A major disadvantage of switched reluctance motors is torque ripple, which causes undesirable acoustic noise and vibration. It is caused by the electromagnetic radial force. In This paper, genetic algorithms are adopted to optimize the motor structure through optimizing of the radial force mathematical model. However, the traditional genetic algorithm has some problems, such as low efficiency and no objective criterion of convergence criteria. A improved strategy based on fixed point theory is presented in this paper. Finally, through a motor example, it is concluded that the convergence speed with the improved genetic algorithm is faster, and the result of structure optimization is better.
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