Influence of the road-surface texture on the speed dependency of tire/road friction

Similar documents
Prediction of Tire/Wet Road Friction from Road Surface Microtexture and Tire Rubber Properties

Tribology Approach to Predict the Variation of Tire/Wet Road Friction with Slip Speed

Smart Bolometer: Toward Monolithic Bolometer with Smart Functions

Thermo-mechanical modelling of the aircraft tyre cornering

Exogenous input estimation in Electronic Power Steering (EPS) systems

Vibro-acoustic simulation of a car window

Hydroplaning speed and infrastructure characteristics

A new simple recursive algorithm for finding prime numbers using Rosser s theorem

Detection and Survey of Interface Defects Within a Pavement Structure with Ultrasonic Pulse Echo

Methylation-associated PHOX2B gene silencing is a rare event in human neuroblastoma.

Easter bracelets for years

Case report on the article Water nanoelectrolysis: A simple model, Journal of Applied Physics (2017) 122,

AC Transport Losses Calculation in a Bi-2223 Current Lead Using Thermal Coupling With an Analytical Formula

RHEOLOGICAL INTERPRETATION OF RAYLEIGH DAMPING

Towards an active anechoic room

Electromagnetic characterization of magnetic steel alloys with respect to the temperature

Water Vapour Effects in Mass Measurement

Can we reduce health inequalities? An analysis of the English strategy ( )

Thomas Lugand. To cite this version: HAL Id: tel

Comment on: Sadi Carnot on Carnot s theorem.

DEM modeling of penetration test in static and dynamic conditions

Simultaneous Induction Heating and Electromagnetic Stirring of a Molten Glass Bath

The beam-gas method for luminosity measurement at LHCb

A non-commutative algorithm for multiplying (7 7) matrices using 250 multiplications

Stator/Rotor Interface Analysis for Piezoelectric Motors

From Unstructured 3D Point Clouds to Structured Knowledge - A Semantics Approach

IMPROVEMENTS OF THE VARIABLE THERMAL RESISTANCE

Characterization of the local Electrical Properties of Electrical Machine Parts with non-trivial Geometry

Dispersion relation results for VCS at JLab

b-chromatic number of cacti

Passerelle entre les arts : la sculpture sonore

A new approach of the concept of prime number

Laboratory test methods for polishing asphalt surfaces and predicting their skid resistance

Evolution of the cooperation and consequences of a decrease in plant diversity on the root symbiont diversity

Analysis of Boyer and Moore s MJRTY algorithm

On Solving Aircraft Conflict Avoidance Using Deterministic Global Optimization (sbb) Codes

Comparison of Harmonic, Geometric and Arithmetic means for change detection in SAR time series

Lorentz force velocimetry using small-size permanent magnet systems and a multi-degree-of-freedom force/torque sensor

On measurement of mechanical properties of sound absorbing materials

Nonlocal computational methods applied to composites structures

The FLRW cosmological model revisited: relation of the local time with th e local curvature and consequences on the Heisenberg uncertainty principle

Completeness of the Tree System for Propositional Classical Logic

Quantum efficiency and metastable lifetime measurements in ruby ( Cr 3+ : Al2O3) via lock-in rate-window photothermal radiometry

L institution sportive : rêve et illusion

On the longest path in a recursively partitionable graph

Basic concepts and models in continuum damage mechanics

Trench IGBT failure mechanisms evolution with temperature and gate resistance under various short-circuit conditions

On Symmetric Norm Inequalities And Hermitian Block-Matrices

A Simple Proof of P versus NP

Multiple sensor fault detection in heat exchanger system

Interactions of an eddy current sensor and a multilayered structure

TRING-module : a high-range and high-precision 2DoF microsystem dedicated to a modular micromanipulation station.

