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Tyre consumption.

2021 - USA - Total Cost of Vehicle Ownership
 6.94 MB

Detailed analysis of the total cost of ownership (TCO) consisting of all costs related to both purchasing and operating the vehicle. This TCO analysis builds on previous work to provide a comprehensive perspective of all relevant vehicle costs of ownership. In this report, we present what we believe to be the most comprehensive explicit financial analysis of the costs that will be incurred by a vehicle owner. This study considers vehicle cost and depreciation, financing, fuel costs, insurance costs, maintenance and repair costs, taxes and fees, and other operational costs to formulate a holistic total cost of ownership and operation of multiple different vehicles. For each of these cost parameters that together constitute a comprehensive TCO, extensive literature review and data analysis were performed to find representative values in order to build a holistic TCO for vehicles of all size classes. The light- and heavy-duty vehicles selected for analysis in this report are representative of those that are on the road today and expected to be available in the future. Table ES-1 summarizes the main parameters in this study, including the cost components which comprise TCO, the sizes and vocations of vehicles which are analyzed, the powertrains of these vehicles, and the model year for analysis of both current and future vehicles.

2019 - EU - Automobile Tyre and Break Wear
 497.82 KB

This chapter covers the emissions of particulate matter (PM) including black carbon (BC) ( 1 ) which are due to road vehicle tyre and brake wear (NFR code 1.A.3.b.vi), and road surface wear (NFR code 1.A.3.b.vii). PM emissions from vehicle exhaust are not included. The focus is on primary particles — in other words, those particles emitted directly as a result of the wear of surfaces — and not those resulting from the resuspension of previously deposited material. It should be noted that the second level of the NFR code for these emission sources relates to ‘combustion’. Clearly, tyre wear, brake wear and road surface wear are abrasion processes, not combustion processes. However, these chapters have been assigned their NFR codes as a matter of convenience, and to allow all emissions from road transport to be assessed together. For the present time, this anomaly has to be accepted by inventory compilers. PM emissions are considered in relation to the general vehicle classes identified in Chapter 1.A.3.b Road transport concerning exhaust emissions from road transport (NFR codes 1.A.3.b.i to b iv), these being passenger cars, light-duty trucks, heavy-duty vehicles and two-wheel vehicles.

The abrasion processes of rubber or tires are extremely complex phenomena and basically different from those of other materials. Much research in tire industry has been done to predict the wear of a tire tread. However, such studies have not considered the history dependency of abrasion as well as directional effects. This paper is to propose an advanced abrasion model for rubber that will takes these two effects into account. As a result the new model can be applied to predict tire tread wear. Within this model, directional damage will be introduced to characterize the history of frictional sliding contact including the change of slip directions. It also covers local contact conditions such as contact pressure, slip velocity or flash temperature. The model will be analyzed theoretically and numerically. A FEM simulation for the Grosch-wheel with different loading conditions using the new abrasion model is performed and validated by experimental data.

MIRAVEC Report D2.1.  This is a report of the findings in Work Package 2 (WP2) in MIRAVEC. The objective of this WP is to describe existing modelling tools and evaluate their capabilities with respect to analysing the effects identified in WP1 “Road infrastructure influence effects on vehicle energy consumption and associated parameters”. The variables identified in WP1 and considered to be the most important to take into consideration when estimating the impact of road infrastructure on road traffic energy use are texture (MPD), IRI (unevenness), rut depth (RUT), gradient (RF), crossfall, horizontal curvature (ADC), road width, traffic volume (AADT) and speed (v). In this report, a selection of projects that have evaluated road characteristics and the effect on energy use are described and analysed. The results of these project shows that there can be benefits energy wise in taking the energy aspect into consideration when planning a new road or choosing rehabilitation measure of the pavement. 

MIRAVEC Report D5.3.  The objective of MIRAVEC was to build on existing knowledge and models in order to achieve a more holistic view considering a broad variety of effects. The project results are compiled in this final report of MIRAVEC project. The first part of this final report is a short summary on the findings and outputs of all Work Packages (WP), while the second part is a summary of all recommendations to National Road Administrations (NRAs) on how to implement the findings, models and tools in pavement and asset management systems. The main findings and recommendations of the project can be summarised as follows:  Five major groups of parameters influencing road vehicle energy and fuel consumption were identified, of which a subset was selected based on impact, potential for influence by National Roads Administrations and integration into existing fuel consumption models. Further analysis showed that while currently monitored parameters can be used for modelling several effects of the infrastructure influence, knowledge gaps remain with respect to other parameters and the correct modelling of associated effects.  There is no current model which takes all infrastructure-related effects into account. Most models for fuel consumption and CO2 emission of road vehicles focus on vehicle and traffic flow characteristics and tend to neglect details of the infrastructure. The Swedish VETO model is one of the most advanced models in this respect and was the basis of many analyses. As the knowledge about the infrastructure influence increases, these models offer the possibility to integrate this knowledge into decision making.  The spreadsheet tool developed in WP3 allows the comparison of the effects of different infrastructure-related measures on fuel consumption and CO2 emission. It requires data about the most widely available pavement and road layout parameters and uses information about traffic flow and vehicles as background information. While the tool can be applied even with limited data, the strong influence of these background data found in the analysis may supersede the infrastructure effects in some cases.  The investigation of the current situation with regard to the occurrence of this topic in pavement and asset management found a growing awareness of its importance with road managers, but so far very limited implementation in the actual systems. While future models based on the more commonly monitored infrastructure parameters will make the integration of vehicle CO2 emission feasible, acceptance and weight in decision making in the view of limited financial resources for maintenance still remain to be achieved. 

