Design and control of switched reluctance motor for electric and hybrid electric vehicle application.

摘要

There is a growing interest in electric vehicle (EV) and hybrid electric vehicle (HEV) due to environmental concerns. Recent efforts are directed towards developing an improved propulsion system for EV and HEV applications. In view of this, an improved propulsion system based on switched reluctance motor (SRM) is presented.; Vehicle dynamics will be studied first to develop the propulsion system design philosophies of EV and HEV. Based on the system design philosophies, the design specifications of the SRM will be identified. Several SRM geometries with varying stator and rotor dimensions will be studied. A non-linear dynamic SRM model will be developed to calculate the control parameters which optimize the performances of the designed SRM. The steady state performances of the designed SRM will be compared for control with these optimal parameters. The effects of number of rotor and stator poles, rotor and stator pole arcs and pole heights, back iron depths etc. on the performance of the SRM will be investigated. Finally, the performances of the designed SRM will be compared with the performances of the several most commonly used motors.; To calculate the optimal control parameters in real time, artificial neural networks (ANN) will be used. Data for the training of the ANN will be obtained from the dynamic model. The dynamic model will generate the optimal control parameters for every torque demand and motor speed off-line, after series of iterations. The trained ANN will recreate these optimal control parameters on-line in real time. Simulation and experimental results will be presented to demonstrate the effectiveness of the optimal control.; The optimal control parameters calculated by the above process optimize the SRM performance for vehicle applications, however, give no attention to the torque ripple. As a consequence, the torque ripple with this control tends to be high. The high speed torque ripple is of no concern due to the high inertia of the vehicle. However, torque ripple at low speed will reduce the performance of the vehicle. To alleviate this problem, the ANN based control scheme will be modified at low speed by profiling the phase current to minimize torque ripple.