Model Predictive Control with Triple Phase Shift Modulation for a Dual Active Bridge DC-DC Converter

Akbar, Seema Mir; Hasan, Ammar; Watson, Alan J.; Wheeler, Pat

Abstract

A fast dynamic response is one of the key demands for the dual active bridge (DAB) dc-dc converter to achieve a well-regulated output voltage over a wide range of operating conditions. Recently, model predictive control (MPC) has become a promising alternative to achieve fast dynamic response when compared to other classical converter control techniques. This paper presents an MPC based control approach augmented with a current stress optimized scheme based on triple phase shift (TPS) modulation to improve the dynamic performance and maintain a desired output voltage level without violating a minimum current stress constraint. A prediction model has been developed to accurately predict the dynamic behavior of the output voltage in the next horizon under the input voltage variations and load disturbances. As the model is developed using the TPS modulation thus inner phase shifts of the H-bridges as well as system's states are required to solve the formulated control problem. The inner phase shifts of the H-bridges are calculated using current stress optimized TPS scheme. Simulation and experimental results are provided to demonstrate the merits of the proposed control algorithm which includes a fast dynamic response without no overshoots in the output voltage, fixed switching frequency, low computational complexity and high degree of robustness.

Citation

Akbar, S. M., Hasan, A., Watson, A. J., & Wheeler, P. (2021). Model Predictive Control with Triple Phase Shift Modulation for a Dual Active Bridge DC-DC Converter. IEEE Access, 9, 98603-98614. https://doi.org/10.1109/ACCESS.2021.3095553

• Journal Article Type: Article
• Acceptance Date: Jul 1, 2021
• Online Publication Date: Jul 8, 2021
• Publication Date: Jul 8, 2021
• Deposit Date: Oct 4, 2021
• Publicly Available Date: Oct 4, 2021
• Journal: IEEE Access
• Electronic ISSN: 2169-3536
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Pages: 98603-98614
• DOI: https://doi.org/10.1109/ACCESS.2021.3095553
• Keywords: General Engineering; General Materials Science; General Computer Science
• Public URL: https://nottingham-repository.worktribe.com/output/5899784
• Publisher URL: https://ieeexplore.ieee.org/document/9477604