The invention provides a novel torque motor structure parameter optimization method, and belongs to the field of motor intelligent optimization design. A finite element analysis system is used for conducting modeling and torque analysis on introduced structural parameters to replace traditional motor mathematical model analysis and calculation, so that errors of calculating results are small, and the accuracy is high. A weight value changing immune clonal selection algorithm is provided, after a weight value changing mechanism is used, the weight between single objective functions can be continuously adjusted along with operation of the algorithm, wherein the weights of the single objective functions close to the design demand can be changed to be small, and the weights of the single objective functions deviating from the design demand can be continuously increased. Accordingly, the convergence rate of the algorithm is increased, a large amount of unnecessary optimizing time is saved, and the optimization result is obtained more quickly. In addition, the algorithm can effectively keep the diversity of a population, global searching and local searching can be achieved simultaneously, early-maturing of evolution and falling into local minimal values of searching can be prevented, and complex non-linear problems can be solved.