Multi-objective optimization of L6e electric vehicle class body structure using the MOPSO method

Authors

Faculty of Automotive Engineering, Iran University of Science and Technology

10.22044/jsfm.2025.16182.3973

Abstract

Given the increasing demand for electric vehicles, optimizing their structural design is a key engineering challenge. In this research, with the aim of achieving an optimal design for the body structure of an L6e class electric vehicle, the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been utilized. In this optimization problem, the main objective is to increase the torsional and bending stiffness of the vehicle's body structure. The dimensions of the structural beams were considered as design variables. Since the complete body structure model in Catia was not suitable for optimization due to the multiplicity of design variables, especially in connections, a simplified model was first created in Abaqus software. This model was constructed using beam elements and rigid connections to facilitate the optimization process. To validate the reliability of the simplified model, torsion and bending tests were performed on both the simplified Abaqus model and the complete Catia model, showing that the difference in stiffness was less than 4%. This result fully confirmed the reliability of the simplified model for use in the optimization process. Finally, Abaqus scripting capability allowed for the parameterization of profile dimensions, which enabled the automatic link of the model to the MOPSO optimization code in Matlab and the generation of new structures. The results of this research showed that by utilizing MOPSO multi-objective optimization, a significant simultaneous increase in the torsional stiffness (32.10%) and bending stiffness (33.79%) of the structure could be achieved, compared to the initial model before optimization.

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References

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Journal of Solid and Fluid Mechanics
Volume 15, Issue 4
September and October 2025
Pages 1-12

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