Roll stabilisation of road vehicles using a variable stiffness suspension system

Anubi, Olugbenga Moses; Crane, Carl D.

doi:10.1080/00423114.2013.843713

Cited by 13 publications

(9 citation statements)

References 21 publications

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“…Braghin et al [9] proposed a rollover control strategy based on aerodynamic load estimation. Anubi et al [10] used variable stiffness suspension to resist vehicle lateral overturning moment. Zhu et al [11] used differential braking and synovial membrane control to control rollover of heavy vehicles, which can effectively improve rollover and yaw stability of heavy vehicles.…”

Section: Introductionmentioning

confidence: 99%

Research on a Novel Vehicle Rollover Risk Warning Algorithm Based on Support Vector Machine Model

Zhu

Yin

et al. 2020

IEEE Access

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A novel vehicle rollover warning algorithm based on support vector machine (SVM) empirical model is proposed to improve the real-time of un-tripped rollover warning algorithm and accuracy of dynamic rollover warning. Considering the nonlinear characteristic of driver-vehicle-road interaction and the uncertainty of modeling, the traditional deterministic methods cannot meet the requirements of accurate vehicle rollover warning modeling. The probability method considering issues of uncertainty is applied to design vehicle dynamic rollover warning algorithm. The SVM empirical model considers the uncertainties of the driver-vehicle-road system and the real variability of the parameters, provides an explicit function of vehicle rollover safety limit and its gradient, and utilizes the hypersurface visualization boundary to define the rollover safety area and the unsafe area. Targeting on sport utility vehicle under the condition of high-speed emergency obstacle avoidance, simulations are carried out to verify the proposed vehicle rollover warning algorithm based on SVM empirical model and of the simulation results show that the proposed algorithm has accurate warning and good real-time performance. It can effectively improve the warning accuracy of vehicle dynamic rollover, reduce the interference of nonlinear and uncertainty, and significantly improve the active safety performance with vehicle rollover prevention. INDEX TERMS rollover warning algorithm, support vector machine, empirical model TIANJUN ZHU was born in Xingtai City, Hebei province, China in 1977. He received the B.S. degree in vehicle engineering from Hebei Agricultural University, Baoding, in 2000. and M.S. degree in mechanical engineering from

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Section: Introductionmentioning

confidence: 99%

Research on a Novel Vehicle Rollover Risk Warning Algorithm Based on Support Vector Machine Model

Zhu

Yin

et al. 2020

IEEE Access

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“…When the deformation of the left and right suspensions is not the same, the torsion of bar produces a roll moment opposite to the roll direction of the vehicle body, which reduces the roll angle of the vehicle and achieves the purpose of stabilizer the body. Research shows that many rollover accidents are caused by poor dynamic performance of vehicles (Anubi and Crane Iii, 2013; Li, Yuan, Zhao and Wang, 2018; Li, Ye and Zhang, 2018; Li, Liu, Wang and Wang, 2018). Because of the complexity of driving conditions, the stabilizer bar will often be under the cyclic impact of pavement loads, and even be severely impacted by larger loads.…”

Section: Introductionmentioning

confidence: 99%

Fatigue life prediction for automobile stabilizer bar

Liu

Wang

et al. 2019

IJSI

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Purpose During the running of automobile, the stabilizer bar is frequently subjected to the impact of complex random loads, which is prone to fatigue failure and accident. In regard to this, the purpose of this paper is to study and discuss fatigue life of automobile stabilizer bar. Design/methodology/approach Durability bench test shows that failure is located at the joint of sleeve and stabilizer bar body. Based on the collection and compilation of micro-strain load spectrum of the stabilizer bar, the strain-life model is studied considering the influence of average stress and maximum stress at failure area. Seven-grade strain-life curves of the stabilizer bar are established. According to the principle of linear damage accumulation, the relationship between fatigue life and damage is discussed, then the fatigue life of stabilizer bar is predicted. Fatigue life evaluation is carried out from three aspects: reliability analysis, static analysis and fatigue life simulation. Findings The results show that the reliability of the test sample is 99.9 percent when the confidence is 90 percent and the durability is 1,073 load spectrum cycles; the ratios of predicted and simulated life to design life are 2.77 and 2.30, respectively. Originality/value Based on the road load characteristics of automobile stabilizer bar, the method of fatigue life prediction and evaluation is discussed, which provides a basis for the design and development of automobile chassis components.

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“…Most semi‐active suspension systems are designed to only vary the damping coefficient of the shock absorber while keeping the stiffness constant. Meanwhile, in suspension optimization, both the damping coefficient and the spring rate of the suspension elements are usually used as optimization arguments . Anubi et al .…”

Section: Introductionmentioning

confidence: 99%

“…Anubi et al . suggested that a semi‐active suspension system that varies both the stiffness and damping of the suspension element could provide more flexibility in balancing competing design objectives . Only few pieces of work regarding the semi‐active suspension with the variation of suspension stiffness can be found in the literature.…”

Section: Introductionmentioning

confidence: 99%

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Attitude control of full vehicle using variable stiffness suspension control

Tchamna

Lee

Youn

2014

Optim. Control Appl. Meth.

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Summary In this paper, the attitude of a ground vehicle travelling in cornering is controlled using a variable stiffness semi‐active suspension control. The main goal of the variable stiffness semi‐active suspension controller is to track as close as possible the performance of the full‐active suspension control. The work is subdivided into two main parts. At first, making use of optimal control theory, the full‐active suspension control of the full car is designed in various ways, depending on the choices of the state's variables. Afterwards, the variable stiffness control algorithm is derived based on the variable damping semi‐active control concept, except that the variable damping is now replaced by the variable stiffness mechanism. Simulation results using various types of manoeuvre show that, when external body forces are applied to the vehicle, the variable stiffness control tracks the performance of the full‐active control for high damping and stiffness coefficient, and for mild damping and stiffness coefficient, the performance of the variable stiffness control follows that of the skyhook controller. Copyright © 2014 John Wiley & Sons, Ltd.

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Roll stabilisation of road vehicles using a variable stiffness suspension system

Cited by 13 publications

References 21 publications

Research on a Novel Vehicle Rollover Risk Warning Algorithm Based on Support Vector Machine Model

Research on a Novel Vehicle Rollover Risk Warning Algorithm Based on Support Vector Machine Model

Fatigue life prediction for automobile stabilizer bar

Attitude control of full vehicle using variable stiffness suspension control

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