To enhance the control performance of permanent magnet synchronous motors(PMSMs)across the full speed range and address control challenges within the field-weakening region

the application of a wide-speed-range model predictive control(MPC)algorithm was explored. Grounded in the principles of explicit MPC and utilizing multi-parametric programming theory

this research transforms the complex online optimization problem of MPC into a more manageable offline optimization problem

parameterized by state variables

thereby mitigating the computational difficulties of online MPC algorithm solutions. Abandoning the intricate partitioning concepts of traditional field-weakening methods

a more intuitive field-weakening current reference strategy was introduced. A predictive model that cascades speed and current was developed

and voltage and current constraints were linearized into a polygonal form to delineate the field-weakening boundary. This ensures the motor's rapid and stable operation within high-speed regimes. Simulation and empirical validations confirm that the algorithm can swiftly identify the optimal operating point at the field-weakening boundary during runtime

with a dynamic process that is free from oscillations and overshoot. As the optimal solutions consistently remain within the constraints

system stability is ensured across an extensive range of operating speeds.