCLC resonant converter with the desired parameters is built. Finally, the proposed PSO-algorithm-based, efficiency-oriented optimal design method is validated by an example.
Keywords: space travelling-wave tube Amplifiers; LCLC resonant converter; PSO algorithm; optimal design method; total power loss (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)
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