Entropies and fractal dimensions

On size, radius and minimum degree

Ultra low frequency pressure transducer calibration

Voltage Stability of Multiple Distributed Generators in Distribution Networks

Full-order observers for linear systems with unknown inputs

Particle-in-cell simulations of high energy electron production by intense laser pulses in underdense plasmas

New Basis Points of Geodetic Stations for Landslide Monitoring

Optical component modelling and circuit simulation using SERENADE suite

Improving the Jet Reconstruction with the Particle Flow Method; an Introduction

Radio-detection of UHECR by the CODALEMA experiment

Diurnal variation of tropospheric temperature at a tropical station

Soundness of the System of Semantic Trees for Classical Logic based on Fitting and Smullyan

On production costs in vertical differentiation models

Quasistatic behavior and force transmission in packing of irregular polyhedral particles

Numerical modification of atmospheric models to include the feedback of oceanic currents on air-sea fluxes in ocean-atmosphere coupled models

Control of an offshore wind turbine modeled as discrete system

On Newton-Raphson iteration for multiplicative inverses modulo prime powers

SOLAR RADIATION ESTIMATION AND PREDICTION USING MEASURED AND PREDICTED AEROSOL OPTICAL DEPTH

A Study of the Regular Pentagon with a Classic Geometric Approach

On Poincare-Wirtinger inequalities in spaces of functions of bounded variation

STATISTICAL ENERGY ANALYSIS: CORRELATION BETWEEN DIFFUSE FIELD AND ENERGY EQUIPARTITION

Axiom of infinity and construction of N

Mirage detection for electrochromic materials characterization. Application to iridium oxide films

The influence of the global atmospheric properties on the detection of UHECR by EUSO on board of the ISS

New estimates for the div-curl-grad operators and elliptic problems with L1-data in the half-space

A non-commutative algorithm for multiplying (7 7) matrices using 250 multiplications

Prompt Photon Production in p-a Collisions at LHC and the Extraction of Gluon Shadowing

The sound power output of a monopole source in a cylindrical pipe containing area discontinuities

The status of VIRGO. To cite this version: HAL Id: in2p

Solution to Sylvester equation associated to linear descriptor systems

Some approaches to modeling of the effective properties for thermoelastic composites

The Windy Postman Problem on Series-Parallel Graphs

Solving the neutron slowing down equation

Eddy-Current Effects in Circuit Breakers During Arc Displacement Phase

MODal ENergy Analysis

A numerical analysis of chaos in the double pendulum

ATOMIC STRUCTURE OF INTERFACES IN GaAs/Ga1-xAlxAs SUPERLATTICES

A Simple Model for Cavitation with Non-condensable Gases

On sl3 KZ equations and W3 null-vector equations

Cutwidth and degeneracy of graphs

Solubility prediction of weak electrolyte mixtures

Numerical Exploration of the Compacted Associated Stirling Numbers

Hook lengths and shifted parts of partitions

Some explanations about the IWLS algorithm to fit generalized linear models

Computation and Experimental Measurements of the Magnetic Fields between Filamentary Circular Coils

Territorial Intelligence and Innovation for the Socio-Ecological Transition

On path partitions of the divisor graph

A novel method for estimating the flicker level generated by a wave energy farm composed of devices operated in variable speed mode

Transcription:

