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A Maximum Incompatibility Constrained Collaborative Optimization Method for Vehicle Weight Reduction
Technical Paper
2018-01-0585
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Collaborative optimization is an important design tool in complex vehicle system engineering. However, there are many problems yet to be resolved when applying the conventional collaborative optimization method in vehicle body weight reduction, such as convergence difficulties and low optimization efficiency. To solve these problems, a maximum incompatibility constrained collaborative optimization method is proposed in the paper. First, the 1-norm equality constraints expression of the system level is used to replace the traditional 2-norm inequality constraints. Then, a maximum incompatibility is selected from modified inequality constraints to improve optimization efficiency. Finally, an overall compatibility constraint is introduced to decrease the influence caused by the initial point. A mathematical example is used to verify the effectiveness and stability of the proposed method. The proposed collaborative optimization method is further demonstrated through a vehicle body weight reduction problem concerning vehicle safety and NVH performances.
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Citation
Dong, W., Zhan, Z., Chen, C., Fang, Y. et al., "A Maximum Incompatibility Constrained Collaborative Optimization Method for Vehicle Weight Reduction," SAE Technical Paper 2018-01-0585, 2018, https://doi.org/10.4271/2018-01-0585.Data Sets - Support Documents
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References
- Xu, H.,Chuang, C., andYang, R. , “A Data Mining-Based Strategy for Direct Multidisciplinary Optimization,” SAE Int. J. Mater. Manf. 8(2):357-363, 2015, doi:10.4271/2015-01-0479.
- Kodiyalam, S.,Yang, R.J.,Gu, L., andTho, C.H. , “Multidisciplinary Design Optimization of a Vehicle System in a Scalable, High Performance Computing Environment,” Structural & Multidisciplinary Optimization 26(3):256-263, 2003, doi:10.1007/s00158-003-0343-2.
- Tappeta, R.V. andRenaud, J.E. , “Multi-Objective Collaborative Optimization,” Journal of Mechanical Design 119(3):403-411, 1997, doi:10.1115/1.2826362.
- Sobieski, I.P.,Kroo, I.M.,Sobieski, I.P., andKroo, I.M. , “Collaborative Optimization Using Response Surface Estimation,” AIAA Journal 38(10):1931-1938, 2000, doi:10.2514/2.847.
- Li, X.,Li, W., andLiu, C. , “Geometric Analysis of Collaborative Optimization,” Structural & Multidisciplinary Optimization 35(4):301-313, 2008, doi:10.1007/s00158-007-0127-1.
- Ji, A.,Yin, X., andYuan, M. , “Hybrid Collaborative Optimization Based on Selection Strategy of Initial Point and Adaptive Relaxation,” Journal of Mechanical Science & Technology 29(9):3841-3854, 2015, doi:10.1007/s12206-015-0830-6.
- Lin, J.G.G. , “Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design,” AIAA Journal 42(2):348-360, 2004, doi:10.2514/1.9098.
- Jang, B.S.,Yang, Y.S.,Jung, H.S., andYeun, Y.S. , “Managing Approximation Models in Collaborative Optimization,” Structural & Multidisciplinary Optimization 30(1):11-26, 2005, doi:10.1007/s00158-004-0492-y.
- Li, H.,Ma, M., andZhang, W. , “Improving Collaborative Optimization for MDO Problems with Multi-Objective Subsystems,” Structural & Multidisciplinary Optimization 49(4):609-620, 2013, doi:10.1007/s00158-013-0995-5.
- Demiguel, A. V., andMurray, W. , “An Analysis of Collaborative Optimization Methods,” Symposium on Multidisciplinary Analysis and Optimization, 2013, doi:10.2514/6.2000-4720.
- Alexandrov, N.M. andLewis, R.M. , “Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design,” AIAA Journal 40(2):301-309, 2002, doi:10.2514/2.1646.
- Yang, L. andWang, D. , “Modified Collaborative Optimization for Feasibility Problem of Final Solution,” Structural & Multidisciplinary Optimization 56(5):1109-1123, 2017, doi:10.1007/s00158-017-1706-4.
- Liu, B.,Yang, J.,Zhan, Z.,Zheng, L. et al. , “An Enhanced Input Uncertainty Representation Method for Response Surface Models in Automotive Weight Reduction Applications,” SAE Int. J. Mater. Manf. 8(3):616-622, 2015, doi:10.4271/2015-01-0423.
- Zhu, P.,Pan, F.,Chen, W., andViana, F.A.C. , “Lightweight Design of Vehicle Parameters under Crashworthiness Using Conservative Surrogates,” Computers in Industry 64(3):280-289, 2013, doi:10.1016/j.compind.2012.11.004.
- Zhan, Z.,Yang, J.,Fu, Y.,Yang, R. et al. , “Research on Validation Metrics for Multiple Dynamic Response Comparison under Uncertainty,” SAE Int. J. Mater. Manf. 8(2):300-308, 2015, doi:10.4271/2015-01-0443.