Model Predictive Control with Load Current Feedforward for Dynamic Performance Enhancement in Two-Stage Starter-Generator System

The two-stage synchronous starter-generator (TSSG) systems have gained significant attention due to their compact structure and high power density. However, their feedback excitation mechanism suffers from slow dynamic response and complex excitation regulation. Traditional dual-PI control methods for voltage and excitation current struggle to meet high-performance requirements. To address this, this paper proposes an excitation current Model Predictive Control (MPC) strategy incorporating load current feedforward. This strategy accelerates dynamic regulation through load current feedforward, replacing the inner-loop PI controller with excitation current MPC, and integrating it with a voltage outerloop PI controller to form a composite control architecture. Simulation results demonstrate that, compared to conventional methods, the proposed approach reduces output voltage fluctuations by $3.4 \%$ and shortens settling time by $61.8 \%$ under abrupt load changes from 50 kVA to 100 kVA, significantly enhancing system dynamic response capability and stability. This method provides a novel approach for optimizing control in highly coupled excitation systems.