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Optimal Design of Motorcycle Rear Suspension Systems Using Genetic Algorithms

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Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 7))

Abstract

Acceleration, braking and turning capabilities are widely influenced by the parameters of the suspension systems. In this paper a geometric configuration of a rear suspension that fits a chosen target curve is obtained. The procedure followed in this study begins by choosing the topology of the rear suspension system. After that, the rear suspension characteristics are selected (highest and lowest force, progressiveness, squat ratio…). Subsequently, user-defined functions are used to obtain the position of each suspension element along the path and, later, to get the forces at each point of the system. Finally, a genetic algorithm is used to obtain an appropriate geometry of the rear suspension elements which fits the given requirements. An example is included to demonstrate the behavior and potential of the method. This strategy takes into account both the progressiveness and desired squat-ratio of the system, which have never been included in a rear suspension design before.

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References

  1. Baronti, F., Lenzi, F., Roncella, R., Saletti, R., DiTanna, O.: Electronic control of a motorcycle suspension for preload self‐adjustment. In: IEEE Transactions on Industrial Electronics, vol. 55/7, pp. 2832–2837, Jul 2008

    Google Scholar 

  2. Cossalter, V., Doria, A., Lot, R.: Optimum suspension design for motorcycle braking. Vehicle Syst. Dyn. Int. J. Veh. Mech. Mobil. 34, 175–198 (2000)

    Article  Google Scholar 

  3. Cossalter, V., Lot, R.: A motorcycle multi-body model for real time simulations based on the natural coordinates approach. Vehicle Sys. Dyn. Int. J. Veh. Mech. Mobil. 37, 423–447 (2002)

    Article  Google Scholar 

  4. Trevitt, A.: Sportbike Suspension Tuning: How to Improve Your Motorcycle’s Handling and Performance. David Bull Publishing, Phoenix (2008)

    Google Scholar 

  5. Loerch, R.R.J., Erdman, A.G., Sandor, N., Mihda, A.: Synthesis of four bar linkages with specified ground pivots. In: Proceedings of 4th Applied Mechanisms Conference, Chicago, pp. 101–106 (1975)

    Google Scholar 

  6. Han, C.: A general method for the optimum design of mechanisms. J. Mech. 1, 301–313 (1966)

    Article  Google Scholar 

  7. Krishnamurty, S., Turcic, D.A.: Optimal synthesis of mechanisms using nonlinear goal programming techniques. Mech.Mach. Theory 27(5), 599–612 (1992)

    Article  Google Scholar 

  8. Cocco, G.: Motorcycle Design and Technology. Motorbooks International, St. Paul (2004)

    Google Scholar 

  9. Cossalter, V.: Motorcycle Dynamics. LULU Press, Modena (2006)

    Google Scholar 

  10. Cabrera, J.A., Simon, A., Prado, M.: Optimal synthesis of mechanisms with genetic algorithms. Mech. Mach. Theory 37, 1165–1175 (2002)

    Article  MATH  Google Scholar 

  11. Kunjur, A., Krishnamurty, S.: Genetic algorithms in mechanical synthesis. J. Appl. Mech. Robot. 4(2), 18–24 (1997)

    Google Scholar 

  12. Storn, R., Price, K.: Differential evolution. A simple and efficient heuristic scheme for global optimization over continuous space. J. Glob. Optim. 11, 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  13. Hwang, W.-M., Shih, J.-M.: Optimal synthesis of suspension mechanism with variable leverage ratio for motorcycle. J. Chin. Soc. Mech. Eng. 8(1), 043–050 (1987)

    Google Scholar 

  14. Foale, T.: Motorcycle Handling and Chassis Design: The Art and Science. Tony Foale Designs, Benidoleig, Alicante (2006)

    Google Scholar 

  15. Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Heidelberg (2003)

    MATH  Google Scholar 

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Correspondence to J. J. Castillo .

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© 2013 Springer Science+Business Media Dordrecht

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Castillo, J.J., Giner, P., Simón, A., Cabrera, J.A. (2013). Optimal Design of Motorcycle Rear Suspension Systems Using Genetic Algorithms. In: Viadero, F., Ceccarelli, M. (eds) New Trends in Mechanism and Machine Science. Mechanisms and Machine Science, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4902-3_19

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  • DOI: https://doi.org/10.1007/978-94-007-4902-3_19

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-4901-6

  • Online ISBN: 978-94-007-4902-3

  • eBook Packages: EngineeringEngineering (R0)

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