A novel estimation scheme of tyre–road friction characteristics based on parameter constraints on varied-µ roads

Xiao, Feng; Hu, Jianjun; Jia, Meixia; Zhu, Pengxing; Deng, Chenghao

doi:10.1016/j.measurement.2022.111077

Cited by 15 publications

(4 citation statements)

References 30 publications

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“…The Effect-based method is based on estimating TRFC based on the response relationship between the road surface, tire, and vehicle dynamics, and is mainly divided into tirevehicle dynamics model estimation method and slope method based on µ − s (tire-road friction coefficient and slip rate) curve [21]. The slope method is only applicable under working conditions where the tire slip rate is small, and the tire's own rubber and inflation performance factors also affect the calculation results of the slope method, so this method is not accurate [22]. The estimation method using the tirevehicle dynamics model has been widely studied in recent years [23].…”

Section: Square Root Cubature Kalman Filtermentioning

confidence: 99%

Enhanced Tire Road Friction Coefficient Estimation Through Interacting Multiple Model Design based on Tire Force Observation

Wan,

Sheng,

Cai

et al. 2024

Preprint

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Accurately understanding the Tire-Road Friction Coefficient (TRFC) interaction is crucial for enhancing overall vehicle control performance. However, existing estimation methods heavily rely on the accuracy of tire modeling, which may not predict TRFC effectively under poor modeling accuracy or changing operating conditions. This paper proposes an interacting multiple-model TRFC estimation method using tire force observation. Firstly, taking advantage of the observation capabilities of distributed drive electric vehicles, a longitudinal force estimator with unknown inputs is designed. Simultaneously, a lateral force observer based on adaptive sliding mode observer (ASMO) is developed, fully utilizing the onboard sensor data of the vehicle. A TRFC estimator with square root cubature Kalman filter, incorporating square root filtering, is proposed to reduce algorithm complexity while ensuring accuracy. Finally, an interacting multiple-model mechanism is specifically developed for both pure longitudinal dynamics and combined conditions. Through Carsim-Matlab co-simulation and high TRFC test conditions of a real vehicle equipped with a 6-axis wheel transducer, it is shown that the algorithm proposed in this article can accurately estimate tire force and TRFC under various maneuvering conditions and different TRFC conditions. Based on the comparison with traditional algorithms, it shows that our proposed algorithm has higher estimation accuracy and robustness.

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Section: Square Root Cubature Kalman Filtermentioning

confidence: 99%

Enhanced Tire Road Friction Coefficient Estimation Through Interacting Multiple Model Design based on Tire Force Observation

Wan,

Sheng,

Cai

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Since the TRFC is difficult to be directly measured by sensors, many scholars have conducted in-depth research on its estimation. The existing research studies are mainly divided into experimental methods [6,7] and model methods [8,9]. The experimental methods use expensive sensors such as radar and camera to identify the pavement state and further estimate the pavement adhesion coefficient on this basis.…”

Section: Literature Reviewmentioning

confidence: 99%

Study on Mathematical Models for Precise Estimation of Tire–Road Friction Coefficient of Distributed Drive Electric Vehicles Based on Sensorless Control of the Permanent Magnet Synchronous Motor

Yu,

Hu,

Zeng

2024

Symmetry

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In order to reduce the use of wheel angular velocity sensors and improve the estimation accuracy and robustness of the tire–road friction coefficient (TRFC) in non-Gaussian noise environments, this paper proposes a sensorless control-based distributed drive electric vehicle TRFC estimation algorithm using a permanent magnet synchronous motor (PMSM). The algorithm replaces the wheel angular velocity signal with the rotor speed signal obtained from the sensorless control of the PMSM. Firstly, a seven-degree-of-freedom vehicle dynamics model and a mathematical model of the PMSM are established, and the maximum correntropy singular value decomposition generalized high-degree cubature Kalman filter algorithm (MCSVDGHCKF) is derived. Secondly, a sensorless control system of a PMSM based on the MCSVDGHCKF algorithm is established to estimate the rotor speed and position of the PMSM, and its effectiveness is verified. Finally, the feasibility of the algorithm for TRFC estimation in non-Gaussian noise is demonstrated through simulation experiments, the Root Mean Square Error (RMSE) of TRFC estimates for the right front wheel and the left rear wheel were reduced by at least 41.36% and 40.63%, respectively. The results show that the MCSVDGHCKF has a higher accuracy and stronger robustness compared to the maximum correntropy high-degree cubature Kalman filter (MCHCKF), singular value decomposition generalized high-degree cubature Kalman filter (SVDGHCKF), and high-degree cubature Kalman filter (HCKF).

