Optimal Design of Tracked Armored Vehicles Firing-on-the-Move Dynamics Based on RMSTMM

The initial disturbance of the projectile is one of the primary factors affecting the firing-on-the-move accuracy of tracked armored vehicles. To reduce the initial disturbance of the projectile and enhance firing precision, an optimal design for such vehicles is essential. The application of dynamics modeling and simulation technologies significantly advances their development. Compared to ordinary dynamics methods, the Multibody System Transfer Matrix Method (MSTMM) and the Reduced Multibody System Transfer Matrix Method (RMSTMM) offer advantages such as lower-order system matrices, faster computational speed, and improved computational stability. Using the MSTMM and the RMSTMM, this study establishes a multi-rigid-flexible-body system dynamics model for firing-on-the-move of tracked armored vehicles, comprising the vehicle body subsystem and separate left/right track subsystems. Numerous factors influence the firing-on-the-move accuracy of tracked armored vehicles. A polynomial regression (PR) model is established to conduct sensitivity analysis on key parameters affecting firing-on-the-move, thereby determining design variables. One typical operating condition is selected. The optimization objectives are the lateral deflection angle, vertical deflection angle, lateral angular velocity, and vertical angular velocity at the muzzle exit of the projectile under this condition. These objectives are aggregated. The firing-on-the-move performance of tracked armored vehicles was optimized using the least squares support vector regression (LSSVR) model and genetic algorithm. Optimization results demonstrate a reduction in the initial disturbance of the projectile, confirming the feasibility of the proposed method. Furthermore, higher computational efficiency compared to ordinary methods provides a theoretical foundation for enhancing firing-on-the-move accuracy.