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Advanced Tire Friction Modeling and Monitoring

Abstract

A proper tire friction model is essential to describe overall vehicle dynamics for simulation, analysis, or control purposes, since the motion of a ground vehicle is primarily determined by the friction forces transferred from roads via tires. Thus, analysis of tire/road friction can provide us an in-sight understand of vehicle dynamics and help us to improve ride performance [l]–[8].

Keywords

Friction Modeling Slip Angle Side Slip Angle Tire Friction Tyre Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Reference

  1. 1.
    D. F. Moore, The friction of pneumatic tyres, Elsevier Scientific Publishing Co., New York, 1975.Google Scholar
  2. 2.
    T. French, Tyre Technology, Ed. Adam Hilger, Bristol, 1989.Google Scholar
  3. 3.
    D. Dowson, History of tribology, Longman Ltd., London, 1998.Google Scholar
  4. 4.
    B. Feeny, A. Guran, and N. Hinrichs, et. al, “A historical review on dry friction and stick-slip phenomena,” ASME Applied Mechanical Reviews, vol. 51, no. 5, pp. 321–341, 1998.CrossRefGoogle Scholar
  5. 5.
    J. Y. Wong, Theory of ground vehicles, John Wiley & Sons, Inc., New York, 1993.Google Scholar
  6. 6.
    U. Kiencke and L. Nielsen, Automotive Control System for Engine, Driveline, and Vehicle, Springer. 2000.Google Scholar
  7. 7.
    W. Hirschberg, G. Rill, and H. Weinfurter, “User-appropriate tyre-modelling for vehicle dynamics in standard and limit situations,” Vehicle System Dynamics, vol. 38, no. 2, pp. 103–125, 2002.CrossRefGoogle Scholar
  8. 8.
    Y. P. Chang, M. El-Gindy, and D. A. Streit, “Literature survey of transient dynamic response tyre models,” International Journal of Vehicle Design, vol. 34, no. 4, pp. 354–386, 2004.CrossRefGoogle Scholar
  9. 9.
    J. Harned, L. Johnston, and G. Scharpf, “Measurement of tire brake force characteristics as related to wheel slip (anti-block) control system design,” SAE Transactions, vol. 78, SAE #690214, pp: 909–925, 1969.Google Scholar
  10. 10.
    E. Bakker, L. Nyborg, and H. B. Pacejka, “Tire modeling for use in vehicle dynamic studies,” Society of Automotive Engineers, SAE #870421, 1987.Google Scholar
  11. 11.
    E. Bakker, H. B. Pacejka, and L. Lidner, “A new tire model with an application in vehicle dynamics studies,” Proceedings of International Congress and Exposition, SAE #890087, 1989.Google Scholar
  12. 12.
    H. B. Pacejka and R. S. Sharp, “Shear force development by pneumatic tires in steady state conditions: a review of modeling aspects,” Vehicle System Dynamics, vol. 20, pp: 121–176, 1991.CrossRefGoogle Scholar
  13. 13.
    P. W. A. Zegelaar and H. B. Pacejka, “The in-plane dynamics of tyres on uneven roads,” Vehicle System Dynamics Supplement, vol. 25, pp. 714–730, 1996.CrossRefGoogle Scholar
  14. 14.
    E. Denti and D. Fanteria, “Models of wheel contact dynamics: an analytical study on the in-plane transient response of a brush model,” Vehicle System Dynamics, vol. 32, pp. 199–225, 2000.CrossRefGoogle Scholar
  15. 15.
    M. Burckhardt, Fahrwerktechnik: Radschlupfregelsysteme, Vogel-Verlag, Germany, 1993.Google Scholar
  16. 16.
    L. Alvarez and J. Yi, “Adaptive emergency braking control in automated highway systems,” Proceedings of IEEE Conference on Decision and Control, vol. 4, pp: 3740–3745, 1999.Google Scholar
  17. 17.
    G. Rill, Simulation von Kraftfahrzeugen, Vieweg, 1994.Google Scholar
  18. 18.
    H. B. Pacejka and E. Bakker, “The magic formula tyre model,” Proceedings of 1st International Colloquium on Tyre Models for Vehicle Dynamics Analysis, pp: 1–18, 1991.Google Scholar
  19. 19.
