Multi-mode Control Strategy for Dual Active Bridge Bidirectional DC-DC Converters

Author(s):  
Yaguang Zhang ◽  
Yong Du
2016 ◽  
Vol 104 (5) ◽  
pp. 840-854 ◽  
Author(s):  
Shen Xu ◽  
Dandan Ni ◽  
Shengli Lu ◽  
Weifeng Sun

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 3012 ◽  
Author(s):  
Zhongbin Zhao ◽  
Jing Zhang ◽  
Yu He ◽  
Ying Zhang

As renewable energy sources connecting to power systems continue to improve and new-type loads, such as electric vehicles, grow rapidly, direct current (DC) microgrids are attracting great attention in distribution networks. In order to satisfy the voltage stability requirements of island DC microgrids, the problem of inaccurate load power dispatch caused by line resistance must be solved and the defects of centralized communication and control must be overcome. A hierarchical, coordinated, multiple-mode control strategy based on the switch of different operation modes is proposed in this paper and a three-layer control structure is designed for the control strategy. Based on conventional droop control, a current-sharing layer and a multi-mode switching layer are used to ensure the stable operation of the DC microgrid. Accurate load power dispatch is satisfied using a difference discrete consensus algorithm. Furthermore, virtual bus voltage information is applied to guarantee smooth switching between various modes, which safeguards voltage stability. Simulation verification is carried out for the proposed control strategy by power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC). The results indicate that the proposed control strategy guarantees the voltage stability of island DC microgrids and accurate load power dispatch under different operation modes.


Author(s):  
Soonil Jeon ◽  
Jang-Moo Lee ◽  
Yeong-Il Park

The adaptive multi-mode control strategy (AMMCS) is defined as the control strategy that switches control parameters for the purpose of adjusting vehicles to diverse traffic conditions and driver’s habits. This strategy is composed of off-line and on-line procedures. In the off-line procedure, several sets of control parameters are optimized under representative driving patterns (RDP). In the on-line procedure, the control parameter switching or interpolation is periodically activated based on the driving pattern recognition (DPR) algorithm, assuming that the driving pattern during the future control horizon doesn’t change significantly compared to the past pattern. The AMMCS is conceptually similar to one of predictive control theories, namely the receding horizon control which is also known as model predictive control. The AMMCS is expected to be applied well to hybrid electric vehicle (HEV) system which is very sensitive to driving patterns. Furthermore, the AMMCS can be combined with the two conventional control strategies using global and local optimization techniques to improve performances further. The design goal of the AMMCS is to minimize fuel consumption and NOx for a pre-transmission single shaft parallel HEV.


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