Armored vehicle floor-occupant-seat local model equivalent loading modeling method

By improving the kernel principal component analysis and Bayesian optimization methods, the problem of efficient evaluation of armored vehicle crew protection systems under explosive impact was solved, and accurate data dimensionality reduction and loading of floor node groups were achieved, thus improving evaluation efficiency and accuracy.

CN120430118BActive Publication Date: 2026-03-17NANJING UNIV OF SCI & TECH
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Patent Information

Application Number
CN202510590578.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-08
Publication Date
2026-03-17
Estimated Expiration
2045-05-08

AI Technical Summary

Technical Problem

Existing armored vehicle crew protection systems suffer from wasted computational resources and time costs in performance evaluation under blast impact. Traditional loading methods cannot accurately capture the motion anisotropy of multi-degree-of-freedom node groups on the floor, resulting in large response errors and making it difficult to perform efficient iterative optimization.

Method used

By employing an improved kernel principal component analysis method and a Bayesian optimization method, and through data dimensionality reduction and loading error quantization, the optimal coordinates of the equivalent principal component node group of the floor node group are determined, thereby achieving equivalent loading of the local finite element model.

Benefits of technology

It significantly improves the efficiency of occupant protection system performance evaluation, shortens the evaluation cycle, ensures the equivalence of loading accuracy and physical magnitude, and breaks through the engineering adaptability limitations of traditional methods.

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Abstract

This invention provides a method for equivalent loading modeling of a local model of an armored vehicle's floor, occupant, and seat. First, a whole-vehicle finite element model is constructed, and the acceleration matrix of the floor node group at the occupant's feet is extracted. The dimensionality of the floor node group acceleration matrix is ​​reduced to obtain the equivalent principal component acceleration matrix. Then, a local finite element model of the floor, occupant, and seat is extracted from the whole-vehicle finite element model. Based on this local finite element model, a joint method of time-domain response error quantization and Bayesian optimization is used to determine the coordinates of the equivalent principal component node groups in the equivalent principal component acceleration matrix. Finally, the equivalent principal component acceleration matrix of the floor node group is loaded onto the occupant's foot floor in the local finite element model, completing the modeling. This invention solves the problems of large loading errors and poor interpretability in traditional local model equivalent loading modeling methods, providing a new solution for the rapid and reliable development of vehicle occupant protection systems.
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