0
TECHNICAL PAPERS

Estimation of the Maximum Tire-Road Friction Coefficient

[+] Author and Article Information
Steffen Müller

Postdoc at the Department of Mechanical Engineering, University of California, Berkeley, California 94720 Since June 1st 2001: BMW AG, 80788 Münchene-mail: steffen.mc.mueller@bmw.de

Michael Uchanski

Department of Mechanical Engineering, University of California, Berkeley, California 94720e-mail: mikeu@vehicle.me.berkeley.edu

Karl Hedrick

Department of Mechanical Engineering, University of California, Berkeley, California 94720

J. Dyn. Sys., Meas., Control 125(4), 607-617 (Jan 29, 2004) (11 pages) doi:10.1115/1.1636773 History: Received January 16, 2002; Revised June 30, 2003; Online January 29, 2004
Copyright © 2003 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
A sampling of tire-road friction estimation research. Complete reference information for these papers in bibliography.
Grahic Jump Location
Normalized longitudinal force, μ, versus longitudinal slip, computed using “Magic Formula”
Grahic Jump Location
Left: Measured μ versus slip data for 18 separate braking maneuvers on dry road and 10 separate braking maneuvers on wet and soapy road. Right: Same raw data as left graph, but the μ axis is divided into bins and one data point per bin is generated for each surface by averaging all of the slip values in that bin.
Grahic Jump Location
Measured μ versus slip data at several time instants during a hard braking maneuver (circles) and their least squares slip curves using tire model of Eq. 5 (solid line). μmax taken from the fitted slip curve tends to depend on the most extreme μ value attained.
Grahic Jump Location
μmax and slope k of regression lines for slip curves during braking. Dark stars come from dry road slip curves, and light diamonds come from soapy road slip curves. Left: Data points with μ ranging from 0 to −0.2 are used to calculate slope of regression lines. Right: Data points with μ ranging between 0 and −0.4 are used to calculate regression line.
Grahic Jump Location
Illustration of “Secant Effect:” Both slip curves calculated from the “brush model,” and both have the same longitudinal stiffness. Yet, the regression lines using data with μ between 0 and 0.4 have different slopes.
Grahic Jump Location
Comparison between measured and estimated traction force. The wheel is on the verge of locking at time=3.5 seconds.
Grahic Jump Location
Measured (solid) and estimated (circles) slip curves during braking. Left: Dry road. Right: Soapy road.
Grahic Jump Location
Regression line slope for the measured and estimated slip curves from Fig. 8, plotted against the friction coefficient (kμcut versus μcut)
Grahic Jump Location
μmax versus k0.4 for braking on dry (dark stars) and soapy (light diamonds) road surfaces using k0.4 of observed slip curves
Grahic Jump Location
Slopes of the linear part of dry-road slip curves taken from the literature

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In