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Optimized Hybrid Phase-Shift Model Predictive Control for Dual Active Bridge Converters with Bayesian

delete2026-04-01
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PRE
AI
H
Hu, Cong *
C
Cheng, Ruofa
Y
Ye, Kui
DOI:10.1587/elex.23.20260139delete
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Abstract

Abstract

En 中文
This paper proposes a Hybrid Phase-Shift Optimized MPC (HPSO-MPC) strategy to enhance Dual Active Bridge (DAB) converter performance. Conventional SPS/DPS methods exhibit limited efficiency, soft-switching capability, and current stress optimization. HPSO-MPC employs model predictive control to formulate a multi-objective optimization model that minimizes current stress while improving output performance. Real-time parameter identification mitigates degradation from component mismatches, and Bayesian optimization dynamically tunes control weights. Simulation and experimental results on a 1-kW prototype validate superior performance: 92.6% peak efficiency (vs. 88.2% for SPS), 44.7% current stress reduction, and enhanced robustness across the full power range.
Keywords:
power range. key dual Active Bridge (DAB)
model predictive control
hybrid phase-shift optimization
multi-objective optimization

Journal

IEICE Electronics Express cover
IEICE Electronics Express
IF:
0.7
Papers:
204
Citations:
1.6K

Organization

N
Nanchang Hangkong University
Scholars:
7.0K
Papers: 3.9K
Citations: 81
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