    P. Dahl, “A solid friction model,” Technical Report TOR-0158(3107-18)-1, The Aerospace Corporation, El Segundo, CA, 1976.Google Scholar
  20. 20.
    P. Dahl, “Measurement of solid friction parameters of ball bearings,” Proceedings of 6th Annual Symposium on Incremental Motion, Control Systems and Devices, pp: 49–60, 1977.Google Scholar
  21. 21.
    P.-A. Bliman and M. Sorine, “Friction modeling by hysteresis operators: application to Dahl, stiction and stribeck effects,” Proceedings of the Conference ‘Models of Hysteresis’, 1991.Google Scholar
  22. 22.
    P.-A. Bliman and M. Sorine, “A system-theoretic approach of systems with hysteresis: application to friction modeling and compensation,” Proceedings of European Control Conference, 1993.Google Scholar
  23. 23.
    P.-A. Bliman and M. Sorine, “Easy-to-use realistic dry friction models for automatic control,” Proceedings of European Control Conference, 1994.Google Scholar
  24. 24.
    C. Canudas de Wit, H. Olsson, and K. J. Astrom, et al, “A new model for control of systems with friction,” IEEE Transactions on Automatic Control, vol. 40, no. 3, pp: 419–425, 1995.zbMATHCrossRefGoogle Scholar
  25. 25.
    C. Canudas de Wit and P. Tsiotras, “Dynamic tire friction models for vehicle traction control,” Proceedings of IEEE Conference on Decision and Control, vol. 4, pp: 3746–3751, 1999.Google Scholar
  26. 26.
    H. Olsson, “Control systems with friction,” PhD thesis, Department of Automatic Control, Lund Institute of Technology, Lund, Sweden, 1996.Google Scholar
  27. 27.
    N. Barabanov and R. Ortega, “Necessary and sufficient conditions for passivity of the LuGre friction model,” IEEE Transactions on Automatic Control, vol. 45, no. 4, pp: 830–832, 2000.zbMATHCrossRefMathSciNetGoogle Scholar
  28. 28.
    M. Gafvert, “Comparisons of two dynamic friction models,” Proceedings of IEEE International Conference on Control Applications, pp: 386–391, 1997.Google Scholar
  29. 29.
    H. Olsson, K.J. Astrom, and C. Canudas de Wit, et. al, “Friction models and friction compensation,” European Journal of Control, vol. 4, no. (3), 1998.Google Scholar
  30. 30.
    J. Deur, “Modeling and analysis of longitudinal tire dynamics based on the LuGre friction model,” Proceedings of 3rd IFAC Workshop Advances in Automotive Control, pp: 101–106, 2001.Google Scholar
  31. 31.
    J. Deur, “A brush-type dynamic tire friction model for non-uniform normal pressure distribution,” CD-ROM Proceedings of 15th Triennial IFAC World Congress, 2002.Google Scholar
  32. 32.
    C. Canudas-de-Wit, P. Tsiotras, and E. Velenis, “Dynamic friction models for longitudinal road/tire interaction: theoretical advances,” 21st IASTED Conference on Modelling, Identification and Control, pp: 48–53, 2002.Google Scholar
  33. 33.
    C. Canudas-de-Wit, P. Tsiotras, and E. Velenis, “Dynamic friction models for longitudinal road/tire interaction: experimental results,” 21st IASTED Conference on Modelling, Identification and Control, 2002.Google Scholar
  34. 34.
    C. Canudas de Wit, P. Tsiotras, and E. Velenis, et. al, “Dynamic friction models for road/tire longitudinal interaction,” Vehicle System Dynamics, vol. 39, no. 3, pp. 189–226, 2003.CrossRefGoogle Scholar
  35. 35.
    J. Yi, L. Alvarez, and X. Claeys, et. al, “Emergency braking control with an observer-based dynamic tire road friction model and wheel angular velocity measurement,” Vehicle System Dynamics, vol. 39, no. 2, pp. 81–97, 2003.CrossRefGoogle Scholar
  36. 36.
    M. Segel, “Theoretical prediction and experimental substantiation of the response of the automobile to steering control,” Proceedings of Automobile division of the institute of mechanical engineers, vol. 7, pp: 310–330, 1956.Google Scholar
  37. 37.
