Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle&nbsp; Via Genetic Algorithm

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Journal of Vibration and Shock ›› 2015, Vol. 34 ›› Issue (8) : 209-213.

Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle Via Genetic Algorithm

Weichao Zhuang1, Liangmo Wang1, Zhaoping Yin2, Jin Ye2, Haixiao Wu2

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Abstract

A method to optimize the powertrain mounting system is developed to improve the vibration isolation performance of the mounting system for a parallel hybrid electric vehicle. The optimization is based on the genetic algorithm with taking the six-degree-freedom decoupling of the powertrain mounting system and the reasonable allocation of natural frequency as the objective function, and the stiffness of each mounting as the design variable. This method is applied to deal with the shaking of steering wheel for a parallel hybrid electric vehi-cle in idling process. And results of dynamics simulation verify the effectiveness of the method. Furthermore, compared to Sequential Quad-ratic Programming (SQP), genetic algorithm overcomes the fault, converging on local optimum. And the decoupling of mounting system obtained from the optimization is better and reliable.

Key words

Powertrain mounting system / Energy decoupling / Optimization / Genetic Algorithm.

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Weichao Zhuang1, Liangmo Wang1, Zhaoping Yin2, Jin Ye2, Haixiao Wu2. Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle Via Genetic Algorithm[J]. Journal of Vibration and Shock, 2015, 34(8): 209-213

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