Online Reactive Power Minimization and Soft Switching Algorithm for Triple-Phase-Shift Modulated Dual Active Bridge Converter

被引:20
作者
Deng, Lunbo [1 ]
Zhou, Guohua [1 ]
Bi, Qiang [1 ]
Xu, Nengmou [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 611756, Peoples R China
基金
中国国家自然科学基金;
关键词
Augmented Lagrangian method (ALM); dual active bridge (DAB) converter; efficiency improvement; reactive power minimization; triple-phase-shift (TPS) modulation; DC-DC CONVERTER; SCHEME;
D O I
10.1109/TIE.2022.3169713
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a dc microgrid, a bidirectional dc-dc converter is an essential link between voltage bus and energy storage system (ESS). When galvanic isolation and high efficiency are required, dual active bridge (DAB) converter is preferred. Due to the instability of renewable energy sources, the DAB converter may transmit high or low power to ESS. To improve the efficiency across wide power range, this article proposes a reactive power minimization and soft switching optimization algorithm that combines the augmented Lagrangian method and triple-phase-shift (TPS) modulation. Unlike an offline algorithm with look-up table, the proposed algorithm can compute phase-shift-angle online, avoiding a large database for various working conditions. A prototype with an 800 W rated power is built, and the efficiency test results validate the efficiency improvement over other TPS-based algorithms. Furthermore, a current regulation experiment demonstrates that the proposed algorithm is suitable for ESS charging, which must deal with varying output voltage and power demand.
引用
收藏
页码:2543 / 2555
页数:13
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