    J. Kasselmann and T. Keranen, “Adaptive steering,” Bendix Technical Journal, vol. 2, pp. 26–35, 1969.Google Scholar
  38. 38.
    J. Ackermann, “Robust car steering by yaw rate control,” Proceedings of the 29th IEEE Conference on Decision and Control, pp: 2033–2034, 1990.Google Scholar
  39. 39.
    J. Ackermann and W. Dareberg, “Automatic track control of a city bus,” IFAC Theory Report on Benchmark Problems for Control Systems Design, 1990.Google Scholar
  40. 40.
    B. Breuer, V. Eichorn, and J. Roth, “Measurement of tyre/road friction ahead of car and inside the tyre,” Proceedings of International Symposium on Advanced Vehicle Control, 1992.Google Scholar
  41. 41.
    Q. Qu and Y. Liu, “On lateral dynamics of vehicles based on nonlinear characteristics of tires,” Vehicle System Dynamics, vol. 34, pp. 131–141, 2000.CrossRefGoogle Scholar
  42. 42.
    E. Ono, S. Hosoe, and D. Tuan, et. al, “Bifurcation in vehicle dynamics and robust front wheel steering control,” IEEE Transactions on Control Systems Technology, vol. 6, no. 3, pp: 412–420, 1998.CrossRefGoogle Scholar
  43. 43.
    J. Stephant, A. Charara, and D. Meizel, “Virtual sensor: application to vehicle sideslip angle and transversal forces,” IEEE Transactions on Industrial Electronics, vol. 51, no. 2, pp: 278–289, 2004.CrossRefGoogle Scholar
  44. 44.
    Y. Furukawa, N. Yuhara, and S. Sano, et. al, “A review of four-wheel steering studies from the viewpoint of vehicle dynamics and control,” Vehicle System Dynamics, no. 18, pp: 151–186, 1989.CrossRefGoogle Scholar
  45. 45.
    P. Raksincharoensak, M. Nagai, and H. Mouri, “Investigation of automatic path tracking control using four-wheel steering vehicle,” Proceedings of the IEEE International Vehicle Electronics Conference, pp: 73–77,2001.Google Scholar
  46. 46.
    J. Ackermann and W. Sienel, “Robust yaw damping of cars with front and rear wheel steering,” IEEE Transactions on Control Systems Technology, vol. 1, no. 1, pp: 15–20, 1993.CrossRefGoogle Scholar
  47. 47.
    H. Peng and M. Tomizuka, “Lateral control of front-wheel-steering rubber-tire vehicles,” PATH Research Report UCB-ITS-PRR-90-5, 1990.Google Scholar
  48. 48.
    T. A. Johansen, I. Petersen, J. Kalkkuhl, J. Ludemann, Gain-scheduled wheel slip control in automotive brake systems, IEEE Transactions on Control Systems Technology, vol. 11, pp. 799–811, 2003.CrossRefGoogle Scholar
  49. 49.
    J. P. Maurice, M. Berzeri, and H. B. Pacejka, “Pragmatic tyre model for short wavelength side slip variations,” Vehicle System Dynamics, vol. 31, pp: 65–94, 1999.CrossRefGoogle Scholar
  50. 50.
    J. Stephant, A. Charara, and D. Meizel, “Force model comparison on the wheel-ground contact for vehicle dynamics,” IEEE Intelligent Vehicle Symposium, vol. 2, pp: 589–593, 2002.CrossRefGoogle Scholar
  51. 51.
    G. Mastinu and E. A. Pairana, “A semi-analytical tyre model for steady and transient state simulations, Proceedings of 1st International Colloquium on Tyre Models for Vehicle Dynamics Analysis, pp: 58–81, 1991.Google Scholar
  52. 52.
    H. B. Pacejka and I. Besseling, “Magic formula tyre model with transient properties,” Proceedings of 2nd International Colloquium on Tyre Models for Vehicle Dynamics Analysis, 1997.Google Scholar
  53. 53.
