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CLC number: TH133.31

On-line Access: 2017-05-03

Received: 2016-03-30

Revision Accepted: 2016-09-26

Crosschecked: 2017-04-11

Cited: 1

Clicked: 1931

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Peng Guo

http://orcid.org/0000-0002-6454-2381

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Journal of Zhejiang University SCIENCE A 2017 Vol.18 No.5 P.393-412

10.1631/jzus.A1600124


Numerical model and multi-objective optimization analysis of vehicle vibration


Author(s):  Peng Guo, Jun-hong Zhang

Affiliation(s):  State Key Laboratory of Engine, Tianjin University, Tianjin 300072, China; more

Corresponding email(s):   pengguo@tju.edu.cn, zhangjh@tju.edu.cn

Key Words:  Vehicle model, Hamming method, Runge-Kutta method, Design of experiment, Multi-objective optimization


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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.

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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1600124"
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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.

基于数值算法的车辆动力学模型及数值求解方法精度的对比研究

目的:通过采用不同数值方法求解不同的车辆动力学模型,为车辆动力学模型研究提供参考;结合正交试验和多目标优化算法来分析各个参数对车辆性能的影响权重,采用多目标优化算法进行车辆动力学多目标优化分析,为车辆的设计提供参考依据。
创新点:研究不同数值方法的求解精度,为车辆动力学求解方法提供新途径;采用正交试验设计研究车辆各参数的影响权重,为车辆设计提供参考;采用多目标优化算法设计车辆,能兼顾车辆多个方面的性能。
方法:采用不同动力学求解算法、正交试验设计和多目标优化分析方法。
结论:1. 基于不同数值求解算法的研究表明,Hamming法要优于Newmark法和有限差分法,四阶Hamming法的精度不如龙格库塔法;2. 正交试验可得到各参数对车辆动力学的影响权重,但忽略了参数间的交互效应;3. 经过多目标优化设计,衡量车辆振动性能的两个指标分别减少了7.22%和6.82%。

关键词:车辆;Hamming法;龙格库塔法;数值算法;动力仿真

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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