The invention discloses a switched reluctance motor structure parameter optimization method based on an adaptive fruit fly algorithm. The method comprises the steps that switched reluctance motor stator pole arc and rotor pole arc structure parameters serve as optimization objects, the motor efficiency and the torque ripple coefficient serve as optimization objects, and by achieving the collaborative optimal efficiency and torque ripple coefficient, the optimal motor structure parameters are obtained. The method has the advantages that optimizing is conducted through a dual population fruit fly algorithm, the searching capability can be effectively enhanced, and the optimization efficiency is improved; random-angle optimizing within the limited range can be given to individual fruit flies, the problem that when optimizing is conducted through a traditional fruit fly algorithm, jumping out of the stator pole arc and rotor pole arc limited border is likely to occur is solved, and the convergence speed is increased; the individual fruit flies adopt a decreasing circle optimizing mode, and the phenomenon of falling into a local optimal solution can be effectively avoided. In a word, the method has the advantages of being high in optimizing speed, high in operation efficiency, not likely to fall into the local optimal solution and the like.