Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor

  • سال انتشار: 1397
  • محل انتشار: مجله علم مهندسی خودرو، دوره: 8، شماره: 4
  • کد COI اختصاصی: JR_IJAEIU-8-4_006
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 53
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نویسندگان

Mohammad Salehpour

University of Guilan,Mechanical Engineering

Ali Jamali

University of Guilan

Ahmad Bagheri

University of Guilan

Nader N. Nariman-zadeh

University of Guilan

چکیده

In this paper, a new version of multi-objective differential evolution with dynamically adaptable mutation factor is used for Pareto optimization of a ۵-degree of freedom vehicle vibration model excited by non-stationary random road profile. In this way, non-dominated sorting algorithm and crowding distance criterion have been combined to differential evolution with fuzzified mutation in order to achieve multi-objective meta-heuristic algorithm. To dynamically tune the mutation factor, two parameters, named, number of generation and population diversity are considered as inputs and, one parameter, named, the mutation factor as output of the fuzzy logic inference system. Conflicting objective functions that have been observed to be optimally designed simultaneously are, namely, vertical seat acceleration, vertical forward tire velocity, vertical rear tire velocity, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Furthermore, different pairs of these objective functions have also been chosen for bi-objective optimization processes. The comparison of the obtained results with those in the literature unveils the superiority of the results of this work. It is displayed that the results of ۵-objective optimization subsume those of bi-objective optimization and, consequently, this achievement can offer more optimal choices to designers.

کلیدواژه ها

Five degree of freedom vehicle vibration model, Non-stationary random road, Pareto, Multi-objective optimization, Differential evolution, Fuzzified mutation

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