Output Bias-Free Predictive Control of Dual Active Bridge Converters in Fuel Cell Vehicles

Dual active bridge (DAB) converters are widely used as a pivotal interface in fuel cell vehicle (FCV) electrical systems. For FCV electrical systems, which usually require precise output voltage tracking performance and fast control dynamics, model predictive control (MPC) becomes a promising alternative. Classical MPC, using popular average modeling for state prediction, will inevitably present the output voltage tracking bias, despite its fast control dynamics. This phenomenon is particularly considerably large when parameter mismatch happens (it is common in practice). To tackle this issue, in this work, we firstly derived the analytical equation of the system. Thereafter, we propose a novel output voltage tracking bias free technique. This is then realized within the FCV continuous control set model predictive control (CCS-MPC). Finally, simulation data verify that, the proposed control strategy (i) is able to eliminate the output voltage tracking bias, (ii) does not sacrifice control dynamic performance, (iii) has fixed switching frequency.