Optimization of vehicle suspension system using genetic algorithm

Sikandar Khan, Mamon M. Horoub, Saifullah Shafiq, Sajid Ali, Umar Nawaz Bhatti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

The vehicle suspension system is one of the main design factors in the automobile industry that can exponentially increase the level of customers comport and satisfaction. Various design strategies can be used to get optimum values for the various parameters in the suspension system. In this paper, a passive vehicle suspension system was modeled, and the system was optimized using Genetic Algorithm (GA) optimization technique. The GA is based on natural evolution and is successfully applied to various real-world problems. The variance of the dynamic load resulting from the vibrating vehicle is taken as the performance measure (i.e., objective function) of the suspension system. During the application of GA, first appropriate mutation rate, crossover rate, and population size were evaluated which were used to calculate optimum values for the parameters in the suspension system. The optimum values for the suspension system correspond to minimum values of the settling time and maximum overshoot and thus helps in decreasing the effect of the dynamic loads by reducing the vehicle vibration.

Original languageEnglish
Title of host publication2019 IEEE 10th International Conference on Mechanical and Aerospace Engineering, ICMAE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages203-207
Number of pages5
ISBN (Electronic)9781728155357
DOIs
StatePublished - Jul 2019

Publication series

Name2019 IEEE 10th International Conference on Mechanical and Aerospace Engineering, ICMAE 2019

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Genetic algorithm
  • Optimum suspension parameters
  • Passive system
  • Vehicle suspension system

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Aerospace Engineering

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