An optimal multi-objective control architecture of PMSM drives

This study proposes an optimal multi-objective control architecture for salient permanent magnet synchronous motors (PMSM) drives. It is aimed at improving overall system performance and energy efficiency in electric vehicle applications. The Vector Model Predictive Control (V-MPC) method enhances robustness under parameter mismatches and load variations, indirectly supporting efficient energy use. In this study, a current-based rotor angle estimation is proposed to enhance the robustness during large load torque variation of the drive. The model employs a step ahead algorithm with unit delay compensation, ensuring mathematical stability and efficacy within the boundaries to manage nonlinear restraints effectively. The 4-sector modified voltage vector selection by using current error optimization is included in this work to reduce the enumeration process and improve the drive performance. This recursion-based stator-current step ahead model by using V-MPC is established to reduce ripples and harmonics in stator current. Moreover, the multi-objective cost function is able to maintain the machine variables during parameter mismatching by increasing system performance. Furthermore, the stability analysis by using Lyapunov energy function are provided in theory. The theoretical claims are validating the feasibility of the proposed scheme in the Simulink MATLAB environment.