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Parametric synthesis of two different trunk lid mechanisms for sedan vehicles using population-based optimisation algorithms.

Authors :
Yildiz, A.
Source :
Mechanism & Machine Theory. Feb2021, Vol. 156, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• Mathematical modeling of the torsional-bar and gas-spring based trunk lid mechanisms for sedan type of vehicles. • An automated structural design approach for two different trunk lid mechanisms. • Minimizing the differences between desired and calculated driving forces. • Comparing the performance of population-based PSO, GA and DE optimization algorithms. This paper proposes a parametric synthesis of two different trunk lid mechanisms for sedan vehicles, incorporating three different population-based optimization techniques: Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and the Differential Evolution (DE). For this purpose, the kinematic equations of the mechanisms are derived and implemented in the quasi-static analysis to determine the necessary driving forces. The lengths and initial angles of four-bar linkage are optimized in order to minimize the sum of the differences between the target and calculated hand force values. The optimization results of the design variables and the performances of the optimization methods are presented. The outcomes indicate that the proposed design procedure is able to provide a trunk lid mechanism in which the target value of driving force in every moving angle is achieved. Furthermore, it is observed that the optimization techniques show different performances due to the fact that they provide better and faster optimal solutions than each other for different cases. The results of this paper are of utmost importance for the manufacturer to obtain an automated design process for the trunk lid mechanisms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094114X
Volume :
156
Database :
Academic Search Index
Journal :
Mechanism & Machine Theory
Publication Type :
Academic Journal
Accession number :
147296233
Full Text :
https://doi.org/10.1016/j.mechmachtheory.2020.104130