Stability-Constraining-Dichotomy-Solution-Based Model Predictive Control to Improve the Stability of Power Conversion System in the MEA

AC cascaded system is one of the basic components of the power conversion system in the modern more-electric aircraft (MEA). However, the ac cascaded system suffers from an instability problem, i.e., even if each subsystem is stable individually, the formed cascaded system may become unstable. Most of the existing stabilization methods are a linear control method, which is based on a small signal model and can only ensure small signal stability near the operation point in theory. Therefore, these existing linear stabilization methods may be ineffective to fix large-signal stability issues. In this paper, a large signal stability constraining dichotomy solution (SCDS)-based model predictive control (MPC) is proposed to improve the stability of the ac cascaded system in the MEA by the Lyapunov criteria. This approach first theoretically presents how to add the system stability item to the MPC cost function in an analytic way instead of using the traditional “experience-based” weight method. Besides, the SCDS-MPC itself is also an improvement to the existing finite control set MPC. It can realize a constant switching frequency and achieve better steady-state/dynamic current control performance. Finally, a 1.5 kW ac cascaded system is fabricated in the laboratory to verify the proposed SCDS-MPC method.