Global Current Stress Optimization with Direct Voltage Constraint Based Model Predictive Control for DAB Converters

Addressing the issue of excessive current stress, which significantly impacts system losses in dual active bridge (DAB) converters, remains challenging. It is primarily due to the limitations of existing current stress optimization (CSO) methods, which fail to adequately consider the physical characteristics of the system, resulting in suboptimal dynamic performance. To overcome these challenges, a global CSO with direct voltage constraint based on model predictive control (MPC) is proposed in this paper. An extended-phase-shift (EPS) modulation combined MPC for DAB converters is formulated. Furthermore, an optimization problem is constructed with the minimization of current stress as the objective, incorporating the cost function and the prediction model of voltage as constraint conditions. Karush-Kuhn-Tucker duality method (KKTDM) is developed to solve this optimization problem, which reduce the dimensionality of multiconstraint CSO problems to enhance the computational efficiency and solution precision. As a result, global optimization of current stress is achieved. The effectiveness of the proposed method in achieving global current stress optimization is validated through relevant results.