Optimization of Automotive Powertrain Mounting System Based on Adaptive Genetic Algorithm

Author

Jiang-hua, Fu ; Wen-ku, Shi ; Teng, Teng ; Zu-bin, Liu

Author_Institution

State Key Lab. of Automobile Dynamic Simulation, Jilin Univ., Changchun, China

Volume

1

fYear

2009

fDate

21-22 Nov. 2009

Firstpage

347

Lastpage

350

Abstract

There are many local optimization solutions to optimize the automotive powertrain mounting system with conventional optimum algorithms which are likely to get trapped in local minima. To overcome this fault, taking the kinetic energy decoupling level as the objective function, stiffness of each mounting served as the design variable, adaptive genetic algorithm which was programmed in the MATLAB software was applied. The corresponding simulation model was built in ADAMS software to verify the result of the adaptive genetic algorithm. The optimum results show that the decoupling effect has been improved.

Keywords

automotive engineering; genetic algorithms; mechanical engineering computing; power transmission (mechanical); ADAMS software; MATLAB software; adaptive genetic algorithm; automotive powertrain mounting system; kinetic energy decoupling level; Adaptive systems; Automotive engineering; Engines; Genetic algorithms; Kinetic energy; Mathematical model; Mechanical power transmission; Optimization methods; Power system modeling; Vehicle dynamics; ADAMS; MATLAB; decoupling; genetic algorithm; mounting; optimization; powertrain;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3859-4

Type

conf

DOI

10.1109/IITA.2009.37

Filename

5369638