谷歌浏览器插件
订阅小程序
在清言上使用

Total Suppression of High-Frequency Transient Oscillations in Dual-Active-Bridge Series-Resonant Converter by Trajectory-Switching Modulation

IEEE Transactions on Power Electronics(2022)

引用 8|浏览16
暂无评分
摘要
Dual-active-bridge series-resonant converter (DABSRC) is increasingly used in many emerging power electronics applications requiring fast dynamic responses. However, under conventional transient phase-shift modulation strategy, DABSRC generally suffers from large-amplitude transient oscillations when its phase-shift angle is changed abruptly by a high-gain controller. These oscillations occur at the beat frequency, which results from the interaction between the switching-frequency and resonant-frequency components in the series-resonant tank during transient states. Besides incurring high voltage and current stresses on the power-stage devices, these transient oscillations also span many switching cycles between the original and new steady states and cause perturbations to the output voltage of DABSRC, thereby degrading its dynamic performance and output voltage quality. To mitigate these problems, a new transient modulation strategy, known as trajectory-switching modulation (TSM), is proposed for achieving an accurate and computationally efficient trajectory planning of the resonant voltages and currents of DABSRC during transient states, and its basic operation is to govern the transient switching patterns of the gating signals according to a simple set of closed-form equations. The proposed TSM strategy can guarantee convergence to the next new steady state within about one switching cycle and avoid needing costly sensors and complex computation for implementation, and it is inherently compatible with high-gain controllers for realizing oscillation-free fast dynamic responses.
更多
查看译文
关键词
Transient analysis,Modulation,Oscillators,Switches,Voltage,Steady-state,Hafnium,Dual-active-bridge (DAB) converter,dynamic response,phase-shift modulation,series-resonant converter,transient oscillations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要