Abstract
This paper presents two effectively unbiased nonlinear estimation schemes which identify tire longitudinal stiffness and effective radius using Global Positioning System (GPS) and antilock braking system (ABS) wheelspeed sensors. A nonlinear approach is taken as one possible approach of eliminating the well known biases that linear least squares algorithms introduce for this problem. These new estimation strategies are then used to experimentally identify the longitudinal stiffness and effective radius of a summer tire and a winter tire under several different test conditions. The data clearly shows that there are several important parameters which govern tire longitudinal stiffness behavior in the low slip region. At a minimum, inflation pressure, tread depth, normal loading and temperature have a strong influence on longitudinal stiffness estimates; the change from dry to wet asphalt had the smallest effect on longitudinal stiffness estimates.
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