    M. Gafvert and J. Svendenius, “Construction of semi-empirical tire models for combined slip,” Technical Report ISRN LUTFD2/TFRT7606SE, Department of Automatic Control, Lund Institute of Technology, Sweden, 2003.Google Scholar
  54. 54.
    J.-O. Hahn, R. Rajamani, and L. Alexander, “GPS-based real-time identification of tire-road friction coefficient,” IEEE Transactions on Control Systems Technology, vol. 10, no. 3, pp: 331–343, 2002.CrossRefGoogle Scholar
  55. 55.
    D. J. Schilling, W. Pelz, and M. G. Pottinger, “A model for combined tire cornering and braking forces,” Investigations and Analysis in Vehicle Dynamics and Simulation, SAE International, SAE #960180, pp: 61–83, 1996.Google Scholar
  56. 56.
    G. Gim and P. E. Nikravesh, “An analytical model of pneumatic tyres for vehicle dynamics simulations, Part 2: Comprehensive slips,” International Journal of Vehicle Design, vol. 12, no. 1, pp: 19–39, 1991.Google Scholar
  57. 57.
    X. Claeys, J. Yi, and L. Alvarez, et. al, “A dynamic tire/road friction model for 3D vehicle control and simulation,” Proceedings of IEEE Intelligent Transportation Systems Conference, pp: 483–488, 2001.Google Scholar
  58. 58.
    J. Deur, J. Asgari, and D. Hrovat, “A 3D brush-type dynamic tire friction model,” Vehicle System Dynamics, vol. 42, no. 3, pp. 133–173, 2004.CrossRefGoogle Scholar
  59. 59.
    S. Velenis, C. Canudas de Wit, and P. Tsiotras, “Extension of the LuGre Dynamic Friction Model to 2D Motion,” Internal report, Laboratoire d’Automatique de Grenoble, France, 2001.Google Scholar
  60. 60.
    J. Martinez, J. Avila and C. Canudas, “A new bicycle vehicle model with dynamic contact friction,” First IFAC Symposium on Automotive Control, 2004.Google Scholar
  61. 61.
    T. L. Ford and F. S. Charles, “Heavy duty truck tire engineering,” SAE #880001, 1988.Google Scholar
  62. 62.
    E. Gohring, E. C. Von Glasner, and H. C. Pflug, “Contribution to the force transmission behavior of commercial vehicle tires,” SAE #912692, 1991.Google Scholar
  63. 63.
    M. Gafvert, “Topics in modeling, control, and implementation in automotive systems,” Ph.D. Dissertation, ISSN 0280-5316, ISRN LUTFD2/TFRT-1066-SE, 2003.Google Scholar
  64. 64.
    G. Mavros, H. Rahnejat and P. King, “Investigation of steady-state tyre force and moment generation under combined longitudinal and lateral slip conditions,” Vehicle System Dynamics, vol. 41, pp. 351–360, 2004.Google Scholar
  65. 65.
    A. Lawrence, Modern Inertial Technology, Springer Verlag, 1993.Google Scholar
  66. 66.
    F. Napolitano, T. Gaiffe, and Y. Cottreau, et. al. “PHINS: the first inertial navigation system based on fiber optic gyroscopes,” Proceedings of St Petersbourg International Conference on Navigation Systems, 2002.Google Scholar
  67. 67.
    R. Usui and A. Ohno, “Recent progress of fiber optic gyroscope and application at JAE,” Optical Fiber Sensors Conference Technical Digest, vol.1, pp: 11–14,2002.CrossRefGoogle Scholar
  68. 68.
    E. Nebot, S. Sukkarieh, and H. Durrant-Whyte, “Inertial navigation aided with GPS information,” Proceedings of the Fourth Annual Conference on Mechatronics and Machine Vision in Practice, pp: 169–174, 1997.Google Scholar
  69. 69.
    F. X. Cao, D. K. Yang, and A. G. Xu, et. al, “Low cost SINS/GPS integration for land vehicle navigation,” Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, pp: 910–913, 2002.Google Scholar
  70. 70.
    C.-Y. Chan, “Magnetic sensing as a position reference system for ground vehicle control,” IEEE Transactions on Instrumentation and Measurement, 51(1), pp: 43–52, 2002.CrossRefGoogle Scholar
  71. 71.
