Author(s): Ana Martínez, Carlos Hernández and Sofia Müller

Abstract: Vehicle crashworthiness is a critical aspect of automotive design, ensuring the safety of passengers during collisions. The use of computer simulation models for crashworthiness evaluation has become increasingly essential due to the complexity and high cost of physical crash tests. These models allow for the assessment of various vehicle components under crash scenarios, reducing the need for extensive physical prototypes. This paper discusses the development and application of advanced computer simulation models used in evaluating vehicle crashworthiness, focusing on the advantages, challenges, and future directions in the field. Finite element analysis (FEA) plays a central role in these simulations by enabling the prediction of vehicle behavior during impacts. The modeling of materials, vehicle structures, and occupant safety systems is essential to achieve accurate predictions. Various simulation tools and methods, including explicit and implicit solvers, are employed for different types of crashes, such as frontal, side, and rear-end collisions. Additionally, the integration of advanced occupant safety models, including the simulation of airbags and seatbelts, enhances the accuracy of crashworthiness assessments. The paper also examines the role of artificial intelligence and machine learning in enhancing the predictive capabilities of crashworthiness models. Despite significant advancements, challenges remain in terms of model validation, computational power, and the need for more comprehensive datasets. The research emphasizes the need for continuous improvements in simulation fidelity and the adoption of hybrid approaches that combine physical testing with simulation for enhanced reliability. In conclusion, computer simulation models are vital tools in modern automotive safety design, contributing to safer vehicles and more efficient development processes.

DOI: 10.22271/27078205.2026.v7.i1a.72

Pages: 24-27 | Views: 9 | Downloads: 5

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