Design of Vehicle Structural Intelligent Systems Stability and Safety Control System Based on Genetic Algorithm

Authors

  • Xia Feng College of Intelligent Equipment and Automotive Engineering, Wuxi Vocational Institute of Commerce, Wuxi, 214153, Jiangsu, China

Abstract

In the field of vehicle structural stability and safety control, traditional optimization methods lack sufficient global search capability and flexibility, making it difficult to simultaneously consider the conflicts and nonlinear relationships between various objectives in complex and multi-objective dynamic environments. In response to these issues, this study used a control system design method based on the improved SPEA2 (Strength Pareto Evolutionary Algorithm 2) to optimize suspension system parameters and power allocation strategies through a combination of elite strategy and Pareto ranking. By constructing a multi-objective optimization model, suspension stiffness, body inclination angle, and power distribution ratio were used as optimization variables, and then a dynamic weight update mechanism was introduced to address target conflicts under complex operating conditions. The experimental results showed the method proposed in this study controlled the yaw rate of the vehicle within 1.4 rad/s during sharp turns, reduced the wheel slip rate to 6.0% on slippery roads, and shortened the power response time to 2.4 seconds. This method effectively improves the dynamic performance of vehicles in complex environments, strengthening the robustness of the system and enhancing its adaptability.


Keywords: genetic algorithm optimization, vehicle stability control, safety control system, multi-objective optimization, pareto-based ranking, suspension system design

Cite As

X. Feng, " Design of Vehicle Structural Intelligent Systems Stability and Safety Control System Based on Genetic Algorithm",
Engineering Intelligent Systems, vol. 33 no. 5, pp. 525-534, 2025.

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Published

2025-09-01

Issue

Vol. 33 No. 5 (2025): International Journal of Engineering Intelligent Systems

Section

Article

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