Optimization Calculation of Single Stage Coil Launcher Based on Prediction Model

Abstract

At present, the optimization design method of electromagnetic coil launcher mainly includes of manual trial and error method and intelligent algorithm. The former has low optimization efficiency and poor effect, while the latter can obtain optimization results, but the calculation time is longer. In order to improve the calculation efficiency and obtain the global optimal solution of the coil launcher, the optimization process of the coil launcher must be improved. In this article, a genetic algorithm based on a predictive model is adopted. By using the output of the predictive model as the optimization target and constraint target of the optimization algorithm, it avoids calling the full model of the coil launcher during the optimization process and effectively reduces the calculation time. The orthogonal test method and the current filament method are used to establish 49 sets of orthogonal sample data of the single-stage coil launcher. The optimal armature speed of the coil launcher obtained in the orthogonal test is 59.81 m/s; the support vector regression (SVR) prediction model is obtained by training on the orthogonal test results, and the prediction error of the test data is 0.39%; the genetic algorithm based on the prediction model is used to optimize the single-stage coil launcher. The calculation result shows that, without constraints, the peak speed of the armature is 60.17 m/s. After the temperature constraint is added, the peak speed of the armature is 59.86 m/s.