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Optimal design of the floor panel for an automotive platform under uncertainty of the vehicle length

  • Lahijani, Abdolah Tavakoli (Automotive Simulation and Optimal Design Research Laboratory, School of Automotive Engineering, Iran University of Science and Technology) ;
  • Shojaeefard, M.H. (Automotive Simulation and Optimal Design Research Laboratory, School of Automotive Engineering, Iran University of Science and Technology) ;
  • Khalkhali, Abolfazl (Automotive Simulation and Optimal Design Research Laboratory, School of Automotive Engineering, Iran University of Science and Technology)
  • Received : 2016.07.25
  • Accepted : 2017.06.19
  • Published : 2018.01.20

Abstract

Length of a vehicle is an important variation to generate different variants of an automotive platform. This parameter is usually adjusted by embedding dimensional flexibility into different components of the Body in White (BIW) including the floor pan. Due to future uncertainties, it is not necessarily possible to define certain values of wheelbase for the future products of a platform. This work is performed to add flexibility into the design process of a length-variable floor pan. By means of this analysis, the cost and time consuming process of optimization is not necessary to be performed for designing the different variants of a product family. Stiffness and mass of the floor pan are two important functional requirements of this component which directly affect the occupant comfort, dynamic characteristics, fuel economy and environmental protection of the vehicle. A combination of Genetic algorithm, GMDH-type of artificial neural networks and TOPSIS methods is used to optimally design the floor pan associated with arbitrary length of the variant in the defined system range. The correlation between the optimal results shows that for a constant mass of the floor pan, the first natural frequency decreases by increasing the length of this component.

Keywords

References

  1. Guillen-Gosalbez, G. (2011), "A novel MILP-based objective reduction method for multi-objective optimization: Application to environmental problems", Comput. Chem. Eng., 35(8), 1469-1477. https://doi.org/10.1016/j.compchemeng.2011.02.001
  2. Ivakhnenko, A.G. (1971), "Polynomial theory of complex systems", IEEE Trans. Syst. Man Cyberm., 1(4), 364-378.
  3. Jamali, A., Nariman-Zadeh, N., Darvizeh, A., Masoumi, A. and Hamrang, S. (2009), "Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process", Eng. Appl. Artif. Intell., 22(4), 676-687. https://doi.org/10.1016/j.engappai.2008.11.005
  4. Khakhali, A., Nariman-Zadeh, N., Darvizeh, A., Masoumi, A. and Notghi, B. (2010), "Reliability-based robust multi-objective crashworthiness optimization of S-shaped box beams with parametric uncertainties", J. Crashworth., 15(4), 443-456. https://doi.org/10.1080/13588261003696458
  5. Khalkhali, A. and Safikhani, H. (2012), "Pareto based multiobjective optimization cyclone vortex finder using CFD, GMDH type neural networks and genetic algorithms", Eng. Optimiz., 44(1), 105-118. https://doi.org/10.1080/0305215X.2011.564619
  6. Khalkhali, A., Farajpoor, M. and Safikhani, H. (2011), "Modeling and multi-objective optimization of forward curved blades centrifugal fans using CFD and neural networks", Trans. Can. Soc. Mech. Eng., 35(1), 63-79.
  7. Khalkhali, A., Khakshournia, S. and Nariman-Zadeh, N. (2014), "A hybrid method of FEM, modified NSGAII and TOPSIS for structural optimization of sandwich panels with corrugated core", J. Sandw. Struct. Mater., 16(4), 398-417. https://doi.org/10.1177/1099636214531516
  8. Khalkhali, A., Khakshournia, S. and Saberi, P. (2016), "Optimal design of functionally graded PmPV/CNT nanocomposite cylindrical tube for purpose of torque transmission", J. Central South U., 23(2), 362-369. https://doi.org/10.1007/s11771-016-3081-5
  9. Lee, D., Gonzalez, L. F., Periaux, J., Srinivas, K. and Onate, E. (2011), "Hybrid-game strategies for multi-objective design optimization in engineering", Comput. Fluid., 47(1), 189-204. https://doi.org/10.1016/j.compfluid.2011.03.007
  10. Martin, M.V. and Ishii, K. (2002), "Design for variety: developing standardized and modularized", Res. Eng. Des., 13(4), 213-235. https://doi.org/10.1007/s00163-002-0020-2
  11. Mignery, L.A. (n.d.). Quiet steel body panel design with DAMP- A custom preprocessor utilizing MSC-PATRAN/NASTRAN.
  12. Mohan Kumar, G.R., Maruthi, B.H., Chandru, B.T. and Manoranjan, S.N. (2015), "Vibration analysis of automotive car floor using FEM and FFT analyzer", J. Tech. Res. Eng., 2(11), 2891-2896.
  13. Senthil Kumar, P., Kalidas, R., Sivakumar, K., Hariharan, E., Gautham, B. and Ethiraj, R. (2013), "Application of Taguchi method for optimizating passenger- friendly vehicle suspension system", J. Lat. Trend. Eng. Technol., 2(1).
  14. Srinivas, N. and Deb, K. (1994), "Multi-objective optimization using non-dominated sorting in genetic algorithms", Evol. Comput., 2(3), 221-248. https://doi.org/10.1162/evco.1994.2.3.221
  15. Suh, E.S. (2005), "Flexile product platforms", Ph.D. Dissertation, Massachusetts Institute of Technology, Massachusetts, U.S.A.
  16. Suh, E.S., De Weck, O., Kim, I.Y. and Chang, D. (2007), "Flexible platform component design under uncertainty", J. Intell. Manuf., 18(1), 115-126. https://doi.org/10.1007/s10845-007-0008-x
  17. Suistoranta, S. (2003), "Managing industrial products of different development stages", Proceedings of the ICED 03 14th International Conference on Engineering Design, Stockholm, Sweden, August.
  18. Sun, G., Fang, J., Tian, X., Li, G. and Li, Q. (2015), "Discrete robust optimization algorithm based on Taguchi method for structural crashworthiness design", Expert Syst. Appl., 42(9), 4482-4492. https://doi.org/10.1016/j.eswa.2014.12.054