    J. I. Hernandez and C.-Y. Kuo, “Steering control of automated vehicles using absolute positioning GPS and magnetic markers,” IEEE Transactions on Vehicular Technology, vol. 52, no. 1, pp: 150–161, 2003.CrossRefGoogle Scholar
  72. 72.
    S. M. Donecker, T. A. Lasky, and B. Ravani, “A mechatronic sensing system for vehicle guidance and control,” IEEE/ASME Transactions on Mechatronics, vol. 8, no. 4, pp: 500–510, 2003.CrossRefGoogle Scholar
  73. 73.
    W. S. Wijesoma, K. R. S. Kodagoda, and A. P. Balasuriya, et. al, “Road edge and lane boundary detection using laser and vision,” Proceedings of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, pp: 1440–1445, 2001.Google Scholar
  74. 74.
    U. Eichhorn and J. Roth, “Prediction and monitoring of tyre/road friction,” XXIV FISITA Congress, London, 1992.Google Scholar
  75. 75.
    B. Breuer, U. Eichhorn, and J. Roth, “Measurement of tyre/road friction ahead of the car and inside the tyre,” Proceedings of International Symposium on Advanced Vehicle Control, pp: 347–353, 1992.Google Scholar
  76. 76.
    S. Germann, M. Wurtenberger, and A. Daiss, “Monitoring of the friction coefficient between tyre and road surface,” Proceedings of the Third IEEE Conference on Control Applications, vol. 1, pp: 613–618, 1994.CrossRefGoogle Scholar
  77. 77.
    C. Liu and H. Peng, “Road friction coefficient estimation for vehicle path prediction,” Vehicle System Dynamics, vol. 25 Supplement, pp. 413–425, 1996.CrossRefGoogle Scholar
  78. 78.
    F. Gustafsson, “Slip-based tire-road friction estimation,” Automatica, vol. 33, no. 6, pp: 1087–1099, 1997.CrossRefMathSciNetGoogle Scholar
  79. 79.
    F. Gustafsson, “Monitoring tire-road friction using the wheel slip,” IEEE Control Systems Magazine, vol. 18, no. 4, pp: 42–49, 1998.CrossRefGoogle Scholar
  80. 80.
    S. Muller, M. Uchanski, K. Hedrick, “Estimation of the maximum tire-road friction coefficient,” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 125, no. 4, pp: 607–617, 2003.CrossRefGoogle Scholar
  81. 81.
    Kiencke, U. and Daiss, A., “Estimation of tyre friction for enhanced ABS systems,” Proceedings of International Symposium on Advanced Vehicle Control, 1994.Google Scholar
  82. 82.
    W. Hwang and B.-S. Song, “Road condition monitoring system using tire-road friction estimation,” Proceedings of International Symposium on Advanced Vehicle Control, pp: 437–442, 2000.Google Scholar
  83. 83.
    J. Wang, L. Alexander, R. Rajamani, “Friction estimation on highway vehicles using longitudinal measurements,” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 126, no. 2, pp: 265–275, 2004.CrossRefGoogle Scholar
  84. 84.
    H. Nishira, T. Kawabe, and S. Shin, “Road friction estimation using adaptive observer with periodical σ-modification,” Proceedings of IEEE International Conference on Control Applications, vol. 1, pp: 662–667, 1999.Google Scholar
  85. 85.
    K. Yi, K. Hedrick, and S. C. Lee, “Estimation of tire-road friction using observer based identifiers,” Vehicles Systems Dynamics, vol. 31, pp: 233–261, 1999.CrossRefGoogle Scholar
  86. 86.
    C. Canudas de Wit and R. Horowitz, “Observers for tire/road contact friction using only wheel angular velocity information,” Proceedings of IEEE Conference on Decision and Control, vol. 4, pp: 3932–3937, 1999.Google Scholar
  87. 87.
    J. Yi, L. Alvarez, and R. Horowitz, et. al, “Adaptive emergency braking control using a dynamic tire/road friction model,” Proceedings of IEEE Conference on Decision and Control, vol. 1, pp: 456–461, 2000.Google Scholar
  88. 88.