Influence of the road-surface texture on the speed dependency of tire/road friction Minh Tan Do, Hassan Zahouani To cite this version: Minh Tan Do, Hassan Zahouani. Influence of the road-surface texture on the speed dependency of tire/road friction. 10th International Conference Metrology and Properties of Engineering Surfaces, Jul 2005, France. 11p., schémas, tabl., graphiques, ill., 2005. <hal-00851275> HAL Id: hal-00851275 https://hal.archives-ouvertes.fr/hal-00851275 Submitted on 13 Aug 2013 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INFLUENCE OF THE ROAD-SURFACE TEXTURE ON THE SPEED DEPENDENCY OF TIRE/ROAD FRICTION Minh-Tan Do LCPC Route de Bouaye BP 4129 44341 Bouguenais Cedex, France minh-tan.do@lcpc.fr Hassan Zahouani ENISE 58, rue Jean Parot 42023 Saint Etienne, France zahouani@enise.fr Abstract : Tire/wet road friction depends on two road-surface texture scales: the macrotexture (centimeter- to millimeter dimensions) is responsible for the speed dependency of friction, and the microtexture (submillimeter dimensions) is responsible for the friction level at any speed. This paper deals firstly with the description of road-microtexture, the macrotexture scale being well documented. Considering the fact that rubber energy-loss controls tire/wet road friction and that angularity of road-surface asperities influences greatly tire deformation, the second author has proposed a description method derived from the motif-combination technique. This method defines two parameters related to the sharpness of asperity summits and the relative position of these summits. A model has been then proposed by the first author to describe the friction-speed curve from roadsurface macro- and microtexture descriptors, tire-related characteristics (rubber properties, wear) and road wetness. The description is based on the Stribeck curve. The speed-dependency friction model is applied to the analysis of car-braking tests. Comparisons between calculated and measured friction-coefficients at different braking speeds are presented and discussed. Key words: friction, texture. 1 Context The braking capacity of a vehicle depends on friction forces developed in the contact area between the vehicle tires and the road. For longitudinal braking, the friction force F x is expressed as F x = µ.f z, where F z is the normal load and µ is the tire/road. 1

The tire/road depends on the wheel slip (κ), expressed as κ = S/V, where S is the relative speed between the tire and the road (called also slip speed) and V is the vehicle speed. An example of µ-κ curve is shown in the figure 1. It can be seen that this curve comprises two parts corresponding to two braking behaviors: - In the first part, µ increases to a maximum value called µ max. The braking is soft : the more the driver brakes, the more the vehicle decelerates. - In the second part, µ decreases to a value called µ locked. The braking is brutal : the wheels are locked and the vehicle slips. 1,20 µ peak 1,00 0,80 0,60 0,40 µ locked 0,20 0,00 0,20 0,40 0,60 0,80 1,00 wheel slip Fig. 1: Example of measurement of as a function of wheel slip. Since µ max and µ locked are essential for the knowledge of friction-slip law, and in consequence for vehicle-handling assessment, methods are developed to estimate them whether from wheel kinematics or from road-surface texture. At LCPC, research has been carried out for more than 30 years to better understand the relationship between road-surface texture and skid resistance. Attempts have been then made to apply this knowledge to the estimation of µ max and µ locked. This paper presents a synthesis of this work, including a collaboration between LCPC and LTDS. 2 Generalities on tire/road contact This paper deals with tire/wet road contact, since the on dry road is generally high and slipperiness is mostly problematic on wet roads. 2.1 Road texture scales Road surface is rough. Two observation scales are defined (Fig. 2): - The macrotexture is defined as surface irregularities which dimensions are between 0.1 mm and 20 mm vertically and between 0.5 mm and 50 mm horizontally [1]. 2

- The microtexture is defined as surface irregularities which dimensions are between 0.001 mm and 0.5 mm vertically and less than 0.5 mm horizontally [1]. Macrotexture 0,1-20 mm 0,5-50 mm Microtexture 0,001-0,5 mm < 0,5 mm 2.2 Tire/road contact area Fig. 2: Road macro- and microtexture scales. The tire/wet road contact area is usually divided into three zones (Fig. 3): - In zone 1, the water separates completely the tire from the road; - In zone 2, the tire is supported by the water and the road asperities; - In zone 3, the tire is supported essentially by the road asperities. tire water road zone 3 zone 2 zone 1 Fig. 3: Scheme of tire/wet road contact. This scheme shows that friction forces are generated mostly in zone 3. When the vehicle speed increases, the zone-3 size can be reduced due to insufficient water drainage. The varies then with the vehicle speed. It is generally admitted that friction value for a given wheel slip depends on road microtexture and that its variation with speed depends on road macrotexture. 2.3 Friction-speed variation and Stribeck curve Two examples of friction-speed variation are shown in the figure 4. They show that speed dependency can be different depending on test conditions (tire, water, etc.). Nevertheless, it was shown in [2] that, despite their different shapes, these curves represent part of the Stribeck curve, which is widely employed for lubricated-contact studies (Fig. 5). 3

