An adapted Burckhardt tire model for off-road vehicle applications

Vieira, D. J.; Orjuela, Rodolfo; Spisser, Matthias; Basset, Michel

doi:10.1016/j.jterra.2022.08.001

Cited by 12 publications

(6 citation statements)

References 20 publications

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“…Therefore, this paper designs a road adhesion coefficient estimator to realize a real-time estimation of road adhesion and improve vehicle stability and safety. Based on the tire-road mathematical model proposed by Burckhardt and its modifications [29,30], the road adhesion coefficient estimator is designed based on a fuzzy algorithm according to the adhesion coefficient and slip rate curve of a standard road.…”

Section: Torque Distribution Controller Based On Road Adhesion Coeffi...mentioning

confidence: 99%

Adaptive Stability Control Based on Sliding Model Control for BEVs Driven by In-Wheel Motors

Guo

Feng

et al. 2023

Sustainability

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High-speed and complex road conditions make it easy for vehicles to reach limit conditions, increasing the risk of instability. Consequently, there is an urgent need to solve the problem of vehicle stability and safety. In this paper, adaptive stability control is studied in BEVs driven by in-wheel motors. Based on the sliding model algorithm, a joint weighting control of the yaw rate and sideslip angle is carried out, and a weight coefficient is designed using a fuzzy algorithm to realize adaptive direct yaw moment control. Next, optimal torque distribution is designed with the minimum sum of four tire load rates as the optimization objective. Then, combined with the road adhesion coefficient and the maximum motor torque constraint, the torque distribution problem is transformed into a functionally optimal solution problem with constraints. The simulation results show that the direct yaw moment controller based on the adaptive sliding mode algorithm has a good control effect on the yaw rate and sideslip angle, and it can effectively improve vehicle adaptive stability control. In the optimal torque distributor based on road surface recognition, the estimated error of road adhesion is within 10%, and has a greater margin to deal with vehicle instability, which can effectively improve vehicle adaptive stability control.

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Section: Torque Distribution Controller Based On Road Adhesion Coeffi...mentioning

confidence: 99%

Adaptive Stability Control Based on Sliding Model Control for BEVs Driven by In-Wheel Motors

Guo

Feng

et al. 2023

Sustainability

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“…where l f and l r are, respectively, the front and rear center-of-gravity distances, I zz is the vehicle's moment of inertia around the vertical axis, m is the total mass of the vehicle, and C α f and C α r are, respectively, the front and the rear cornering stiffnesses obtained by considering the Adapted Burckhardt Tire Model (ABTM), as developed in [27]. Due to the complexity of Equations (5a) and (5b), a straightforward interaction model for control design cannot be obtained.…”

Section: Vehicle Synthesis Modelmentioning

confidence: 99%

A Robust Lateral Control Architecture for Off-Road Vehicle Guidance on Deformable Soils

Vieira,

Vie,

Orjuela

et al. 2023

Electronics

Self Cite

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This paper introduces a novel lateral guidance strategy for autonomous ground vehicles operating in deformable environments. The strategy combines a geometric algorithm with a dynamic controller to leverage the advantages of both methods. The geometric algorithm is based on a modified Pure Pursuit method, which calculates the lateral error by considering a dynamic parameter associated with the look-ahead distance. The controller takes model uncertainties and time-variant parameters into account in a grid-based LPV (Linear Parameter Varying) synthesis. To validate the proposed control architecture, a dedicated off-road vehicle simulator that accounted for deformable soils was used. The effectiveness and robustness of the proposed lateral guidance strategy were demonstrated by integrating and validating the control architecture on a vehicle prototype. The results indicate that the proposed approach effectively handled complex and uncertain deformable environments. Overall, this study presents a new lateral guidance strategy that enhances the performance and reliability of autonomous ground vehicles in challenging environments.

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“…The estimation methods based on the curve of the adhesion coefficient and the slip rate [ 17 ], together with the relationship between the right torque and the side deflection angle of tires [ 18 ], are common in the vehicle field, which only needs the common on-board sensors, such as wheel speed sensors and attitude sensors. For example, aligning the torque and the side-slip angle or the relationship description between the tire lateral force is performed through linearization [ 19 ], Brush [ 20 , 21 ], TMsimple [ 22 ], Pacejka [ 23 ], and Burckhardt [ 24 ] to identify adhesion coefficients under the condition of lateral movements of the vehicle. However, such a method based on the response recognition of tires is affected by many external uncertainties due to the complexity of the generation mechanism of the tire noise, and sometimes it is insurmountable to accurately identify the adhesion coefficients.…”

Section: Introductionmentioning

confidence: 99%

Adhesion Coefficient Identification of Wheeled Mobile Robot under Unstructured Pavement

Zhang,

Song,

et al. 2024

Sensors

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Because of its uneven and large slope, unstructured pavement presents a great challenge to obtaining the adhesion coefficient of pavement. An estimation method of the peak adhesion coefficient of unstructured pavement on the basis of the extended Kalman filter is proposed in this paper. The identification accuracy of road adhesion coefficients under unstructured pavement is improved by introducing the equivalent suspension model to optimize the calculation of vertical wheel load and modifying vehicle acceleration combined with vehicle posture data. Finally, the multi-condition simulation experiments with Carsim are conducted, the estimation accuracy of the adhesion coefficient is at least improved by 3.6%, and then the precision and effectiveness of the designed algorithm in the article are verified.

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An adapted Burckhardt tire model for off-road vehicle applications

Cited by 12 publications

References 20 publications

Adaptive Stability Control Based on Sliding Model Control for BEVs Driven by In-Wheel Motors

Adaptive Stability Control Based on Sliding Model Control for BEVs Driven by In-Wheel Motors

A Robust Lateral Control Architecture for Off-Road Vehicle Guidance on Deformable Soils

Adhesion Coefficient Identification of Wheeled Mobile Robot under Unstructured Pavement

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