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Road Surface Condition Detection and Identification and Vehicle Anti-Skid Control

Ye, Maosheng
http://rave.ohiolink.edu/etdc/view?acc_num=csu1227197539

Abstract Details

2008, Master of Science in Mechanical Engineering, Cleveland State University, Fenn College of Engineering.
Road surface condition is greatly dependent on the surface's friction coefficient. The abrupt change of the coefficient results in variation of wheel slip which likely leads to vehicle instability. Vehicle steering model and the dynamic equations for four-wheel drive vehicle is developed. A new observer, called Extended State Observer (ESO) is used to estimate the longitudinal velocity, lateral velocity and yaw rate, and more importantly an additional quantity known as system dynamics. A trained neural network was employed to help determine the friction coefficient. Fuzzy logic was employed to quickly detect the change of road surface condition and further classify the surface condition. The presented methods were simulated with a vehicle encountering a significant change from a uniform-μ (i.e. uniform friction coefficient) surface to a split-μ surface (i.e. different friction coefficient on each side of the wheels) during cornering. The results this obtained show that the developed techniques could effectively detect and identify the road surface condition. Further more, a new anti-skid controller by means of Active Disturbance Rejection Controller (ADRC) and the ESO is proposed. The simulation results show that the controller can effectively control the vehicle's yaw rate while cornering.
Paul Lin, PhD (Committee Chair)
Zhiqiang Gao, PhD (Committee Member)
Majid Rashidi, PhD (Committee Member)
94 p.
Mechanical Engineering
Vehicle dynamics; Intelligent systems; Detection and Identification; Anti-skid Control; Extended State Observer; Active Disturbance Rejection Control

Recommended Citations

Citations

  • Ye, M. (2008). Road Surface Condition Detection and Identification and Vehicle Anti-Skid Control [Master's thesis, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1227197539

    APA Style (7th edition)

  • Ye, Maosheng. Road Surface Condition Detection and Identification and Vehicle Anti-Skid Control. 2008. Cleveland State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1227197539.

    MLA Style (8th edition)

  • Ye, Maosheng. "Road Surface Condition Detection and Identification and Vehicle Anti-Skid Control." Master's thesis, Cleveland State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=csu1227197539

    Chicago Manual of Style (17th edition)

csu1227197539
2,122
© 2008, all rights reserved.
This open access ETD is published by Cleveland State University and OhioLINK.