The Multi-Objective Optimization Design of Leaf Spring of few Piece Variable Cross-Section

Qin Man Fan; Qin Man Fan

doi:10.4028/www.scientific.net/AMR.213.231

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 213The Multi-Objective Optimization Design of Leaf...

The Multi-Objective Optimization Design of Leaf Spring of few Piece Variable Cross-Section

Abstract:

Being the ability of global optimization, MOPSO algorithm have some virtue such as high calculate velocity, good solution quality, great robustness, and so on. In allusion to a leaf spring of few piece variable cross-section, its multi-objective optimization mathematical model was built regarding minimum mass and minimum stiffness deviation as sub-objective functions. Taking the leaf spring of front suspension of a light truck as an example, the Pareto optimal solution set of optimization problem was obtained by using MOPSO algorithm. The optimization results show that the mass of the leaf spring reduced by 24.2% and the stiffness deviation is only 0.32% after optimization by using MOPSO algorithm.

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Periodical:

Advanced Materials Research (Volume 213)

Pages:

231-235

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.213.231

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Online since:

February 2011

Authors:

Qin Man Fan, Qin Man Fan

Keywords:

Leaf Spring, Multi-Objective, Optimization Design, Particle Swarm Optimization Algorithm (PSO)

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References

[1] CoelloCA, PulidoGT, LechugaMS. Handling multiple objectives with particles warm optimization, IEEE Transactions on Evolutionary Computation, vol. 8, p.256~279, Apr. (2004).

Google Scholar

[2] EberhartR, KennedyJ. A new optimizer using particles warm theory, Proc 6th Int Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, p.39~43.

Google Scholar

[3] Han ShueTan, Thomas Bradsha. Model identification of an automotive hydraulic active suspension system, Proeeedings of the American Control Conference, Albuquerque, New Mexico, June 1997, p.2920~2924.

Google Scholar

[4] Erol Sancaktar, Mathieu Gratton. Design, analysis, and optimization of composite leaf springs for light vehicle applications, Composite Structures, 1999, p.195~204.

DOI: 10.1016/s0263-8223(98)00136-6

Google Scholar

[5] K.E. Parsopoulos and M.N. Vrahatis. Particle Swarm Optimization Method in Multiobjective Problems, In Proceedings of the 2002 ACM Symposium on Applied Computing (SAC 2002), 2002, p.603~607.

DOI: 10.1145/508791.508907

Google Scholar