Sensorless PMSM Drive Using Adaptive Harmonics Elimination based Modified Flux Observer with Regenerative Braking Capability for LEV Application

Author(s):  
Sumit Kumar ◽  
Bhim Singh
Author(s):  
Rafael Rivelino da Silva Bravo ◽  
Artur Tozzi C Gama ◽  
Amir Antonio Martins Oliveira ◽  
Victor Juliano De Negri

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 55
Author(s):  
Nicholas Hawkins ◽  
Bhagyashri Bhagwat ◽  
Michael L. McIntyre

In this paper, a nonlinear controller is proposed to manage the rotational speed of a full-variable Squirrel Cage Induction Generator wind turbine. This control scheme improves upon tractional vector controllers by removing the need for a rotor flux observer. Additionally, the proposed controller manages the performance through turbulent wind conditions by accounting for unmeasurable wind torque dynamics. This model-based approach utilizes a current-based control in place of traditional voltage-mode control and is validated using a Lyapunov-based stability analysis. The proposed scheme is compared to a linear vector controller through simulation results. These results demonstrate that the proposed controller is far more robust to wind turbulence than traditional control schemes.


Author(s):  
Lingying Zhao ◽  
Min Ye ◽  
Xinxin Xu

To address the comfort of an electric vehicle, a coupling mechanism between mechanical friction braking and electric regenerative braking was studied. A cooperative braking system model was established, and comprehensive simulations and system optimizations were carried out. The performance of the cooperative braking system was analyzed. The distribution of the braking force was optimized by an intelligent method, and the distribution of a braking force logic diagram based on comfort was proposed. Using an intelligent algorithm, the braking force was distributed between the two braking systems and between the driving and driven axles. The experiment based on comfort was carried out. The results show that comfort after optimization is improved by 76.29% compared with that before optimization by comparing RMS value in the time domain. The reason is that the braking force distribution strategy based on the optimization takes into account the driver’s braking demand, the maximum braking torque of the motor, and the requirements of vehicle comfort, and makes full use of the braking torque of the motor. The error between simulation results and experimental results is 5.13%, which indicates that the braking force’s distribution strategy is feasible.


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