• Title/Summary/Keyword: Tire road friction coefficient estimation

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A Study of Tire Road Friction Estimation for Controlling Rear Wheel Driving Force of 4WD Vehicle (4WD 차량의 후륜 구동력 제어를 위한 구동시 노면마찰계수 추정에 관한 연구)

  • Park, Jae-Young;Shim, Woojin;Heo, Seung-Jin
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.5
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    • pp.512-519
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    • 2016
  • In this study, the tire road friction estimation(TRFE) algorithm for controlling the rear wheel driving force of a 4WD vehicle during acceleration is developed using a standard sensor in an ordinary 4WD passenger car and a speed sensor. The algorithm is constructed for the wheel shaft torque, longitudinal tire force, vertical tire force and maximum tire road friction estimation. The estimation results of shaft torque and tire force were validated using a torque sensor and wheel force transducer. In the algorithm, the current road friction is defined as the proportion calculated between longitudinal and vertical tire force. Slip slop methods using current road friction and slip ratio are applied to estimate the road friction coefficient. Based on this study's results, the traction performance, fuel consumption and drive shaft strength performance of a 4WD vehicle are improved by applying the tire road friction estimation algorithm.

AEBS Algorithm with Tire-Road Friction Coefficient Estimation (타이어-노면 마찰계수 추정을 이용한 AEBS 알고리즘)

  • Han, Seungjae;Lee, Taeyoung;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.5 no.2
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    • pp.17-23
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    • 2013
  • This paper describes an algorithm for Advanced Emergency Braking(AEB) with tire-road friction coefficient estimation. The AEB is a system to avoid a collision or mitigate a collision impact by decelerating the car automatically when forward collision is imminent. Typical AEB system is operated by Time-to-collision(TTC), which considers only relative velocity and clearance from control vehicle to preceding vehicle. AEB operation by TTC has a limit that tire-road friction coefficient is not considered. In this paper, Tire-road friction coefficient is also considered to achieve more safe operation of AEB. Interacting Multiple Model method(IMM) is used for Tire-road friction coefficient estimation. The AEB algorithm consists of friction coefficient estimator and upper level controller and lower level controller. The numerical simulation has been conducted to demonstrate the control performance of the proposed AEB algorithm. The simulation study has been conducted with a closed-loop driver-controller-vehicle system using using MATLAB-Simulink software and CarSim Vehicle model.

Estimation of Tire-Road Friction Coefficient using Observers (관측기를 이용한 노면과 타이어 간의 마찰계수 추정)

  • 정태영;이경수;송철기
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.6
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    • pp.722-728
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    • 1998
  • In this paper real-time estimation methods for identifying the tire-road friction coefficient are presented. Taking advantage of the Magic Formula Tire Model, the similarity technique and the specific model for the vehicle dynamics, a reduced order observer/filtered-regressor-based method is proposed. The Proposed method is evaluated on simulations of a full-vehicle model with an eight state nonlinear vehicle/transmission model and nonlinear suspension model. It has been shown through simulations that it is possible to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speeds using the proposed identification method. The proposed method can be used as a useful option as a part of vehicle collision warning/avoidance systems and will be useful in the implementation of a warning algorithm since the tire-road friction can be estimated only using RPM sensors.

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A Study on Lateral Tire-road Friction Coefficient Estimation Using Tire Pneumatic Trail Information (타이어 뉴메틱 트레일 정보를 활용한 횡방향 타이어 노면 마찰 계수에 관한 연구)

  • Han, Kyoungseok;Choi, Seibum
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.3
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    • pp.310-318
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    • 2016
  • The demands for vehicle safety systems such as ABS and ESC have been increased. Accurate vehicle state estimation is required to realized the abovementioned systems and tire-friction coefficient is crucial information. Estimation of lateral tire-road friction coefficient using pneumatic trail information is mainly dealt in this paper. Pneumatic trail shows unique characteristics according to the wheel side slip angle and these property is highly sensitive to vehicle lateral motion. The proposed algorithm minimizes the use of conventional tire models such as magic formula, brushed tire model and Dugoff tire model. The pure side slip maneuver, which means no longitudinal dynamics, is assumed to achieve the ultimate goal of this paper. A simulation verification using Carsim and Simulink is performed and the results show the feasibility of the proposed algorithms.

