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Real-time identification of tire–road friction conditions

Real-time identification of tire–road friction conditions

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Tire–road friction characteristics are deeply interlaced with all vehicle dynamics control systems, as road conditions strongly affect the control schemes behaviour. This work aims at the real-time estimation of the wheel slip value corresponding to the peak of the tire–road friction curve, in order to provide anti-lock braking systems (ABS) with reliable information on its value upon activation. Different techniques based on recursive least squares and the maximum likelihood approach are used for friction curve fitting and their merits and drawbacks thoroughly examined. In addition, since one of the main issues in slip-based friction estimation during braking is vehicle speed estimation, an effective algorithm for addressing this task is developed. The proposed peak slip value estimation strategy is analysed and tested both in simulation and on data collected on an instrumented test vehicle. In the latter case, the vehicle speed estimation algorithm is used, and the estimated vehicle speed provided as input for friction estimation. Practical applicability constraints posed by typical ABS systems are also considered.

Inspec keywords: vehicle dynamics; least squares approximations; velocity control; road vehicles; wheels; maximum likelihood estimation; braking; recursive estimation; tyres; curve fitting; friction

Other keywords: antilock braking system; recursive least square method; tire-road friction condition; real-time identification; road friction curve fitting; maximum likelihood approach; vehicle speed estimation; wheel slip value estimation; all vehicle dynamics control system

Subjects: Vehicle mechanics; Mechanical components; Other topics in statistics; Road-traffic system control; Velocity, acceleration and rotation control; Products and commodities; Statistics; Numerical analysis; Control technology and theory (production); Interpolation and function approximation (numerical analysis); Tribology (mechanical engineering)

References

    1. 1)
      • L. Ljung , T. Soderstrom . (1983) Theory and practice of recursive identification.
    2. 2)
      • J. Yi , L. Alvarez , R. Horowitz . Adaptive emergency braking control with underestimation of friction coefficient. Trans. Control Syst. Technol. , 3 , 381 - 392
    3. 3)
      • B.J. Quinn , M. Fernandes . A fast technique for the estimation of frequency. Biometrika , 3 , 489 - 497
    4. 4)
      • Watanabe, K., Kinase, K., Kobayashi, K.: `Absolute speed measurement of vehicles from noisy acceleration and erroneous wheel speed', Proc. Symp. Intelligent Vehicles, 14–16 July 1993.
    5. 5)
      • S.M. Savaresi , M. Tanelli , P. Langthaler , L. Del Re . New regressors for the identification of tire deformation in road vehicles via in-tire accelerometers. IEEE Trans. Control Syst. Technol. , 4 , 769 - 780
    6. 6)
      • Eichorn, U., Roth, J.: `Prediction and monitoring of tire-road friction', Proc. 20th FISITA World Congress, 1992, Montreal, (CA).
    7. 7)
      • L. Ray . Nonlinear tire force estimation and road friction identification: simulation and experiments. Automatica , 10 , 1819 - 1833
    8. 8)
      • Semmler, S., Fischer, D., Isermann, R., Schwarz, R., Rieth, P.: `Estimation of vehicle velocity using brake-by-wire actuators', Proc. 15th IFAC World Congress, 21–26 July 2002, Barcelona, Spain.
    9. 9)
      • G.L. Gissinger , C. Menare , A. Constans . A mechatronic conception of a new intelligent braking system. Control Eng. Pract. , 163 - 170
    10. 10)
      • T.C. Hsia . (1977) System identification.
    11. 11)
      • S.M. Savaresi , S. Bittanti , H.C. So . Closed-form unbiased frequency estimation of a noisy sinusoid using notch filters. IEEE Trans. Autom. Control , 7 , 1285 - 1292
    12. 12)
      • T.A. Johansen , J. Petersen , J. Kalkkuhl , J. Lüudemann . Gain-scheduled wheel slip control in automotive brake systems. IEEE Trans. Control Syst. Technol. , 6 , 799 - 811
    13. 13)
      • L. Alvarez , J. Yi , X. Claeys , R. Horowitz . Emergency braking control with an observer-based dynamic tire/road friction model and wheel angular velocity measurement. Vehicle Syst. Dyn. , 2 , 81 - 97
    14. 14)
      • Kobayashi, K., Cheok, K.C., Watanabe, K.: `Estimation of absolute vehicle speed using fuzzy logic rule-based Kalman filter', Proc. 1995 American Control Conference, 21–23 June 1996, Seattle, USA.
    15. 15)
      • Breuer, B., Eichorn, U., Roth, J.: `Measurement of tyre-road friction ahead of the car and inside the tyre', Proc. Int. Symp. Advanced Vehicle Control, AVEC’92, 1992, p. 347–353.
    16. 16)
      • Jiang, F., Gao, Z.: `An adaptive nonlinear filter approach to the vehicle velocity estimation for ABS', Proc. 2000 IEEE Int. Conf. Control Application, 25–27 September 2000, Anchorage.
    17. 17)
      • M. Tanelli , A. Astolfi , S.M. Savaresi . Robust nonlinear output feedback control for brake-by-wire control systems. Automatica , 4 , 1078 - 1087
    18. 18)
      • E. Ono , K. Asano , M. Sugai , S. Ito , M. Yamamoto , M. Sawada , Y. Yasui . Estimation of automotive tire force characteristics using wheel velocity. Control Eng. Prac. , 1361 - 1370
    19. 19)
      • H.B. Pacejka . (2002) Tyre and vehicle dynamics.
    20. 20)
      • M. Muller , M. Uchanski , K. Hedrick . Estimation of the maximum tire-road coefficient. J. Dyn. Syst. Meas. Control , 607 - 617
    21. 21)
      • P.E. Wellstead , N.B. Pettit . Analysis and redesign of an antilock brake system controller. IEE Proc. Control Theory Appl. , 5 , 413 - 426
    22. 22)
      • K. Holmström , J. Petersson . A review of the parameter estimation problem of fitting positive exponential sums to empirical data. Appl. Math. Comput. , 1 , 31 - 61
    23. 23)
      • Alvarez, L., Horowitz, R., Olmos, L.: `Adaptive emergency braking control with observer-based dynamic tire-road friction model and underestimation of friction coefficient', Proc. 15th IFAC World Congress, 21–26 July 2002, Barcelona, Spain.
    24. 24)
      • Klein, R., Daiss, A., Eichfeld, H.: `Antilock braking system and vehicle speed estimation using fuzzy logic', Proc. first Embedded Computing Conf., 1996, Paris.
    25. 25)
      • F. Gustafsson . Slip-based tire-road friction estimation. Automatica , 6 , 1087 - 1099
    26. 26)
      • U. Kiencke , L. Nielsen . (2000) Automotive control systems.
    27. 27)
      • S.M. Savaresi , M. Tanelli , C. Cantoni . Mixed slip-deceleration control in automotive braking systems. ASME J. Dyn. Syst., Meas. Control , 1 , 20 - 31
    28. 28)
      • Tanelli, M., Savaresi, S.M.: `Friction-curve peak detection by wheel-deceleration measurements', Proc. IEEE Conf. Intelligent Transportation Systems, 2006, Toronto, Canada.
    29. 29)
      • L. Ray . Nonlinear state and tire force estimation for advanced vehicle control. IEEE Trans. Control Syst. Technol. , 1 , 117 - 124
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