International Journal of Automotive Technology

, Volume 18, Issue 6, pp 1007–1015 | Cite as

Multidisciplinary design optimization for front structure of an electric car body-in-white based on improved Collaborative Optimization method

  • Wenwei Wang
  • Fengling Gao
  • Yuting Cheng
  • Cheng Lin


In this investigation, an Improved Collaborative Optimization (ICO) method based Multidisciplinary Design Optimization (MDO) framework for front structure of an electric car body-in-white (BIW) is presented. ICO method based on 1-norm and dynamic flabby coefficient, which shows relatively high efficiency and accuracy, is first proposed here and prepared to conduct MDO in this work. Finite element analysis (FEA) results of the baseline design for an integral battery electric car body structure show that its front part needs to be optimized designed in the consideration of full-lap frontal crashworthiness. Selecting the thicknesses of 5 components, with global mass and free basic frequency constraints, a multidisciplinary size optimization problem is implemented using both ICO and standard CO methods combined with OLHS technique, metamodel and SQL algorithm. Optimal scheme based on ICO method is preferred and selected for its better performance compared with result calculated by standard CO method. The energy absorption of redesigned front body structure is finally raised by 14.2 % with 55 iterations.

Key words

Multidisciplinary design optimization Improved collaborative optimization Car body Crashworhtiness Finite element analysis 


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  1. Alexandrov, N. M. and Lewis, R. M. (2002). Analytical and computational aspects of collaborative optimization for multidisciplinary design. AIAA J. 40, 2, 301–309.CrossRefGoogle Scholar
  2. Aute, V. and Azarm, S. (2006). A genetic algorithms based approach for multidisciplinary multiobjective collaborative optimization. 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conf., Portsmouth, Virginia, 1–17.Google Scholar
  3. Cavazzuti, M., Baldini, A., Bertocchi, E., Costi, D., Torricelli, E. and Moruzz, P. (2011). High performance automotive chassis design: a topology optimization based approach. Structural and Multidisciplinary Optimization 44, 1, 45–56.CrossRefGoogle Scholar
  4. Duddeck, F. (2008). Multidisciplinary optimization of car bodies. Structural and Multidisciplinary Optimization 35, 4, 375–389.CrossRefGoogle Scholar
  5. Gao, Y. K. and Sun, F. (2011). Multi-disciplinary optimisation for front auto body based on multiple optimisation methods. Int. J. Vehicle Design 57, 2–3, 178–195.CrossRefGoogle Scholar
  6. Han, M. H. and Deng, J. (2006). Improvement of collaborative optimization. Chinese J. Mechanical Engineering 42, 11, 34–38.CrossRefGoogle Scholar
  7. Hwang, S. Y., Jeong, H. S., Kim, N. and Domblesky, J. (2016). Design process to minimize roof surface defects using a flexural function and finite element analysis. Int. J. Automotive Technology 17, 1, 127–133.CrossRefGoogle Scholar
  8. Johnson, M. E., Moore, L. M. and Ylvisaker, D. (1990). Minimax and maximin distance designs. J. Statistical Planning and Inference 26, 2, 131–148.MathSciNetCrossRefGoogle Scholar
  9. Jin, R., Chen, W. and Simpson, T. W. (2001). Comparative studies of metamodelling techniques under multiple modelling criteria. Structural and Multidisciplinary Optimization 23, 1, 1–13.CrossRefGoogle Scholar
  10. Kroo, I., Altus, S., Braun, R., Gage, P. and Sobieski, I. (1994). Multidisciplinary optimization methods for aircraft preliminary design. 5th Symp. Multidisciplinary Analysis and Optimization, 697–707.Google Scholar
  11. Li, Z. K., Xia, W. Q., Qin, X. W. and Chang, Z. H. (2014). Improvement of the safety capability on lateral collision for pure electric car. Auto Mobile Science & Technology, 1, 11–16.CrossRefGoogle Scholar
  12. Long, J. Q., Yuan, Z. P., Fu, X. F. and Zhou, S. J. (2015). A research on the body lightweighting of an extendedrange electric vehicle based on frontal crash safety. Automotive Engineering 37, 4, 466–471.Google Scholar
  13. Lin, C., Gao, F. L., Wang, W. W. and Chen, X. K. (2016). Multi-objective optimization design for a battery pack of electric vehicle with surrogate models. Int. J. Vbroengineering 18, 4, 2343–2358.CrossRefGoogle Scholar
  14. Meng, D. B., Huang, H. Z., Wang, Z. L., Xiao, N. C. and Zhang, X. L. (2014). Mean-value first-order saddlepoint approximation based collaborative optimization for multidisciplinary problems under aleatory uncertainty. J. Mechanical Science and Technology 28, 10, 3925–3935.CrossRefGoogle Scholar
  15. Nguyen, P. T. L., Lee, J. Y., Yim, H. J., Lee, S. B. and Heo, S. J. (2015). Analysis of vehicle structural performance during small-overlap frontal impact. Int. J. Automotive Technology 16, 5, 799–805.CrossRefGoogle Scholar
  16. Pedersen, C. B. W. (2004). Crashworthiness design of transient frame structures using topology optimization. Computer Methods in Applied Mechanics and Engineering 193, 6–8, 653–678.CrossRefzbMATHGoogle Scholar
  17. Su, Z. G., Long, J. Q. and Zhou, S. J. (2013). Safety simulation of rear-end collision and experimental study for extended range electric vehicle. China Mechanical Engineering 24, 7, 964–970.Google Scholar
  18. Wakayama, S. and Kroo, I. (1995). Subsonic wing planform design using multidisciplinary optimization. J. Aircraft 32, 4, 746–753.CrossRefGoogle Scholar
  19. Wen, Q. G., Song, B. W. and Wang, P. (2013). Research on several problems of collaborative optimization algorithm based on ISIGHT software. J. Northwestern Polytechnical University 31, 1, 145–148.Google Scholar
  20. Wang, Y. H. (2015). Multi-objective optimization for dynamic response of the car frame system. Int. J. Vibroengineering 17, 2, 859–869.MathSciNetGoogle Scholar
  21. Xu, H. (2014). An improved collaborative optimization algorithm. Ship Electronic Engineering 34, 7, 60–64.Google Scholar
  22. Xiao, Z., Fang, J. G., Sun, G. Y. and Li, Q. (2014). Crashworthiness design for functionally graded foamfilled bumper beam. Advances in Engineering Software, 85, 81–95.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Wenwei Wang
    • 1
    • 2
  • Fengling Gao
    • 1
    • 2
  • Yuting Cheng
    • 3
  • Cheng Lin
    • 1
    • 2
  1. 1.National Engineering Laboratory for Electric VehiclesBeijing Institute of TechnologyBeijingChina
  2. 2.Collaborative Innovation Center of Electric Vehicles in BeijingBeijingChina
  3. 3.China FAW Group Corporation R&D CenterJilinChina

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