Dynamic performance analysis and parameters perturbation study of inerter–spring–damper suspension for heavy vehicle

Xiaofeng Yang,Yujie Shen,Hongchang Li,Long Yan,Yanling Liu

doi:10.1177/1461348420962898

Abstract

Inerter, a new type of mass element, can increase the inertia of motion between two endpoints. In order to study the dynamic inertia effect of inerter–spring–damper suspension for heavy vehicle on ride comfort and road friendliness, the inerter–spring–damper suspension is applied and its mechanism is studied. This paper establishes a half vehicle model of inerter–spring–damper suspension for heavy vehicle. The parameters of inerter–spring–damper suspension for heavy vehicle are optimized by multi-objective genetic algorithm and system simulations are carried out. The parametric influence of different spring stiffness, damping coefficient, inertance, and load on suspension performance is also studied. The simulation results demonstrate that the centroid acceleration and pitch angular acceleration are improved by 24.90% and 23.54%, respectively, and the comprehensive road damage coefficient is reduced by 4.05%. The results illustrate that the inerter–spring–damper suspension can decrease the vertical vibration of vehicle suspension especially in low frequency and reduce the road damage. The analyses of suspension parameters perturbation reveal their different effect laws of the different wheels on vehicle ride comfort and road friendliness, which provide a theoretical basis for setting parameters of inerter–spring–damper suspension.

Highlights

In recent decades, with the rapid development of global economy and highway transportation, heavy vehicles as the main equipment for freight transport, their production scale, and quantity are growing rapidly
In order to improve the comprehensive performance of an ISD suspension for heavy vehicle, the multi-objective genetic algorithm is adopted as the optimization method of ISD suspension structural parameters based on establishing a half vehicle model
23.54% respectively in time domain analysis, and the working spaces of front suspension and balanced suspension are improved by 21.82% and 8.11% respectively, and the root mean square (RMS) values of dynamic tire load of front, middle, and rear wheel decrease by 7.80%, 3.50%, and 3.87%, respectively

Summary

Introduction

With the rapid development of global economy and highway transportation, heavy vehicles as the main equipment for freight transport, their production scale, and quantity are growing rapidly. In order to improve the comprehensive performance of an ISD suspension for heavy vehicle, the multi-objective genetic algorithm is adopted as the optimization method of ISD suspension structural parameters based on establishing a half vehicle model. The perturbation effects of spring stiffness, damping coefficient, inertance and load on road friendliness, and ride comfort for heavy vehicle are studied, which provides a theoretical basis for further research and coordinated control of ISD suspension for heavy vehicle. In order to improve the comprehensive performance of heavy vehicle ISD suspension, based on the establishment of half car model, multi-objective genetic algorithm is used to optimize the main parameters. T is the fitness function (unified objective function), BA(X), SWS(X), are the root mean square (RMS) values of body acceleration, suspension working space, and dynamic tire load of ISD suspension for heavy vehicle, respectively. According to Cole and Cebon,[1] the road damage coefficient J is calculated by the 95th percentile aggregate fourth power force, and its formula is

A is the standard deviation of

Findings

Conclusion