CLC number: TH133.31
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-04-11
Cited: 1
Clicked: 5082
Peng Guo, Jun-hong Zhang. Numerical model and multi-objective optimization analysis of vehicle vibration[J]. Journal of Zhejiang University Science A, 2017, 18(5): 393-412.
@article{title="Numerical model and multi-objective optimization analysis of vehicle vibration",
author="Peng Guo, Jun-hong Zhang",
journal="Journal of Zhejiang University Science A",
volume="18",
number="5",
pages="393-412",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1600124"
}
%0 Journal Article
%T Numerical model and multi-objective optimization analysis of vehicle vibration
%A Peng Guo
%A Jun-hong Zhang
%J Journal of Zhejiang University SCIENCE A
%V 18
%N 5
%P 393-412
%@ 1673-565X
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1600124
TY - JOUR
T1 - Numerical model and multi-objective optimization analysis of vehicle vibration
A1 - Peng Guo
A1 - Jun-hong Zhang
J0 - Journal of Zhejiang University Science A
VL - 18
IS - 5
SP - 393
EP - 412
%@ 1673-565X
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1600124
Abstract: It is crucial to conduct a study of vehicle ride comfort using a suitable physical model, and a precise and effective problem-solving method is necessary to describe possible engineering problems to obtain the best analysis of vehicle vibration based on the numerical model. This study establishes different types of vehicle models with different degrees of freedom (DOFs) that use different types of numerical methods. It is shown that results calculated using the Hamming and runge-Kutta methods are nearly the same when the system has a small number of DOFs. However, when the number is larger, the hamming method is more stable than other methods. The hamming method is multi-step, with four orders of precision. The research results show that this method can solve the vehicle vibration problem. Orthogonal experiments and multi-objective optimization are introduced to analyze and optimize the vibration of the vehicle, and the effects of the parameters on the dynamic characteristics are investigated. The solution F1 (vertical acceleration root mean square of the vehicle) reduces by 0.0352 m/s2, which is an improvement of 7.22%, and the solution F2 (dynamic load coefficient of the tire) reduces by 0.0225, which is an improvement of 6.82% after optimization. The study provides guidance for the analysis of vehicle ride comfort.
The authors presented a dynamic simulation of the different vehicle systems, a study of establishing the 2-DOF, 4-DOF, 7-DOF model were created in a simulation program.
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