Brake Parameter Optimization Design Based on MOEA/D

Article Preview

Abstract:

The design level of the brake is important in ensuring the vehicles’ fast and safe running. Since the present brake parameter optimization design model can not meet the requirements of the practical application very well, this paper proposes a drum brake multi-objective optimization model aiming at minimizing the volume of the drum brake and minimizing the brake’s temperature rise. The algorithm of MOEA/D is adopted in the simulation. The simulation results indicate that the Pareto front we get is suitable for real and engineering problems, which is helpful for designers to choose appropriate parameters to optimize the brake and provides designers with great consultative value.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

484-489

Citation:

Online since:

June 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Cheng Lin, Zhang Wenming. Optimization design of mining trucks & Caliper Disc Brake[J]. Mining Rearch and Development, 2008, (01): 41-43.

Google Scholar

[2] Li Zhihua, Zhang Xuanlong, Guo Linchao. Optimal Design for CaliperDisc Brake[J]. Machine Design and Research, 2009, (02): 83-85.

Google Scholar

[3] Li Jun. Optimization Design of Tractor Brake Based on Hybrid PSO[J]. Chinese Agricutural Mechanizaion, 2011, (04): 93-96.

Google Scholar

[4] Chen Lian. Simulated Annealing Algorithm for Function Optimization and Application in Caliper-type Brake[J]. Coal Mine Machinary, 2006, (10): 38-41.

Google Scholar

[5] Liu Weixin. Structural Analysis & Design of Vehicle Brake System [M] Tsinghua University Press, (2004).

Google Scholar

[6] Chen Lian. Simulated Annealing Algorithm for Function Optimization and Application in Caliper-type Brake[J]. Coal Mine Machinary, 2006, (10): 38-41.

Google Scholar

[7] Zhang Q, Li H. MOEA/D: A multiobjective evolutionary algorithm based on decomposition[J]. Evolutionary Computation, IEEE Transactions on, 2007, 11(6): 712-731.

DOI: 10.1109/tevc.2007.892759

Google Scholar

[8] Li H, Zhang Q. Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II[J]. Evolutionary Computation, IEEE Transactions on, 2009, 13(2): 284-302.

DOI: 10.1109/tevc.2008.925798

Google Scholar

[9] Zhang Q, Liu W, Tsang E, et al. Expensive multiobjective optimization by MOEA/D with Gaussian process model[J]. Evolutionary Computation, IEEE Transactions on, 2010, 14(3): 456-474.

DOI: 10.1109/tevc.2009.2033671

Google Scholar