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“…In such complex moving conditions, the car must keep a stable trajectory of movement under the driver's control. There are many studies related to automobile motion stabilization such as: Research on optimizing control inputs to stabilize the horizontal trajectory of the vehicle [1], in these studies refer to transverse automobile dynamics with the effect of tire friction against the road surface, stabilization of the car's horizontal trajectory by controlling the operation of the differential [2], algorithm studies for estimating the transverse velocity and transverse force of tires affecting vehicle stability when cornering, Simulation results show that the developed system can reliably estimate the upper and lower bounds of vehicle lateral variables during both steady and transient maneuvers [3], building the horizontal stabilization algorithm of cars [4], development of single-track transverse dynamics models for automobiles [5], study of driver models applied to automotive dynamics, a brief look beyond is added to better complete the view on the involved task of driving and driver modeling for automobile dynamics application [6], the paper studies the horizontal stability control of the car using front-wheel steering and in combination with the brake system [7]. When studying the stability of the automobile fully, it is necessary to consider the dynamics of the car [8], stability analysis illustrating the influence of the following attributes on the stability and performance of lateral vehicle Engineering control: Vehicle handling properties, virtual force application point, sensing location, controller damping [9].…”

Section: Introductionmentioning

confidence: 99%

Study of the influence of lateral forces and velocity on the lateral dynamics of automobile

Nguyen,

Bui

2024

Eureka: PE

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Stability of a car's trajectory of motion is the ability of a car to retain its required state of motion, under different conditions of motion. Depending on different states of motion, cars can lose direction of motion instability when there is a lateral force, due to vehicle speed, due to turning or braking the road with different grip coefficients on the sides of the wheel. In such complex moving conditions, cars need to keep a stable trajectory of movement under the driver's control. The paper examines the stability of the car's trajectory in linear motion conditions with the influence of lateral forces and the velocity of the vehicle, these two factors act to change the state of movement of the vehicle, which significantly affects the safety of the vehicle's movement. The authors looked at the effect of vehicle velocity and lateral forces on vehicle transverse dynamics: lateral forces caused by horizontal winds, inclination of the road surface, speed of movement of the vehicle acting on the entire body create centrifugal inertial forces; this force acts to cause the tires to deform. At this point the vehicle is shifted from its original trajectory. In the research content, the authors built a lateral Dynamics Model, in which the influencing factors are set as inputs to the model including vehicle velocity and transverse wind forces, output is the rotation angle of the body, transverse acceleration and horizontal displacement of the vehicle. The simulation results showed that the effect of vehicle speed was relatively large: lateral displacement increased by 228 % at a speed of 120 km/h. Therefore, when driving on the highway, there should always be driver control to ensure that the car does not deviate from the lane

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A novel estimation scheme of tyre–road friction characteristics based on parameter constraints on varied-µ roads

Cited by 15 publications

References 30 publications

Enhanced Tire Road Friction Coefficient Estimation Through Interacting Multiple Model Design based on Tire Force Observation

Enhanced Tire Road Friction Coefficient Estimation Through Interacting Multiple Model Design based on Tire Force Observation

Study on Mathematical Models for Precise Estimation of Tire–Road Friction Coefficient of Distributed Drive Electric Vehicles Based on Sensorless Control of the Permanent Magnet Synchronous Motor

Study of the influence of lateral forces and velocity on the lateral dynamics of automobile

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