Multiobjective Optimization of Multistage Synchronous Induction Coilgun Based on NSGA-II

The structure and trigger control strategy have become the most important factors that restrict the performance of the multistage synchronous induction coilgun (MSSICG). However, it is still a difficult task to design MSSICG under overload constraint due to coupling between the multiple parameters. In this paper, the maximization of the emission efficiency and acceleration stationarity is treated as a multiobjective optimization problem. By analyzing the relationship between the number of turns and the other structural parameters of the launch, the multiobjective optimization model of MSSICG is established by the current filament method which was verified by the experimental data and finite-element method. And then the second generation nondominated sorting genetic algorithm (NSGA-II) and multiobjective particle swarm optimization (MOPSO) were employed to optimize the model in order to maximize the energy transfer efficiency while achieving the smooth acceleration of the armature. With the formulated optimization model, a five-stage synchronous induction coilgun is optimized as a special case. A decision-making procedure based on the fuzzy membership function is used for obtaining best compromise solution from the set of Pareto-solutions obtained through NSGA-II and MOPSO. In addition, the optimization performance of the proposed multiobjective optimization model and the single-objective optimization model of the MSSICG was compared. The result of optimization shows that the proposed multiobjective optimization model of MSSICG can effectively improve the performance of the coilgun compared with the single-objective optimization model which takes of the launch velocity and overload acceleration as the combination objective function or only the launch velocity.