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CFD-based Optimization for Automotive Aerodynamics

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Optimization and Computational Fluid Dynamics

Abstract

The car drag reduction problem is a major topic in the automotive industry because of its close link with fuel consumption reduction. Until recently, a computational approach of this problem was unattainable because of its complexity and its computational cost. A first attempt in this direction has been presented by the present author as part of a collaborative work with the French car manufacturer Peugeot Citroën PSA [4]. This article described the drag minimization of a simplified 3D car shape with a global optimization method that coupled a Genetic Algorithm (GA) and a second-order Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. The present chapter is intended to give a more detailed version of this work as well as its recent improvements. An overview of the main characteristics of automotive aerodynamics and a detailed presentation of the car drag reduction problem are respectively proposed in Sects. 7.1 and 7.2. Section 7.3 is devoted to the description of various fast and global optimization methods that are then applied to the drag minimization of a simplified car shape discussed in Sect. 7.4. Finally in Sect. 7.5, the chapter ends by proposing the applicability of CFD-based optimization in the field of airplane engines.

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References

  1. Ahmed, S.R., Ramm, R., Faltin, G.: Some salient features of the time averaged ground vehicle wake. SAE Paper 840300 (1984)

    Google Scholar 

  2. Beyer, H.G., Schwefel, H.P.: Evolution Strategies. Kluwer Academic Publisher (2002)

    Google Scholar 

  3. Druez, N., Dumas, L., Lecerf, N.: Adaptive hybrid optimization of aircraft engine blades. Journal of Computational and Applied Mathematics, special issue in the honnor of Hideo Kawarada 70th birthday (in press) (2007)

    Google Scholar 

  4. Dumas, L., Muyl, F., Herbert, V.: Hybrid method for aerodynamic shape optimization in automotive industry. Computers and Fluids 33, 849–858 (2004)

    Article  MATH  Google Scholar 

  5. Dumas, L., Muyl, F., Herbert, V.: Comparison of global optimization methods for drag reduction in the automotive industry. In: Lecture Notes in Computer Science, vol. 3483, pp. 948–957. Springer (2005)

    Google Scholar 

  6. Dumas, L., Muyl, F., Herbert, V.: Optimisation de forme en aérodynamique automobile. Mécanique et Industrie 6(3), 285–288 (2005)

    Article  Google Scholar 

  7. Espinoza, F., Minsker, B., Goldberg, D.E.: A self adaptive hybrid genetic algorithm. In: Proceedings of the Genetic and Evolutionary Computation Conference GECCO 2001, pp. 75–80. Morgan Kaufmann Publishers (2001)

    Google Scholar 

  8. Franck, G., Nigro, N., Storti, M., d’Elía, J.: Numerical simulation of the Ahmed vehicle model near-wake. Int. J. Num. Meth. Fluids (in press) (2007)

    Google Scholar 

  9. Giannakoglou, K.C.: Acceleration of ga using neural networks, theoretical background. GA for optimization in aeronautics and turbomachinery. In: VKI Lecture Series (2000)

    Google Scholar 

  10. Gillieron, P., Chometon, F.: Modelling of stationary three dimensional separated flows around an Ahmed reference model. In: ESAIM Proceedings. Third International Workshop on Vortex Flows and Related Numerical Methods, vol. 7, pp. 173–182 (1999)

    MATH  Google Scholar 

  11. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley (1989)

    Google Scholar 

  12. Han, T.: Computational analysis of three-dimensional turbulent flow around a bluff body in ground proximity. AIAA Journal 27(9), 1213–1219 (1988)

    Google Scholar 

  13. Han, T., Hammond, D.C., Sagi, C.J.: Optimization of bluff body for minimum drag in ground proximity. AIAA Journal 30(4), 882–889 (1992)

    Article  Google Scholar 

  14. Jin, Y.: A comprehensive survey on fitness approximation in evolutionary computation. Soft Computing 9, 3–12 (2005)

    Article  Google Scholar 

  15. Jin, Y., Olhofer, M., Sendhoff, B.: A framework for evolutionary optimization with approximate fitness functions. IEEE Transactions on Evolutionary Computation 6, 481–494 (2002)

    Article  Google Scholar 

  16. Makowski, F.T., S.-E., K.: Advances in external-aero simulation of ground vehicles using the steady RANS equations. SAE Paper 2000-01-0484 (2000)

    Google Scholar 

  17. Mohammadi, B., Pironneau, O.: Analysis of the k-ε turbulence model. John Wiley & Sons (1994)

    Google Scholar 

  18. Morel, T.: Aerodynamic drag of bluff body shapes characteristic of hatch-back cars. SAE Paper 7802670 (1978)

    Google Scholar 

  19. Ong, Y.S., Nair, P.B., Keane, A.J., Wong, K.W.: Surrogate-assisted evolutionary optimization frameworks for high-fidelity engineering design problems. In: Knowledge Incorporation in Evolutionary Computation, Studies in Fuzziness and Soft Computing Series, pp. 307–332. Springer Verlag (2004)

    Google Scholar 

  20. Poloni, C.: Hybrid GA for multi objective aerodynamic shape optimisation, Genetic algorithms in engineering and computer science. In: G. Winter, J. Périaux, M. Galan, P. Cuesta (eds.) Genetic Algorithms in Engineering and Computer Science. John Wiley & Sons, Inc., New York, NY, USA (1995)

    Google Scholar 

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Dumas, L. (2008). CFD-based Optimization for Automotive Aerodynamics. In: Thévenin, D., Janiga, G. (eds) Optimization and Computational Fluid Dynamics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72153-6_7

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  • DOI: https://doi.org/10.1007/978-3-540-72153-6_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72152-9

  • Online ISBN: 978-3-540-72153-6

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