A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Zhang, Buyang; Zong, Changfu; Chen, Guoying; Huang, Yanjun; Xu, Ting

doi:10.1186/s10033-019-0323-0

Cited by 11 publications

(14 citation statements)

References 31 publications

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“…To observe wheel forces, the model of a four-axle truck in Ref. [26] was improved in this research. This model divides the truck into three parts, where each part can be regarded as an isolated system, and two virtual forces are used to describe the connection between the parts.…”

Section: Modellingmentioning

confidence: 99%

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Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

Zhang

Wang

et al. 2021

Chin. J. Mech. Eng.

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Vertical tire forces are essential for vehicle modelling and dynamic control. However, an evaluation of the vertical tire forces on a multi-axle truck is difficult to accomplish. The current methods require a large amount of experimental data and many sensors owing to the wide variation of the parameters and the over-constraint. To simplify the design process and reduce the demand of the sensors, this paper presents a practical approach to estimating the vertical tire forces of a multi-axle truck for dynamic control. The estimation system is based on a novel vertical force model and a proposed adaptive treble extend Kalman filter (ATEKF). To adapt to the widely varying parameters, a sliding mode update is designed to make the ATEKF adaptive, and together with the use of an initial setting update and a vertical tire force adjustment, the overall system becomes more robust. In particular, the model aims to eliminate the effects of the over-constraint and the uneven weight distribution. The results show that the ATEKF method achieves an excellent performance in a vertical force evaluation, and its performance is better than that of the treble extend Kalman filter.

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Section: Modellingmentioning

confidence: 99%

“…(3)-( 5) can be obtained from Ref. [26]. Here, l s1 is the distance between the first separation point and the first axle.…”

Section: Modellingmentioning

confidence: 99%

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Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

Zhang

Wang

et al. 2021

Chin. J. Mech. Eng.

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“…Zhao et al 32 design an integrated rollover control system based on active steering and differential braking by using H∞ controller. Zhang et al 33 proposed an integrated control system specially designed for multi-axle vehicles (Differential braking and active steering). Hassan et al 34 investigated the effects of tyre characteristics on vehicular rollover and lateral stability.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode control for overturning prevention and hardware-in-loop experiment of heavy-duty vehicles based on dynamical load transfer ratio prediction

Han

Huang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part K:

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Aiming at the rollover risk of heavy-duty vehicles, an adaptive rollover prediction and control algorithm based on identification of multiple road adhesion coefficients is proposed, and the control effect has been verified by hardware-in-the-loop experiments. Based on the establishment of a 3 DOFs (Degree of freedom) vehicle dynamic model, the roll angle of the vehicle dynamic model is estimated in real time by using Kalman filter algorithm. In order to ensure the real-time operation of anti-rollover control strategy for multi-body dynamic heavy vehicle model, a sliding mode variable structure controller for anti-rollover of vehicles is designed to determine the optimal yaw moment. Specially, the recognition algorithm of road surface type is integrated into the control rollover algorithm. When the control system with road recognition algorithm recognizes whether the vehicle is in danger of rollover, it can not only adjust the state of the vehicle, but also shorten the time to reach the stable area of the vehicle's lateral load transfer rate by about 2 s. In order to further improve its adaptability and control accuracy, a Hardware-in-loop test platform for three-axis heavy-duty vehicles is built to verify the proposed anti-rollover control strategy. The results prove that the proposed control strategy can accurately predict the rollover risk and control the rollover in time.

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“…However, due to expensive equipment, mass production models will not be equipped with sensors for body sideslip angle. Therefore the currently adopted measures are utilizing some estimation methods to get body sideslip angle [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Vehicle Lateral Motion State Estimation Based on Adaptive Cubature Kalman Filter

He¹,

Zhang²,

Zhou³

et al. 2020

Preprint

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Accurate and reliable vehicle state information is very significant to the vehicle lateral stability control, while it is hard to get information such as body sideslip angle and lateral tire forces due to lack the nonlinearity of the tire. This paper presents a new combined method (adaptive cubature Kalman filter(ACKF) and adaptive proportion integral observer(APIO)) to estimate body sideslip angle, yaw rate and lateral tire force for vehicle system. Firstly, based on a four-wheel vehicle dynamics model, (ACKF) is used to estimate body sideslip angle and yaw rate with considering the nonlinear lateral tire force stage. Due to system nonlinearities and un-modeled dynamics, APIO is used to improve the estimated body sideslip angle by utilizing the estimated yaw rate and vehicle lateral speed. Then, ACKF is used to estimate the front and rear lateral tire forces based on the one-order tire dynamics model. By utilizing the partition coefficient calculated by the vertical force model, the front and rear lateral tire forces are further distributed to left and right wheels. For comparison, estimation model based on extended Kalman filter(EKF) is built and investigated. Simulation using Matlab/Simulink-CarSim and car test verifies the effectiveness of the proposed method.

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A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Cited by 11 publications

References 31 publications

Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

Sliding mode control for overturning prevention and hardware-in-loop experiment of heavy-duty vehicles based on dynamical load transfer ratio prediction

Vehicle Lateral Motion State Estimation Based on Adaptive Cubature Kalman Filter

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