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

Abstract

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.