Vector Control Optimization of Traction Motors Based on Online Parameter Identification

In order to further improve the accuracy of parameter identification under the fluctuation of traction motor speed (torque) and improve the speed control performance of the motor, the vector control strategy of traction motor is optimized. An online identification model of motor parameters based on recursive least squares (RLS) and model reference adaptive method (MRAS) is proposed. The motor stator and rotor parameters identified by RLS are input into MRAS on the basis of the rotor flux observation model. A proportional-integral adaptive law by use of Popov’s hyperstability theory is designed to identify the rotor resistance. Through the above optimization, the vector control strategy is optimized to realize effective control of speed regulation characteristics of traction motors in different speed intervals and under different working conditions. Consequently, the effectiveness of the proposed model and control strategy is realized and verified by simulation.