Optimization of Nonlinear Passive Suspension System to Minimize Road Damage for Heavy Goods Vehicle

IF 0.8 4区工程技术 Q4 ACOUSTICS

International Journal of Acoustics and Vibration Pub Date : 2021-03-30 DOI:10.20855/IJAV.2020.25.11724

Shailendra Kumar, A. Medhavi, Raghuvir Kumar

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引用次数: 7

Abstract

Major contributors to the road damage are Heavy Goods Vehicles (HGV), resulting in high maintenance costs of roads. This high cost makes it necessary to look into the issue seriously for minimizing the road damage. An Automobile Engineer can reduce road damage through the efficient design of a suspension system. The design involves satisfying the two conflicting criteria of riding comfort and vehicle handling with the restriction on the suspension travel. This paper involves designing an automobile suspension system, to improve the performance of the vehicle without a significant change in the cost of the suspension system and minimize road damage. To achieve the aforesaid objective, the use of a nonlinear passive suspension is suitable as compared to a linear passive suspension system. For the analysis, a HGV model of vehicle suspension has been considered. The suspension system considered for investigation comprises of a cubical nonlinear spring and a linear damper. Road damage has been represented by the fourth power of the tire dynamic load. A genetic algorithm has been used to optimize the half truck model to minimize road damage. The solution has been obtained using MATLAB and SIMULINK.

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重型货车道路损伤最小化的非线性被动悬架系统优化

造成道路损坏的主要原因是重型货车，导致道路维护成本高。这种高昂的成本使得有必要认真研究这个问题，以最大限度地减少道路损坏。汽车工程师可以通过有效设计悬架系统来减少道路损坏。该设计涉及满足两个相互冲突的标准，即乘坐舒适性和车辆操纵性，并限制悬架行程。本文涉及设计一种汽车悬架系统，以在不显著改变悬架系统成本的情况下提高车辆性能，并最大限度地减少道路损坏。为了实现上述目的，与线性被动悬架系统相比，使用非线性被动悬架是合适的。为了进行分析，考虑了车辆悬架的HGV模型。考虑研究的悬架系统包括一个立方体非线性弹簧和一个线性阻尼器。道路损坏已经用轮胎动态载荷的四次方来表示。使用遗传算法对半卡车模型进行优化，以最大限度地减少道路损坏。利用MATLAB和SIMULINK软件对该问题进行了求解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Acoustics and Vibration ACOUSTICS-ENGINEERING, MECHANICAL

CiteScore

1.60

自引率

10.00%

发文量

审稿时长

12 months

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