Optimal design of a quadratic parameter varying vehicle suspension system using contrast-based Fruit Fly Optimisation

Stratis Kanarachos, Arash Moradinegade Dizqah, Georgios Chrysakis, Michael E. Fitzpatrick

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)
207 Downloads (Pure)


In the UK, in 2014 almost fifty thousand motorists made claims about vehicle damages caused by potholes. Pothole damage mitigation has become so important that a number of car manufacturers have officially designated it as one of their priorities. The objective is to improve suspension shock performance without degrading road holding and ride comfort. In this study, it is shown that significant improvement in performance is achieved if a clipped quadratic parameter varying suspension is employed. Optimal design of the proposed system is challenging because of the multiple local minima causing global optimisation algorithms to get trapped at local minima, located far from the optimum solution. To this end an enhanced Fruit Fly Optimisation Algorithm – based on a recent study on how well a fruit fly’s tiny brain finds food – was developed. The new algorithm is first evaluated using standard and nonstandard benchmark tests and then applied to the computationally expensive suspension design problem. The proposed algorithm is simple to use, robust and well suited for the solution of highly nonlinear problems. For the suspension design problem new insight is gained, leading to optimum damping profiles as a function of excitation level and rattle space velocity.
Original languageEnglish
Pages (from-to)463-477
Number of pages15
JournalApplied Soft Computing
Early online date11 Nov 2017
Publication statusPublished - 1 Jan 2018


  • Fruit Fly Optimisation
  • Potholes
  • Suspension design
  • Swarm intelligence

ASJC Scopus subject areas

  • Software


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