Model learning of the tire–road friction slip dependency under standard driving conditions

Abstract Tread pattern wear is predicted by using an explicit finite element model (FEM) and compared with the indoor drum test results under a set of actual driving conditions. One pattern is used to determine the wear rate equation, which is composed of slip velocity and tangential stress under a single driving condition. Two other patterns with the same size (225/45ZR17) and profile are used to be simulated and compared with the indoor wear test results under the actual driving conditions. As a study on the rubber wear rate equation, trial wear rates are assumed by several constitutive equations and each trial wear rate is integrated along time to yield the total accumulated wear under a selected single cornering condition. The trial constitutive equations are defined by independently varying each exponent of slip velocity and tangential stress. The integrated results are compared with the indoor test results, and the best matching constitutive equation for wear is selected for the following wear simulation of two other patterns under actual driving conditions. Tens of thousands of driving conditions of a tire are categorized into a small number of simplified conditions by a suggested simplification procedure which considers the driving condition frequency and weighting function. Both of these simplified conditions and the original actual conditions are tested on the indoor drum test machines. The two results can be regarded to be in good agreement if the deviation that exists in the data is mainly due to the difference in the test velocity. Therefore, the simplification procedure is justified. By applying the selected wear rate equation and the simplified driving conditions to the explicit FEM simulation, the simulated wear results for the two patterns show good match with the actual indoor wear results.

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A Modified Dugoff Tire Model for Combined-slip Forces

Tire Science and Technology ◽

10.2346/1.3481696 ◽

2010 ◽

Vol 38 (3) ◽

pp. 228-244 ◽

Cited By ~ 19

Author(s):

Nenggen Ding ◽

Saied Taheri

Keyword(s):

Vehicle Dynamics ◽

Tire Model ◽

Magic Formula ◽

Model Based ◽

Proposed Model ◽

Road Friction ◽

On Line ◽

Double Lane Change ◽

Tire Forces ◽

Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

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Prediction of Tire Tread Wear with FEM Steady State Rolling Contact Simulation

Tire Science and Technology ◽

10.2346/1.2135268 ◽

2003 ◽

Vol 31 (3) ◽

pp. 189-202 ◽

Cited By ~ 24

Author(s):

D. Zheng

Keyword(s):

Weight Loss ◽

Steady State ◽

Cross Section ◽

Rolling Contact ◽

Dynamic Simulations ◽

Element Analysis ◽

Vehicle Acceleration ◽

Steady State Rolling ◽

Driving Conditions ◽

Rate Profile

Abstract A procedure based on steady state rolling contact Finite Element Analysis (FEM) has been developed to predict tire cross section tread wear profile under specified vehicle driving conditions. This procedure not only considers the tire construction effects, it also includes the effects of materials, vehicle setup, test course, and driver's driving style. In this algorithm, the vehicle driving conditions are represented by the vehicle acceleration histogram. Vehicle dynamic simulations are done to transform the acceleration histogram into tire loading condition distributions for each tire position. Tire weight loss rates for different vehicle accelerations are generated based on a steady state rolling contact simulation algorithm. Combining the weight loss rate and the vehicle acceleration histogram, nine typical tire loading conditions are chosen with different weight factors to represent tire usage conditions. It is discovered that the tire tread wear rate profile is changing continuously as the tire is worn. Simulation of a new tire alone cannot be used to predict the tire cross-section tread wear profile. For this reason, an incremental tread wear simulation procedure is performed to predict the tire cross section tread wear profile. Compared with actual tire cross-section tread wear profiles, good results are obtained from the simulations.

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Effect of Polymer, Road Surface, and Driving Conditions on Wear Surface Characteristics of Tire Treads

Tire Science and Technology ◽

10.2346/1.2167171 ◽

1973 ◽

Vol 1 (4) ◽

pp. 354-362 ◽

Cited By ~ 2

Author(s):

F. R. Martin ◽

P. H. Biddison

Keyword(s):

Wear Surface ◽

Surface Characteristics ◽

Road Surface ◽

The Other ◽

Mechanical Degradation ◽

Textured Surface ◽

Test Track ◽

Driving Conditions ◽

Styrene Butadiene ◽

Cylindrical Particles

Abstract Treads made with emulsion styrene-butadiene copolymer (SBR), solution SBR, polybutadiene (BR), and a 60/40 emulsion SBR/BR mixture were built as four-way tread sections on G78-15 belted bias tires, which were driven over both concrete and gravel-textured highways and on a small, circular, concrete test track. The tires were front mounted. When driven on concrete highway, all except the BR tread had either crumbled- or liquid-appearing surfaces, thought to have been formed by mechanical degradation or fatigue. When cornered on concrete, these materials formed small cylindrical particles or rolls. The BR tread had a smooth, granular-textured surface when driven on concrete highway and a ridge or sawtooth abrasion pattern when cornered on concrete. All the materials appeared rough and torn when run on gravel-textured highway. The differences in wear surface formed on BR tread and the other three are thought to be due primarily to the relatively high resilience of BR.

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An Expert Data-Driven Air Combat Maneuver Model Learning Approach

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-0526 ◽

2021 ◽

Author(s):

Su-Jeong Park ◽

Soon-Seo Park ◽

Han-Lim Choi ◽

Kyeong-Soo An ◽

Young-Gon Kim

Keyword(s):

Data Driven ◽

Learning Approach ◽

Model Learning ◽

Air Combat ◽

Expert Data

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PERBAIKAN KUALITAS PEMBELAJARAN DAN HASIL BELAJAR SISWA DENGAN MODEL LEARNING CYCLE COOPERATIVE 5 FASE DALAM PENGAJARAN KIMIA

Konstruktivisme Jurnal Pendidikan & Pembelajaran ◽

10.30957/konstruk.v7i1.22 ◽

2015 ◽

Vol 7 (1) ◽

pp. 29-38

Author(s):

Esti Munafiah ◽

Agus Basir Ali Akbar S

Keyword(s):

Action Research ◽

Learning Process ◽

Mastery Learning ◽

Learning Cycle ◽

Model Learning ◽

Classroom Action Research ◽

Academic Year

The objective of this study is to see learning process using LCC model for chemistry course. The study used classroom action research with three cycles each of which implements planning, acting, observing and reflection. Subject of the study was 40 students of grade 8E of MTsN Blitar in the academic year 2009/2010. The findings of the study are as follows: (1) Cycle I: students participation 62.5%, mean score of worksheet 60, mean score of quiz 41,7, and mastery learning 3 students; (2) Cycle II: students participation 86.6%, mean score of worksheet 81, mean score of quiz 72.38, and mastery learning 26 students; (3) Cycle III: students participation 100%, mean score of worksheet 89, mean score of quiz 72.44, and mastery learning 39 students.

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