Model Predictive Control Based Field-Weakening Strategy for Traction EV Used Induction Motor

The field-weakening scheme is generally adopted for traction motors to achieve a wider speed range where the common proportional and integration compensator is needed to regulate the flux-producing current. However, the regulator performance deteriorates due to dc-link voltage disturbances and motor parameter nonlinearities in the different speed regions. To solve this issue, a model predictive control (MPC) based field-weakening algorithm is proposed for a traction electric vehicle using a low-voltage induction motor. The augmented prediction state relationship between stator voltage and flux-producing current is established for motor current control. The steady-state error can be eliminated with an integrator embedded within the augmented equation. The overall closed-loop control is presented where the system eigenvalues are adjusted in real time for various speed regions, and accordingly, the controller performance can be evaluated with the amplitude of the eigenvalues. Moreover, the weight coefficient in the cost function can be adjusted corresponding to speed variation for guaranteed motor control performance. The simulation and experimental results are provided to verify the proposed MPC-based field-weakening algorithm.