Vector Control Model for Permanent Magnet Synchronous Motors

The vector control model for Permanent Magnet Synchronous Motors (PMSM) represents a high-performance control strategy that achieves decoupling of torque and magnetic field through Field-Oriented Control (FOC), enabling precise motor speed regulation. The core principle involves decomposing three-phase currents into excitation (Id) and torque (Iq) components for independent control, facilitating dynamic response. In code implementation, this typically requires real-time current sampling and coordinate transformation algorithms. ### Control Structure Coordinate Transformation: Clarke and Park transforms convert three-phase stator currents into direct-axis (d-axis) and quadrature-axis (q-axis) components in a rotating reference frame, eliminating time-varying coupling. Code implementation involves matrix operations using trigonometric functions for angle tracking. Current Loop Design: PI regulators independently control Id and Iq components. Id is typically set to zero to maintain constant flux, while Iq directly correlates with motor torque. Programming requires discrete PI controller design with anti-windup protection. Speed Closed Loop: The outer loop compares speed feedback (e.g., from encoders) with target RPM, outputting Iq references through PI regulation. The inner current loop ensures fast tracking response. Implementation involves cascade control structure with prioritized current loop execution. ### Key Technical Points Field Orientation: Maintaining d-axis alignment with rotor permanent magnet flux ensures effective decoupling control, requiring accurate rotor position detection (e.g., resolver or sensorless algorithms). Flux Weakening Control: At high speeds, negative Id injection expands speed range while preventing voltage saturation, implemented through voltage constraint algorithms. Disturbance Rejection: During load transients, the speed loop rapidly adjusts Iq to maintain stability, requiring robust controller tuning with feedforward compensation techniques. This model finds extensive applications in electric vehicles and industrial servo systems, balancing dynamic performance with operational efficiency. Typical code architecture includes SVPWM generation, ADC interrupt handling, and real-time observer implementations for sensorless control variants.