1,00 1,00 0,80 0,60 0,40 0,20 0,80 0,60 0,40 0,20 0,00 0 50 100 0,00 0 50 100 speed (km/h) speed (km/h) Fig. 4: Examples of friction-speed variation. F T /F N limit lubrication λ 1 mixed lubrication (elasto)hydrodynamic lubrication λ 0 ηv/p F N F T, V A λa p, η viscosity pressure 3 Friction estimation Fig. 5: Lubricated contact and Stribeck curve. 3.1 Approach Since µ max and µ locked should depend on speed, the following approach is adopted for their estimation: - model the µ-v curve; - express the model constants as a function of macro- and microtexture descriptors. 3.2 Friction-speed modeling The following model was proposed from [2] to describe the variation of tire/road friction with speed: a V µ = µ 0 exp + bv V (1) s 4

where µ 0 : friction at theoretical zero speed; V s : Stribeck speed; a, b: shape and viscous parameters respectively. The full lines in figure 4 are obtained for (a = 1, b = 0) and (a = 3, b = 0) respectively. It was proved from [2]: - that µ 0 is related to the road microtexture; - that V s is related to the road macrotexture and the wheel slip; - that a is related to the water thickness above road asperities (WD) and the tiretread depth (TD); - that bv term is negligible (roughly 0.01) compared with commonly used tire/wet road friction range (0.2 < µ < 0.9). In the figure 6, the exponent (a) is plotted against the ratio WD/TD (the symbols correspond to two road surfaces). This ratio takes into account the water-drainage action provided by the tire pattern. Despite some scatters (encircled points), it can be seen that (a) increases with increasing WD/TD, meaning that the shape of friction-speed curves varies with the amount of water. Beyond the limit defined by WD/TD = 1, (a) stabilizes at 3. Physically, WD/TD = 1 expresses the fact that the water saturates completely the tire patterns. Simple fitting (full line in figure 6) shows that (a) can be written as: WD a = 3 1 exp k (2) TD where k: parameter to be obtained from fitting. 3,5 3,0 2,5 a 2,0 1,5 1,0 0,5 0,0 0 1 2 3 4 5 WD/TD Fig. 6: Variation of shape parameter with water depth and tire tread depth. In the figure 7, variations of Stribeck speed with road macrotexture for two wheel slips are shown. The macrotexture is expressed by the standardized Mean Profile Depth (MPD) [1], which is the distance between the highest profile peaks and the mean profile line. The following formula was found to fit well the measurements [2] (full line in figure 7): V s = 117.MPD c.κ 0.9 (3) 5

where κ: wheel slip; c: vehicle-dependent parameter. It should be noted that this formula was found for road-monitoring devices which the measuring wheel is generally towed by a vehicle. 200 V s (km/h) 150 100 50 κ = 0.86 κ = 0.34 0 0 1 2 3 4 MPD (mm) Fig. 7: Variation of Stribeck speed with road macrotexture and wheel slip. 3.3 Calculation of µ 0 from road microtexture This work comprises two parts: - the microtexture description. - The calculation of friction from microtexture descriptors using a contact model. 3.3.1 microtexture description Few works are done on road microtexture compared with those on road macrotexture which descriptors are standardized [1]. Collaboration between LCPC and LTDS was developed few years ago to find out a microtexture description method relevant for tire/road friction purpose. Works are detailed in [3]; they are briefly reminded here. Example of road profiles is shown in the figure 8. The Y-scale shows that the observed scale is the surface microtexture. The characterization method is based on the following established facts: - friction is generated only in direct-contact spots between the tire and the road surface. - the road-asperity shape is the most relevant factor for friction generation. 6

