• Title/Summary/Keyword: Brush Tire Model

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Analysis of Limitation and Improvement of Degree of Freedom for Brush Tire Model (브러쉬 타이어 모델의 한계점 분석 및 자유도 개선)

  • Kim, Jong-Min;Jung, Samuel;Yoo, Wan-Suk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.7
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    • pp.585-590
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    • 2017
  • Vehicle behavior is determined by forces and a torques generated at the ground contact surface of the tire. Various tire models are used to calculate the forces and torques acting on the tire. The brush model calculates the forces and torques with fewer coefficients than other tire models. However, owing to fewer degrees of freedom in calculating the forces, this model has limitations in precisely expressing measured data. In this study, this problem was addressed by adding the least parameters to the friction coefficient and tire properties of the brush model, and the proposed model was validated.

A Study on Lateral Tire-road Friction Coefficient Estimation Using Tire Pneumatic Trail Information (타이어 뉴메틱 트레일 정보를 활용한 횡방향 타이어 노면 마찰 계수에 관한 연구)

  • Han, Kyoungseok;Choi, Seibum
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.3
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    • pp.310-318
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    • 2016
  • The demands for vehicle safety systems such as ABS and ESC have been increased. Accurate vehicle state estimation is required to realized the abovementioned systems and tire-friction coefficient is crucial information. Estimation of lateral tire-road friction coefficient using pneumatic trail information is mainly dealt in this paper. Pneumatic trail shows unique characteristics according to the wheel side slip angle and these property is highly sensitive to vehicle lateral motion. The proposed algorithm minimizes the use of conventional tire models such as magic formula, brushed tire model and Dugoff tire model. The pure side slip maneuver, which means no longitudinal dynamics, is assumed to achieve the ultimate goal of this paper. A simulation verification using Carsim and Simulink is performed and the results show the feasibility of the proposed algorithms.