A Model Predictive Control for Dual Active DC-DC Converter with Multi Object Optimization

被引：0
|
作者：
Deng, Yaru [1 ]
Zhong, Ming [1 ]
Yin, Shuai [1 ]
Zhu, Yutong [2 ]
Song, Wensheng [1 ]
Yang, Kexin [1 ]
机构：
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu, Peoples R China
[2] Beijing Zongheng Electromech Technol Dev Co Ltd, Beijing, Peoples R China
来源：
6TH IEEE INTERNATIONAL CONFERENCE ON PREDICTIVE CONTROL OF ELECTRICAL DRIVES AND POWER ELECTRONICS (PRECEDE 2021) | 2021年
关键词：
dual active DC-DC converters (DAB); model predictive control (MPC); virtual direct power (VDP); current stress optimization (CSO); dynamic response performance; POWER;
D O I：
10.1109/PRECEDE51386.2021.9680888
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In the application of power electronic transformers (PET), there are more and more researches on dual active DC-DC converters (DAB). In this paper, the DAB transmission power model under dual-phase-shift (DPS) control is analyzed, and a virtual direct power model predictive control (VDP-MPC) on DAB is proposed, which can effectively improve the efficiency and dynamic response performance without a current sensor. Finally, the VDP-MPC and current stress optimization (CSO) are combined, a simulation model is built on MATLAB/Simulink, and compared with the simulation model under traditional single-phase-shift (SPS) control. The simulation results show that the proposed method can improve steady-state performance, and significantly improve the dynamic response performance of DAB.
引用
收藏
页码：285 / 290
页数：6
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