140 138 θ indentor height (µm) 136 134 2α 132 valleys 130 2840 2850 2860 2870 2880 2890 abscissa (µm) Fig. 8: Road profile and microtexture descriptors. Road asperities where contact occurs are defined as indentors (Fig. 8). An indentor is then part of the road profile between two valleys. The indentor distribution is characterized by two parameters: the shape (cotangent of angle α) and the relief (angle θ). Simple algorithm is developed to detect all profile peaks and valleys called extremes. The characteristic angles are calculated by means of the following formulae: 1 α = tan 2 1 x x i z z i i 1 i 1 + tan 1 x z i+ 1 i+ 1 x i z i where: - x i : abscissa of the extreme n (i) (if index (i) is a peak, the indexes (i-1) and (i+1) are valleys); - z i : height of the extreme n (i). And (4) θ = tan 1 z x j+ 1 j+ 1 z x j j (5) where: - x j : abscissa of the peak n (j); - z j : height of the peak n (j). Tests performed on laboratory specimens showed that the shape and relief parameters are well correlated to friction (Fig. 9) [3]. Nevertheless, in order to have a predictive tool, these parameters need to be integrated in a model. 7

0,8 0,8 0,6 0,6 0,4 4 6 8 10 12 0,4 0,05 0,10 0,15 0,20 0,25 θ (degree) cotg α Fig. 9: Relationship between relief (θ) and shape (cotg α) parameters and friction. 3.3.2 contact model This contact model is developed by M. Stefani (LCPC researcher) with the original aim to simulate the hysteresis effect of friction (energy loss by viscoelastic properties of the rubber). The model geometry represents the contact between a rubber pad and part of a road profile between two peaks called motif (Fig. 10). No surface friction (adhesion) is considered. Therefore, the model assumes that friction forces are generated uniquely by deformation of the Kelvin solid representing the rubber pad. The relaxation time of this solid (ratio η/k) is used as the rubber characteristic. It should be noted that the Stefani model is developed for microtexture-study purpose, so the calculated friction is low-speed. Example of Kelvin-solid path D A K η V α 2 α 1 B C Contact duration t 1 Contact duration t 2 L 1 L 3 L 2 Fig. 10: Geometry of the contact model. Due to the motif geometry, contact loss can occur between the solid and the motif. Vertical and horizontal forces are calculated and integrated over the contact durations t 1 and t 2. The ratio between their resultants (f v and f h respectively) is defined as a coefficient of friction µ. Details of the calculations can be found in [3]. 8

By setting L 3 = 0, this contact model can be coupled with the characterization method developed above to calculate µ from road profiles. The first results [3] obtained on laboratory surfaces composed of coarse aggregates show that two friction values must be considered, which correspond to µ calculated at two scales: the roughness scale related to the profile and the undulation scale related to its envelop (line connecting all profile peaks). Indentors of the roughness scale are determined from the bold line of the figure 8, and those of the undulation scale from the dotted line (Fig. 8). 4 Validation 4.1 Methodology In this paragraph, the method developed in paragraph 3 is applied to the estimation of µ locked at two speeds. The methodology is the following: - calculate µ 0 from road microtexture-profile measurements; - calculate V s from road macrotexture-profile measurements; - draw the theoretical µ locked -V curve. 4.2 Experimental program Test campaigns were carried out on 30 sites comprising test tracks and trafficked roads (closed during test periods). On each site, the experimental program comprises (Fig. 11): - Braking tests; - Road macrotexture measurements; - Core sampling (four 20 cm-diameter cores) in the braking paths for microtexture measurements in laboratory. braking paths L d h 10m surface wetting by tank truck macrotexture measurements core sampling for microtexture measurements Fig. 11: Experimental program and view of LCPC instrumented vehicle. The macrotexture was measured using a standardized volumetric method [1]. A known glass bead volume is spread on the road to form a circular patch. Measuring the circle diameter, it can be deduced the mean texture depth. In this paper, this value will be assumed to be also the road profile MPD. 9

