Modeling and Analysis of Vehicle Shimmy with Consideration of the Coupling Effects of Vehicle Body

Li, Xiaogao; Zhang, Ning; Jin, Xianjian; Chen, Nan

doi:10.1155/2019/3707416

Cited by 5 publications

(3 citation statements)

References 15 publications

(28 reference statements)

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“…where F z is the vertical load acting on the wheels, φ is the camber angle of the wheels, and the parameters p C1 , p D1 , p D2 , p BCD1 , p BCD2 , p BCD3 , p E1 , and p E2 are all constants determined for each tire. In this study, the value of φ is 0, and the values of p C1 , p D1 , p D2 , p BCD1 , p BCD2 , p BCD3 , p E1 , and p E2 are listed in Table 2 [37][38][39].…”

Section: Mathematical Modelingmentioning

confidence: 99%

An Integrated Lagrangian Modeling Method for Mechanical Systems with Memory Elements

Nie,

Liu,

Zhang

2024

Machines

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Mechanical memory elements cannot be accurately modeled using the Lagrangian method in the classical sense, since these elements are nonconservative in the plane of their non-constitutive relationships, and the system differential equations are not self-adjoint and therefore do not allow a Lagrangian formulation. To overcome this problem, the integrated Lagrangian modeling method is introduced, in which the associated conventional energies in the system are replaced by the corresponding memory state functions of the memory elements. An example, a vehicle shimmy system equipped with fluid mem-inerters, is presented to verify the improvement of modeling accuracy of mechanical systems with memory elements via the integrated Lagrangian method. The simulation results show that under pulse and random excitation, using the Lagrangian method to model the system, the values of system response indicators exhibit significant errors ranging from 5.17% to 24.54% compared with the values obtained by the integrated Lagrangian method, namely, the accurate values. In addition, the influencing factors of the error and are discussed and the fractional-order memory elements and their modeling are also briefly generalized.

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Section: Mathematical Modelingmentioning

confidence: 99%

An Integrated Lagrangian Modeling Method for Mechanical Systems with Memory Elements

Nie,

Liu,

Zhang

2024

Machines

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“…To further analyze the influence of the sprung mass on vehicle shimmy, some scholars have also established different shimmy models with more DOF. The influence of the parameters, such as the road adhesion coefficient, wheelbase, and vehicle mass, on the dynamic stability of the nonlinear system was discussed (Li et al, 2019; Wei et al, 2017). These achievements provide good theoretical supports for further study on vehicle shimmy.…”

Section: Introductionmentioning

confidence: 99%

Modal analysis and dynamic shimmy behavior of vehicle–road system

Wei

Shi

et al. 2021

Journal of Vibration and Control

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To analyze the influence of the road roughness excitation on vehicle shimmy, a 12 degrees-of-freedom dynamic model of vehicle–road system is developed. The Hopf bifurcation theory is used to study the system stability. On this basis, the natural frequency and modal properties of the vehicle system are elaborated. It can be found that the roll mode plays a crucial role in the vehicle stability. Then, the dynamic shimmy behavior exposed to the sinusoidal and random road roughness excitations is investigated with the help of the modal analysis and the largest Lyapunov exponent. Furthermore, the numerical results are verified through the measurement results, and the influence of the front wheel track on vehicle shimmy is also examined. The results show that the decrease of the front wheel track is an effective way to attenuate vehicle shimmy for different road roughness excitations.

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“…The simulation results show that Hopf bifurcation will occur under the condition of a certain vehicle forward speed. X.G Li [15] built a 9-DOF model considering the coupled motion of the vehicle body on the basis of the 5-DOF system, and compared the two models, and found that the 9-DOF shimmy was more likely to occur in the low-speed zone. D.G Wei [16]established a mathematical model for dual-axle steering mechanism of a multi-axle vehicle considering dry friction to study the mechanism of self-excited shimmy of multi-axle vehicle with dual-axle steering mechanism.…”

Section: Introductionmentioning

confidence: 99%

Research on Shimmy Characteristics and Control Strategy of Double-Axle Steering Mechanism with Multiple Limit Cycles Considering Vehicle-Road Coupling

Zhang

Wei

Jiang

et al. 2021

Preprint

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The vehicle and the road are a coupled system, the road surface characteristics have a great influence on the vehicle's handling stability and driving safety. So in this study, A 9-DOF mathematical model of dual-axle steering mechanism considering the vehicle-road coupling is established. Taking one multi-axle vehicle with dual-axle steering mechanism for example, the numerical calculation method is used to reproduce the multiple limit-cycles shimmy, and the effects of the road adhesion coefficient on the multiple limit-cycles shimmy characteristics is analyzed. The results show that the maximum swing angles of first and second axle and the speed ranges of multiple limit-cycles shimmy occurring decrease with the road adhesion coefficient decreasing, and as the road adhesion coefficient decreases, the speed range of multiple limit-cycles occurring tend to shrink to the middle speed range(40-50km/h) which is multi-axle vehicles often travelling. In addition, we also found that the multiple limit-cycles shimmy characteristic of the dual-axle steering mechanism is more sensitive to the change of the road adhesion coefficient of second axle than the change of the road adhesion coefficient of first axle. This finding can provide theoretical guidance for suppressing multiple limit-cycles shimmy of multi-axle vehicle with dual-axle steering mechanism. Finally, we propose a control strategy for the multiple limit cycle shimmy phenomenon, which reduces the amplitude of the shimmy and the interval of multiple limit cycles.

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Modeling and Analysis of Vehicle Shimmy with Consideration of the Coupling Effects of Vehicle Body

Cited by 5 publications

References 15 publications

An Integrated Lagrangian Modeling Method for Mechanical Systems with Memory Elements

An Integrated Lagrangian Modeling Method for Mechanical Systems with Memory Elements

Modal analysis and dynamic shimmy behavior of vehicle–road system

Research on Shimmy Characteristics and Control Strategy of Double-Axle Steering Mechanism with Multiple Limit Cycles Considering Vehicle-Road Coupling

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