FCS-MPC for T-Type Three-Level Dual Three-Phase PMSM Drives with Multi-objective Decoupling Optimization

In conventional vector space decomposition coordinate system, the numerous vectors in three-level dual three-phase drives complicate vector traversal for model predictive control (MPC). Traditional MPC empirically selects candidate vectors, but it is difficult to meet all control objectives. Although weighted cost functions are widely adopted in multi-objective optimization (MOO), they introduce issues such as objective coupling and challenging weight design, hindering global optimality. Based on the multi-vector and control flexibility of the system, this paper proposes a weight-free MPC strategy with multi-objective decoupling optimization. First, dimensionality reduction analysis is conducted on basic vectors in double αβ coordinate systems. Using the mapping relationship with conventional coordinates, a set of candidate virtual vectors (VVs) with low common-mode voltage (CMV) and zero harmonic voltage is synthesized. Moreover, dynamic vector scheduling further minimizes switching actions, achieving decoupled control over harmonic suppression, CMV reduction, and switching frequency optimization during candidate vector construction. Second, to address the neutral point voltage control issue caused by the lack of redundant small vectors in the candidate set, a group of redundant VVs—equal in amplitude and phase to the original VVs but without redundant small vectors—is designed. Their output ratio is adjusted in real time via a voltage predictive model, enabling active and decoupled regulation of the neutral-point voltage. The algorithm’s effectiveness in MOO is validated through steady-state and dynamic experiments.