Thirteen microtexture profiles were measured on each core. Their sampling interval is 10 µm and their length is 80 mm (8001 points). 4.3 Braking tests Braking tests were done by means of a light instrumented vehicle (Peugeot 406) with and without ABS activation. Decelerations are recorded during braking of front wheels from speed V 1 to speed V 2, then the brake is released. Tests were done for two speed ranges: 90 km/h (V 1 ) to 70 km/h (V 2 ), and 60 km/h (V 1 ) to 40 km/h (V 2 ). Friction coefficients are deduced from deceleration measurements using the following formula [4]: 2 2 2 V V V V M 1 2 1 + 2 A B + 2 d 2 µ = (6) 2 2 V1 V 2 h Zav M + 2 d L where: - µ: ; - M: vehicle mass; - d: braking distance (Fig. 11); - V i (i = 1, 2): test speed; - Z av : load on the front axle; - h: height of the vehicle center of gravity (Fig. 11); - L: vehicle wheelbase (Fig. 11). - A, B: coefficients to be estimated for each vehicle from specific tests. The is µ peak (respectively µ locked ) for braking with ABS (respectively without ABS). The associated speeds are the mean of the speed range: 80km/h for highspeed deceleration tests and 50km/h for low-speed deceleration tests. 4.4 Comparison between theoretical and experimental µ locked For the calculation of Stribeck speed, formula (3) was used with κ = 1 (for µ locked ) and c = 0.19 (empirical value employed for a road-monitoring device using locked measuring wheel). Since there was no water depth measurement, it was decided to calculate the µ-v curve for two extreme values of the exponent (a) of the formula (1). From the figure 6, it can be said that these values are 1 and 3 respectively. Typical comparison results are shown in the figure 12. The lines represent the theoretical µ-v curves (full line: a = 1; dotted line: a = 3); they should be the limits since they correspond to extreme values of (a). The points are µ locked values obtained from braking tests. It can be seen that the comparison is satisfactory since the experimental points are inside the theoretical curves. 10

1,00 0,80 0,60 0,40 0,20 0 50 100 1,00 0,80 0,60 0,40 0,20 0 50 100 LCPC test tracks speed (km/h) Trafficked road speed (km/h) 5 Conclusions Fig. 12: Experimental µ locked and theoretical µ locked -V curves (. The main objective of the work presented in this paper is to see if tire/road friction coefficients can be estimated from road surface texture. It was shown from the above paragraphs that this objective could be reached. Knowledge of road macro- and microtexture can be used, via models, to estimate µ max and µ locked, which are two important parameters for vehicle handling assessment. Further validation results are needed. Nevertheless, the first results are promising enough to look already for possible improvements in texture measurement methods. Macrotexture can be currently measured by on-board sensors. However, efforts are still needed for the development of on-site microtexture measurements. 6 References [1] ISO 13473-1. Characterization of pavement texture by use of surface profiles - Part 1: Determination of Mean Profile Depth. [2] M.-T. Do, P. Marsac, A. Mosset. Tribology Approach to Predict the Variation of Tire/Wet Road Friction with Slip Speed, Proceedings of the PIARC 5th International Symposium on Pavement Surface Characteristics, 6-9 June 2004, Toronto, Canada. [3] M.-T. Do, H. Zahouani. Frottement Pneumatique/Chaussée Influence de la Microtexture des Surfaces de Chaussée, Actes des Journées Internationales de Tribologie, 2-4 Mai 2001, Obernai, France, 2001, pp. 49-61. [4] MICHELIN. "The Tyre - Grip", Ed. Société de Technologie Michelin, ISBN 2-06-000311-3, 2000. 11