1. INTRODUCTION The tractive and braking performance of tires on ice has drawn much attention from the researchers around the world, as it is closely related to the vehicle active safety system. It is important, for example, to know how the Anti-lock Brake System (ABS) will perform for a car running on icy roads. In order to consider the tire performance under such conditions as part of the vehicle control system, an adequate tire model is needed; this effort includes the model development, the parameterization of the model, and the collection of the experimental tire-ice data needed for model parameterization and validation. A relatively small number of previous studies focused on the mathematic model that predicts the traction performance of tire on ice and could be possibly used on the vehicle control system. A model of traction force in the tire contact patch on ice was proposed by Hayhoe [1] assuming that the contact patch could be divided into two regions: a dry sliding region and a water flm region. Based on the same assumption, subsequent models for predicting the traction force of tire on ice, with higher accuracy and simpler expression relative to the model in [1], were developed by Peng [2, 3]. However, none of those models takes into account the non-uniformity of the pressure distribution in the contact patch, which a modular-structured model, proposed by Bhoopalam [4], does. Furthermore, while the aforementioned models are shown to predict the tractive performance of tire on ice within an acceptable tolerance, none of them account for the lateral dynamics properties of tires, which are critical in predicting the lateral forces. Therefore, such models may not be suitable for use in the vehicle control system that has to control the lateral dynamics. For these control systems, a modifed version of the Dugoff tire model could be employed to characterize the lateral and the longitudinal tire forces in the sideslip angle and road friction estimation [5, 6, 7]. Experimental testing of tires on ice can illustrate the infuence of operational parameters on the tractive, braking, and handling performance of a tire, and can provide the necessary validation data for tire-ice interaction models, as well as for the parameterization of Investigating the Parameterization of Dugoff Tire Model Using Experimental Tire-Ice Data Rui He and Emilio Jimenez Virginia Tech. Dzmitry Savitski Technische Universitat Ilmenau Corina Sandu Virginia Tech Valentin Ivanov Technische Universitat Ilmenau ABSTRACT Tire modeling plays an important role in the development of an Active Vehicle Safety System. As part of a larger project that aims at developing an integrated chassis control system, this study investigates the performance of a 19” all-season tire on ice for a sport utility vehicle. A design of experiment has been formulated to quantify the effect of operational parameters, specifcally: wheel slip, normal load, and infation pressure on the tire tractive performance. The experimental work was conducted on the Terramechanics Rig in the Advanced Vehicle Dynamics Laboratory at Virginia Tech. The paper investigates an approach for the parameterization of the Dugoff tire model based on the experimental data collected. Compared to other models, this model is attractive in terms of its simplicity, low number of parameters, and easy implementation for real-time applications. The relations correlating tire forces with slip ratios were identifed by applying zero-phase fltering techniques to the raw test data. Next, an optimization procedure was utilized to extract parameters for the Dugoff tire model from the tire-on-ice drawbar pull coeffcient versus slip ratio at certain levels of normal load and infation tire pressure. CITATION: He, R., Jimenez, E., Savitski, D., Sandu, C. et al., "Investigating the Parameterization of Dugoff Tire Model Using Experimental Tire-Ice Data," SAE Int. J. Passeng. Cars - Mech. Syst. 10(1):2017, doi:10.4271/2016-01-8039. Published 09/27/2016 Copyright © 2016 SAE International doi:10.4271/2016-01-8039 saepcmech.saejournals.org 83 © SAE International