An Optimal Multi-Objective Control Architecture of PMSM Drives

This study represents a substantial progression in electric vehicles (EV) motor control, providing an optimal method to improve battery span and overall system behaviour in salient permanent magnet synchronous motors (PMSM). So, to enhance the parameter robustness of PMSMs with isolated DC power sources, a vector model predictive current control (V-MPC) method is proposed. In this study, a speed sensor-less control scheme 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.