The selection of electric machines for an Electric Vehicle (EV) is mainly based on reliability, efficiency, and robustness, which makes the 5-phase Permanent Magnet Synchronous Motor (PMSM) among the best candidates. However, control performance of any motor drive can be deeply affected by both: (1) internal disturbances caused by parametric variations and model uncertainties and (2) external disturbances related to sensor faults or unexpected speed or torque variation. To ensure stability under those conditions, an Active Disturbance Rejection Controller (ADRC) based on an online dynamic compensation of estimated internal and external disturbances, and a Linear ADRC (LADRC) are investigated in this paper. The control performance was compared with traditional controller and evaluated by considering parametric variation, unmodeled disturbances, and speed sensor fault. The achieved results clearly highlight the effectiveness and high control performance of the proposed ADRC-based strategies.
The impact of the third order current harmonic cannot be ignored in a five-phase permanent magnet synchronous motor (PMSM), on the contrary of the three-phase PMSM. So, to realize the speed sensorless control for PMSM, a Sliding Mode Observer (SMO) is suggested with consideration the impact of third order harmonic. At the outset, a Sliding Mode Control (SMC) with injection of the third order current harmonic is designed for speed sensorless control of PMSM model for Electric Vehicle (EV). Then, Sliding Mode Observer is built to estimate the motor speed, torque and current in (d,q) frame, in order to improve the performance of sensorless control strategy. Besides, the stability of the SMC and SMO are studied using Lyapunov stability criteria. The feasibility of this technique will be evaluated using MATLAB/Simulink platform Index Terms-Five phase PMSM, Third order current harmonic, Sliding Mode Control, Sliding Mode Observer, electric vehicle.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.