    J. Yi, L. Alvarez, and X. Claeys, et. al, “Emergency braking control with an observer-based dynamic tire/road friction model and wheel angular velocity information,” Proceedings of American Control Conference, vol. l, pp: 19–24,2001.Google Scholar
  89. 89.
    L. Li, F.-Y. Wang, and G. Shan, et. al, “Design of tire fault observer based on estimation of tire/road friction conditions, Automatica Sinica, vol.28, no. 5, pp: 689–694, 2003.Google Scholar
  90. 90.
    J. R. Zhang, S. J. Xu, and A. Rachid, “Robust sliding mode observer for automatic steering of vehicles,” Proceedings of IEEE Intelligent Transportation Systems, pp: 89–94, 2000.Google Scholar
  91. 91.
    C. Lee, K. Hedrick, and K. Yi, “Real-time slip-based estimation of maximum tire-road friction coefficient,” IEEE/ASME Transactions on Mechatronics, vol. 9, no. 2, pp: 454–458, 2004.CrossRefGoogle Scholar
  92. 92.
    D. M. Bevly, J. C. Gerdes, and C. Wilson, “The use of GPS based velocity measurements for measurement of sideslip and wheel slip,” Vehicle System Dynamics, vol. 38, no. 2, pp. 127–147, 2002.Google Scholar
  93. 93.
    R. Daily and D. M. Bevly, “The use of GPS for vehicle stability control systems,” IEEE Transactions on Industrial Electronics, vol. 51, no. 2, pp: 270–277, 2004.CrossRefGoogle Scholar
  94. 94.
    W. Sienel, “Estimation of the tire cornering stiffness and its application to active car steering,” Proceedings of IEEE Conference on Decision and Control, vol. 5, pp: 4744–4749, 1997.Google Scholar
  95. 95.
    S. Saraf and M. Tomizuka, “Slip angle estimation for vehicles on automated highways,” Proceedings of American Control Conference, vol. 3, pp: 1588–1592, 1997.Google Scholar
  96. 96.
    L. R. Ray, “Nonlinear tire force estimation and road friction identification: simulation and experiments,” Automatica, vol. 33, no. 10, pp: 1819–1833, 1997.zbMATHCrossRefMathSciNetGoogle Scholar
  97. 97.
    L. R. Ray, “Experimental determination of tire forces and road friction,” Proceedings of American Control Conference, vol. 3, pp: 1843–1847, 1998.Google Scholar
  98. 98.
    B. Samadi, R. Kazemi, and K. Y. Nikravesh, et. al, “Real-time estimation of vehicle state and tire-road friction forces,” Proceedings of American Control Conference, vol. 5, pp: 3318–3323, 2001.Google Scholar
  99. 99.
    K. Huh, J. Kim, and K. Yi, et. al, “Monitoring system design for estimating the lateral tire force,” Proceedings of American Control Conference, vol. 2, pp: 875–880, 2002.Google Scholar
  100. 100.
    Kimbrough, S., “A brake control strategy for emergency stops that involve steering: Part 1 theory,” Proceedings of the 2nd Symposium on Transportation Systems, 1990 ASME Winter Annual Meeting, 1990.Google Scholar
  101. 101.
    Kimbrough, S., “A brake control strategy for emergency stops that involve steering: Part 2 implementation issues and simulation results,” Proceedings of the 2nd Symposium on transportation Systems, 1990 ASME Winter Annual Meeting, 1990.Google Scholar
  102. 102.
    R. Emig, H. Goebels, and H. J. Schramm, “Antilock braking systems (ABS) for commercial vehicles-status 1990 and future prospects,” Vehicle Electronics in the 90’s: Proceedings of the International Congress on Transportation Electronics, pp: 515–523, 1990.Google Scholar
  103. 103.
    R. Bosch, Automotive handbook, Robert Bentley, Publisher, 4th ed, 1997.Google Scholar
  104. 104.
    M. Schinkel and K. Hunt, “Anti-lock braking control using a sliding mode like approach,” Proceedings of American Control Conference, vol. 3, pp: 2386–2391, 2002.Google Scholar
  105. 105.
    P. E. Wellstead and N. B. O. L. Pettit, “Analysis and redesign of an anti-lock brake system controller,” IEE Proceedings-Control Theory and Applications, vol. 144, no. 5, pp: 413–426, 1997.CrossRefGoogle Scholar
  106. 106.
