Validation and optimization of modular railgun model

Considering the electromagnetic railgun structure features, an applied model has been established by modularization modeling method. Because model validation plays a key role in system simulation for analysis and optimization of railgun, a novel validation method is proposed in this paper. By utilizing the railgun dynamic test and predicted data, the simulation model is validated based on theil's inequality coefficient (TIC) method. To execute sufficient validation of the model and improve reliability of the validation results, similarity theory is adopted to analyze the credibility of simulation model by comparing the characteristics of the railgun. Inspired by analytic hierarchy process (AHP) for multiple attribute decision making, we define the muzzle velocity, current peak and discharging time as evaluation index for assessing the credibility of the simulation model and then evaluation structure is established. The final synthesis results demonstrate the feasibility of the adopted validation method and the validity of the modular model. The whole system model is run under MATLAB software platform, which is divided into several main components encapsulated into classes by object-oriented technology. On the basis of the validated model, an optimization pursuing highest velocity with the constraint of the current peak and the residual current in the rail is carried out to find a set of optimal parameters for the railgun using genetic algorithm.