Estimation of Tire Braking Force and Road Friction Coefficient Between Tire and Road Surface For Wheel Slip Control (휠 슬립 제어를 위한 타이어와 노면 사이의 타이어 제동력 및 노면 마찰계수 추정)

  • Hong, Dae-Gun;Huh, Kun-Soo;Yoon, Pal-Joo;Hwang, In-Yong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.5
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    • pp.517-523
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    • 2004
  • Recently, wheel slip controllers with controlling the wheel slip directly has been studied using the brake-by-wire actuator. The wheel slip controller is able to control the braking force more accurately and can be adapted to various different vehicles more easily than the conventional ABS systems. The wheel slip controller requires the information about the tire braking force and road condition in order to achieve the control performance. In this paper, the tire braking forces are estimated considering the variation of the friction between brake pad and disk due to aging of the brake, moisture on the contact area or heating. In addition, the road friction coefficient is estimated without using tire models. The estimated performance of tire braking forces and the road friction coefficient is evaluated in simulations.

A Study on the Estimation of Frictiom Coefficient between Tire and Road Surface Using Running Car data (실차 데이터를 이용한 차륜과 노면간의 마찰계수 예측에 관한 연구)

  • 우관제;산기준일
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.6
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    • pp.207-213
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    • 1999
  • In this study, the possibility of estimation of friction coefficient between tire and road surface using running car data are checked. To get necessary data, such as tire and car velocities and braking force, a test car is driven with certain magnitude of decelerations from pre-set initial velocities to stop . The data are used to estimate friction coefficient with property chosen parameters , e.g,, driving stiffness, pressure distribution functions, etc. Experimental results show that running data car be used with properly chosen parameters to estimate friction coefficient.

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Rack Force Estimation Method using a Tire Mesh Model (TIRE MESH 모델을 활용한 랙추력 추정법 개발)

  • Kim, Minjun;Chang, Sehyun;Lee, Byungrim;Park, Youngdae;Cho, Hyunseok
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.3
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    • pp.130-135
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    • 2014
  • In this paper, a new estimation method is proposed to calculate steering rack axial force using a 3 dimensional tire mesh model when a car is standing on the road. This model is established by considering changes of camber angle and contact patch between the tires and the ground according to steering angle. The steering rack bar axial force is estimated based on the static equilibrium equations of forces and moments. A tire friction force is supposed to act on the center point of the contact patch, and the proportional coefficient of friction depending on contact patch is suggested. Using the proposed estimation method, rack axial force sensitivity analysis is evaluated according to changes of suspension geometry. Then optimal motor power of Motor Driven Power Steering(MDPS) is evaluated using suggested rack forces.

Analysis of Uncertainties in Estimation of Critical Speeds from Tire Yaw Marks (타이어 요마크로부터 임계속도 추정의 불확실성 해석)

  • Han, Inhwan
    • Transactions of the Korean Society of Automotive Engineers
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    • v.23 no.4
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    • pp.361-370
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    • 2015
  • There will inevitably be errors and uncertainties in tire yaw mark related critical speed formula, which is derived merely from the relationship between the centrifugal force and the friction force acting on the point-mass vehicle. Constructing and measuring yaw marks through appropriate simulation works have made it possible to perform uncertainty analysis in calculation of critical speeds under variation of variety of conditions and parameters while existing yaw mark experimental tests have not performed properly. This paper does not present only the critical speed analysis results for parametric sensitivity and uncertainty of chord and middle ordinate, coefficient of friction and road grade, but also modeling uncertainty such as variation of braking level during turning and vehicle size. The yaw mark analysis methods and results may be now applied in practice of traffic accident investigation.

A Development of New Vehicle Model for Yaw Rate Estimation (요각속도 추정을 위한 새로운 차량 모델의 개발)

  • Bae, Sang-Woo;Shin, Moo-Hyun;Kim, Dae-Kyun;Lee, Jang-Moo;Lee, Jae-Hyung;Tak, Tae-Oh
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.565-570
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    • 2001
  • Vehicle dynamics control (VDC) system requires more information on driving conditions compared with ABS and/or TCS. In order to develop the VDC system, tire slip angles, vehicle side-slip angle, and vehicle lateral velocity as well as road friction coefficient are needed. Since there are not any cheap and reliable sensors, recent researches on parameter estimation have given rise to a number of parameter estimation techniques. This paper presents new vehicle model to estimate vehicle's yaw rate. This model is improved from the conventional 2 degrees of freedom vehicle model, so-called bicycle model, taking nonlinear effects into account. These nonlinear effects are: (i) tyre nonlinearity; (ii) lateral load transfer during cornering; (iii) variable gear ratio with respect to vehicle velocity. Estimation results are validated with the experimental results.

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