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Parameter Optimization of Anti-Roll Bar Based on Stiffness
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The anti-roll bar is an important structural component of the automobile, which can effectively prevent the automobile from rolling and improve the safety of the automobile during steering. In the design of the current anti-roll bar, the stiffness is determined by empirical or oversimplified mathematical models, often not reaching the optimal value. In this paper, eight parameters are used to determine the structure of the anti-roll bar. Combining the Deformation Energy theorem and Castigliano’s theorem, a mathematical model of the stiffness is established. The optimal solution and corresponding parameter values of the mathematical model are obtained by nonlinear programming and genetic algorithm. The influence of structural parameters on the anti-roll bar stiffness is analyzed, and the regular pattern of design is obtained. In addition, the finite element method is used to verify the stiffness solution model. In the experiment, the anti-roll bar designed by the regular pattern is attached to the Baja Racing, and the stiffness of the bar is changed by adjusting the length of the arm of the bar, then the correctness of the design regular pattern is verified by testing the roll response. The improved anti-roll bar can effectively improve the anti-roll stiffness and has a better effect on the cornering stability of the automobile.
- Zhenyu Wang - Wuhan University of Technology
- Donghua Guo - Wuhan University of Technology
- Haoyu Wang - Wuhan University of Technology
- Gangfeng Tan - Suizhou-WUT Industry Research Institute
- Yifeng Jiang - Wuhan University of Technology
- Ming Li - Wuhan University of Technology
- Xiaoge Hou - Wuhan University of Technology
CitationWang, Z., Guo, D., Wang, H., Tan, G. et al., "Parameter Optimization of Anti-Roll Bar Based on Stiffness," SAE Technical Paper 2020-01-0921, 2020, https://doi.org/10.4271/2020-01-0921.
Data Sets - Support Documents
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