Integrated Longitudinal Vehicle Dynamics Control with Tire/Road Friction Estimation

The contact friction characteristic between a tyre and the road is a key factor that dominates the dynamics performance of a vehicle under critical conditions. Vehicle dynamics control systems, such as anti-lock braking systems, traction control systems, and electronic stability control systems (e.g. Elektronisches Stabilitäts Programm (ESP)), need an accurate road friction coefficient to adjust the control mode. No time delay in the estimation of road friction should be allowed, thereby avoiding the disappearance of the optimal control point. A comprehensive method to predict the road friction is suggested on the basis of the sensor fusion method, which is suitable for variations in the vehicle dynamics characteristics and the control modes. The multi-sensor signal fusion method is used to predict the road friction coefficient for a steering manoeuvre without braking; if active braking is involved, simplified models of the braking pressure and tyre force are adopted to predict the road friction coefficient and, when high-intensity braking is being considered, the neural network based on the optimal distribution method of the decay power is applied to predict the road friction coefficient. The method is validated through a ground test under complicated manoeuvre conditions. It was verified that the comprehensive method predicts the road friction coefficient promptly and accurately.

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Road Friction Estimation Method Based on Fusion of Machine Vision and Vehicle Dynamics**Resrach supported by ‘National key Research and Development Program of China’ (Grant No. 2018YFB0104805), ‘National Natural Science Foundation of China’ (Grant No. U15642073) and ‘National Natural Science Foundation of China’ (Grant No. 51975414).

2020 IEEE Intelligent Vehicles Symposium (IV) ◽

10.1109/iv47402.2020.9304538 ◽

2020 ◽

Author(s):

Da Jin ◽

Bo Leng ◽

Xing Yang ◽

Lu Xiong ◽

Zhuoping Yu

Keyword(s):

Machine Vision ◽

Research And Development ◽

Natural Science ◽

Vehicle Dynamics ◽

Estimation Method ◽

Development Program ◽

Road Friction ◽

Friction Estimation

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A Modified Dugoff Tire Model for Combined-slip Forces

Tire Science and Technology ◽

10.2346/1.3481696 ◽

2010 ◽

Vol 38 (3) ◽

pp. 228-244 ◽

Cited By ~ 19

Author(s):

Nenggen Ding ◽

Saied Taheri

Keyword(s):

Vehicle Dynamics ◽

Tire Model ◽

Magic Formula ◽

Model Based ◽

Proposed Model ◽

Road Friction ◽

On Line ◽

Double Lane Change ◽

Tire Forces ◽

Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

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Amortized Variational Inference for Road Friction Estimation

2020 IEEE Intelligent Vehicles Symposium (IV) ◽

10.1109/iv47402.2020.9304712 ◽

2020 ◽

Author(s):

Shuangshuang Chen ◽

Sihao Ding ◽

L. Srikar Muppirisetty ◽

Yiannis Karayiannidis ◽

Marten Bjorkman

Keyword(s):

Variational Inference ◽

Road Friction ◽

Friction Estimation

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Direct Longitudinal Force Feedback for High-Performance Vehicle Dynamics Control Systems

10.1115/detc2021-69432 ◽

2021 ◽

Author(s):

Giorgio Riva ◽

Luca Mozzarelli ◽

Matteo Corno ◽

Simone Formentin ◽

Sergio M. Savaresi

Keyword(s):

Model Predictive Control ◽

Control Systems ◽

Predictive Control ◽

Vehicle Dynamics ◽

High Performance ◽

Force Feedback ◽

Longitudinal Force ◽

Spiral Path ◽

Comparable Performance ◽

Vehicle Dynamics Control

Abstract State of the art vehicle dynamics control systems do not exploit tire road forces information, even though the vehicle behaviour is ultimately determined by the tire road interaction. Recent technological improvements allow to accurately measure and estimate these variables, making it possible to introduce such knowledge inside a control system. In this paper, a vehicle dynamics control architecture based on a direct longitudinal tire force feedback is proposed. The scheme is made by a nested architecture composed by an outer Model Predictive Control algorithm, written in spatial coordinates, and an inner longitudinal force feedback controller. The latter is composed by four classical Proportional-Integral controllers in anti-windup configuration, endowed with a suitably designed gain switching logic to cope with possible unfeasible references provided by the outer loop, avoiding instability. The proposed scheme is tested in simulation in a challenging scenario where the tracking of a spiral path on a slippery surface and the timing performance are handled simultaneously by the controller. The performance is compared with that of an inner slip-based controller, sharing the same outer Model Predictive Control loop. The results show comparable performance in presence of unfeasible force references, while higher robustness is achieved with respect to friction curve uncertainties.

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