Multi-Objective Optimization of the Switched Reluctance Motor for Improved Performance in a Heavy Hybrid Electric Vehicle Application
The goal of this research is to improve the performance of the switched reluctance motor for a heavy hybrid electric vehicle based application. In order to achieve this, the stator and rotor tooth shapes and the switching current waveforms are modified from their base values. A multi-objective optimization problem is formulated to minimize the square of the RMS current and the normalized torque ripple. The optimization is solved using a genetic algorithm and a Pareto-optimal front is obtained. Finally, a time-domain simulation is employed to study the performance of the optimal designs over a wide range of operating speeds.
Aliprantis, Purdue University.
Off-Campus Purdue Users:
To access this dissertation, please log in to our