Analysis and optimization of tracked vehicle ride comfort based on particle swarm optimization

Zhuang Tang; Zhi-an Zhang

doi:10.1117/12.2646854

7 September 2022 Analysis and optimization of tracked vehicle ride comfort based on particle swarm optimization

Zhuang Tang, Zhi-an Zhang

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 1232948 (2022) https://doi.org/10.1117/12.2646854
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

Aiming at the problems of insufficient theoretical analysis and single optimization method in the current ride comfort analysis and optimization of tracked vehicles, the mechanical model is derived and converted into a mathematical model, combined with particle swarm algorithm to realize the ride comfort analysis and optimization of tracked vehicles. The mathematical model of its 7-degree-of-freedom vibration system is established by Newton's second law, and its model is built in Simulink. The model input uses the time-domain signal of road roughness established by the filtered white noise simulation method, and the model output is the vertical vibration acceleration at the center of mass of the tracked vehicle. When the particle swarm optimization algorithm is used to optimize the equivalent stiffness and equivalent damping of the tracked vehicle suspension, the root mean square of the vertical vibration acceleration at the center of mass is used as the objective function to realize the iterative optimization of the ride comfort of the tracked vehicle. The results show that the mathematical model of the tracked vehicle is built in SIMULINK, combined with the particle swarm optimization algorithm, so that the root mean square value of the vertical vibration acceleration at the center of mass reaches the global optimal value, and the ride comfort of the tracked vehicle can be realized simply and quickly. The optimization analysis provides a reference experience for the simulation and optimization of the driving comfort of tracked vehicles.

Citation Download Citation

Zhuang Tang and Zhi-an Zhang "Analysis and optimization of tracked vehicle ride comfort based on particle swarm optimization", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 1232948 (7 September 2022); https://doi.org/10.1117/12.2646854

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KEYWORDS

Roads

Optimization (mathematics)

Particle swarm optimization

Mathematical modeling

Analytical research

Simulink

Computer simulations

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