Permanent magnet passively compensated pulsed alternator (PMCPA) offers advantages of high-power density, high energy density, and compact size as a power source for electromagnetic launch systems. This paper optimizes the electromagnetic launch system driven by the PMCPA. Firstly, a complete mathematical model of the PMCPA and a simplified model of the electromagnetic launch system are established. Based on the characteristics of the electromagnetic launch system, new optimization objectives and constraints are proposed. To meet the load requirements and fully utilize the performance of the PMCPA, this paper employs a method of driving the electromagnetic launch system using two interconnected PMCPAs. To achieve better Pareto optimal solutions, the non-dominated sorting genetic algorithm-II (NSGA-II) is used and improved to some extent. Due to the strong model constraints and the tendency of the algorithm to fall into local optima, the Hammersley point set is used to generate the initial population, and adaptive boundaries and dynamic selection strategies are introduced to ensure the algorithm’s exploration capability and convergence. Finally, finite element simulations are used to verify the optimization results, and several typical discharge currents are presented.

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Modeling of Interconnected Compensated Pulse Alternators Driving Electromagnetic Launch System and Multi-objective Optimization Using NSGA-II

  • Tongyang Zhao,
  • Tao Ma,
  • Bofeng Zhu,
  • Xiao Zhang,
  • Junyong Lu

摘要

Permanent magnet passively compensated pulsed alternator (PMCPA) offers advantages of high-power density, high energy density, and compact size as a power source for electromagnetic launch systems. This paper optimizes the electromagnetic launch system driven by the PMCPA. Firstly, a complete mathematical model of the PMCPA and a simplified model of the electromagnetic launch system are established. Based on the characteristics of the electromagnetic launch system, new optimization objectives and constraints are proposed. To meet the load requirements and fully utilize the performance of the PMCPA, this paper employs a method of driving the electromagnetic launch system using two interconnected PMCPAs. To achieve better Pareto optimal solutions, the non-dominated sorting genetic algorithm-II (NSGA-II) is used and improved to some extent. Due to the strong model constraints and the tendency of the algorithm to fall into local optima, the Hammersley point set is used to generate the initial population, and adaptive boundaries and dynamic selection strategies are introduced to ensure the algorithm’s exploration capability and convergence. Finally, finite element simulations are used to verify the optimization results, and several typical discharge currents are presented.