Adaptive vibration cancellation for tire-road friction coefficient estimation on winter maintenance vehicles

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Abstract

This paper focuses on the development and experimental evaluation of a novel adaptive feedforward vibration cancellation based friction estimation system. The friction estimation utilizes a small instrumented redundant wheel on the vehicle. Unlike other systems previously documented in literature, the developed system can provide a continuous measurement of the friction coefficient under all vehicle maneuvers, even when the longitudinal and lateral accelerations are both zero. A key challenge in the development of the estimation system is the need to remove the influence of vibrations and the influence of vehicle maneuvers from the measured signal of a force sensor. An adaptive feedforward algorithm based on the use of accelerometer signals as reference inputs is developed. The parameters of the feedforward model estimated by the adaptive algorithm themselves serve to determine the value of the friction coefficient. At the same time, the influence of vibrations and of vehicle maneuvers is removed. Detailed experimental results are presented on a skid pad wherein the road surface changes from dry asphalt to ice. Results are presented at different speeds and with and without lateral and longitudinal maneuvers. Excellent performance is obtained in estimation of the friction coefficient. The performance of the adaptive feedforward algorithm is shown to be significantly superior to that of a simple cross-correlation based algorithm for friction estimation.

Original languageEnglish (US)
Article number5286244
Pages (from-to)1023-1032
Number of pages10
JournalIEEE Transactions on Control Systems Technology
Volume18
Issue number5
DOIs
StatePublished - Sep 2010

Bibliographical note

Funding Information:
Manuscript received November 15, 2008; revised June 01, 2009; accepted August 11, 2009. Manuscript received in final form August 24, 2009. First published October 13, 2009; current version published August 25, 2010. Recommended by Associate Editor G. E. Stewart. This work was supported in part by the Minnesota Department of Transportation under Contract 81655.

Funding Information:
Rajesh Rajamani received the M.S. and Ph.D. de-grees from the University of California at Berkeley, in 1991 and 1993, respectively, and the B.Tech. de-gree from the Indian Institute of Technology, Madras, India, in 1989. He is currently a Professor with the Department of Mechanical Engineering, University of Minnesota, Minneapolis. His active research interests include sensors and control systems for automotive and biomedical applications. He has authored over 70 journal publications and holds 4 patents. He is the author of Vehicle Dynamics and Control (Springer, 2005). Dr. Rajamani has served as Chair of the IEEE Technical Committee on Automotive Control and on the editorial boards of the IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY and the IEEE/ASME TRANSACTIONS ON MECHATRONICS. Among several honors, Dr. Rajamani has been a recipient of the CAREER Award from the National Science Foundation, the 2001 Outstanding Paper Award from the journal IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, and the 2007 O. Hugo Schuck Award from the American Automatic Control Council.

Keywords

  • Adaptive feedforward
  • friction coefficient
  • vehicle dynamics
  • vibration cancellation

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