    P. Tsiotras and C. Canudas-de-Wit, “On the optimal braking of wheeled vehicles,” Proceedings of American Control Conference, vol. 1, no. 6, pp: 569–573, 2000.Google Scholar
  107. 107.
    D. Zhang, H. Zheng, and J. Sun, et. al, “Simulation study for anti-lock braking system of a light bus,” Proceedings of the IEEE International Vehicle Electronics Conference, pp: 70–77, 1999.Google Scholar
  108. 108.
    S. Drakunov, U. Ozguner, and P. Dix, et. al, “ABS control using optimum search via sliding modes,” IEEE Transactions on Control Systems Technology, vol. 3, no. 1, pp: 79–85, 1995.CrossRefGoogle Scholar
  109. 109.
    M. Krstik and H.-H. Wang, “Design and stability analysis of extremum seeking feedback for general nonlinear systems,” Proceedings of IEEE Conference on Decision and Control, pp. 1743–1748, 1997.Google Scholar
  110. 110.
    I. Petersen, T. A. Johansen, and J. Kalkkuhl, et. al, “Wheel slip control using gain-scheduled LQ-LPV/LMI analysis and experimental results,” European Control Conference, 2003.Google Scholar
  111. 111.
    S. Taheri and E. H. Law, “Slip control braking of an automobile during combined braking and steering manoeuvres,” Advanced Automotive Technologies, vol. 40, pp: 209–227, 1991.Google Scholar
  112. 112.
    K. Yi, K. Hedrick, and S. Lee “Estimation of tire-road friction using observer based identifiers,” Vehicle System Dynamics, vol. 31, no. 4, pp: 233–261, 1999.CrossRefGoogle Scholar
  113. 113.
    T. Shim and D. Margolis, “Model-based road friction estimation,” Vehicle System Dynamics, vol. 41, no. 4, pp: 249–276, 2004.CrossRefGoogle Scholar
  114. 114.
    W.R. Pasterkamp and H. B. Pacejka, “Application of neural networks in the estimation of tire/road friction using the tire as a sensor,” SAE #971122,1997.Google Scholar
  115. 115.
    M. Beato, V. Ciaravola, and M. Russo, et. al, “Lateral tyre force by a milliken test on a flat track roadway simulator,” Vehicle System Dynamics, vol. 34, pp. 117–129,2000.CrossRefGoogle Scholar
  116. 116.
    J. A. Cabrera, A. Ortiz, and E. Carabias, et. al, “An alternative method to determine the magic tyre model parameters using genetic algorithms,” Vehicle System Dynamics, vol. 41, no. 2, pp: 109–127, 2004.CrossRefGoogle Scholar
  117. 117.
    H. S. Bae, J. Ryu, and J. C. Gerdes, “Road grade and vehicle parameter estimation for longitudinal control using GPS,” Proceedings of IEEE Conference on Intelligent Transportation Systems, pp: 166–171, 2001.Google Scholar
  118. 118.
    W. R. Patserkamp and H. B. Pacejka, “The tire as a sensor to estimate friction,” Vehicle System Dynamics, vol. 27, pp. 409–422, 1997.CrossRefGoogle Scholar
  119. 119.
    A. Pohl, R. Steindl, and L. Reindl, “The “intelligent tire” utilizing passive SAW sensors measurement of tire friction,” IEEE Transactions on Instrumentation and Measurement, vol. 48, no. 6, pp: 1041–1046, 1999.CrossRefGoogle Scholar
  120. 120.
    A. Pohl, “A review of wireless SAW sensors,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 47, no. 2, pp: 317–332, 2000.CrossRefMathSciNetGoogle Scholar
  121. 121.
    M. Mizuno, H. Sakai, and K. Oyama, et. al, “The development of the tire side force model considering the dependence of surface temperature of tire,” Vehicle System Dynamics, vol. 41, pp. 361–370, 2004.Google Scholar
  122. 122.
    L. Li, and F.-Y. Wang, “Research advances in vehicle lateral motion monitoring and control,” International Journal of Intelligent Control and Systems, vol. 9, no. 3, 2004.Google Scholar

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