2013 - EU - MIRAVEC Energy Project Documents
 2.22 MB

Various reports and presentations from the EU MIRAVEC looking at the impact of infrastructure on vehicle energy.

MIRAVEC Report D1.1: This document describes the different road infrastructure parameters which can contribute to the overall road vehicle energy consumption and highlights those which can be influenced by infrastructure design. It is a report on the effects and parameters that need be considered in order to determine the influence of road infrastructure on road vehicle energy consumption by modelling. The effects and properties were divided into the following five groups: A. Effects of pavement surface characteristics (rolling resistance, texture, longitudinal and transversal unevenness, cracking, rutting, other surface imperfections) B. Effects of road design and layout (e.g. road curvature, gradient and crossfall, lane provision) C. Traffic properties and interaction with the traffic flow (e.g. free flowing traffic vs. stop-and-go, speed limits, access restrictions) D. Vehicle and tyre characteristics including the potential effect of technological changes in this area E. Meteorological effects (e.g. temperature, wind, water, snow, ice)

2012 - China - Simulating Tyre Wear
 2.21 MB

The tire wear model is build based on Archard wear theory. In this tire wear model, the steady rolling of tire is considred. Moerover, the analisys for the steady rolling of tire is used in the simulation. In this paper, 195/65R15 tire is used to build a 3D tire FE model for simulation. The tire radial direction modal and natural frequency are calculated to valitate the 3D tire FE model. At first, using Pro/E and Abaqus software the tire patten is obtained. Next, the contact footprint and pressure between tire and road are analyzed with the tire rolling dynamics. The three situations are considered to analyze the state of tire wear, the side slip angles, the vertical load and the inner pressure.

2011 - China - Simulation of Tyre Wear
 100 KB

The theory of tire wear computation is researched, and steady state transfer analysis and steady state rolling slippage are analyzed and deduced; the uniform wear rate of discrete node on the tire tread pattern is induced based on adhesive wear mechanism. Tire body model and tread pattern model are established by using Neo-Hooken constitutive model and linear elastic model, and the whole tire model is formed. Tire wear simulation analysis is preceded with combination of Abaqus Arbitary Lagrangian and Eulerian (ALE) method and the user subroutine programmed according to tire wear computation model. Tire wear of different mileage under free rolling state, tire wear under breaking condition and driving condition are compared, and slip angle, load and tire pressure’s impact on tire wear are analyzed.

2011 - China - Analysis of Impact Factors of Tyre Wear
 100 KB

The formula of tire wear is established considering temperature effect and the dynamic characteristics of vehicles. In addition, the effects of speed, ambient temperatures, tire pressure and sprung mass for tire wear are analyzed. Finally, the main impact factors of tire tread wear are obtained through the parameters sensitivity analysis. The results show that: the established model of tire wear is feasible, and the results can reflect the wear conditions of tires, which provides a theoretic foundation to predict tire wear for different types of tire under different running conditions.

2000 - NZ - Memos on Tyre Modelling
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Memos giving additional background to mechanistic tyre modelling.

1999 - WB - Tyre Wear Modelling for HDM 4
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This study has aimed to determine an appropriate formulation for the calculation of tyre wear in HDM 4. In particular, a method has been proposed for calculating the eased tyre wear which occurs in congested traffic conditions, compared to free flowing traffic conditions at the same mean speed on a homogeneous section of road.

1999 - Tyre Consumption Modelling Issues
 43.38 KB

Memo describing issues with HDM-4 tyre consumption modelling

1999 - Japan - Tire Model to Predict Treadwear
 100 KB

This study examines treadwear on tires caused by low severity cornering during free roll. The authors previously proposed a method to predict treadwear using rubber pad wear tests. This method required measurements from actual tires to obtain the tread frictional parameters, i.e., the sliding distance, sliding velocity, and contact pressure. The present study proposes an analytical tire model for predicting treadwear that does not require measurements from actual tires. This enables treadwear prediction during the tire design stage, prior to test tire construction. A continuous tread model for lateral tread deformation is described to evaluate the frictional parameters. The treadwear is then predicted from the parameters and the rubber pad wear rate. The predicted treadwear rates are compared with actual treadwear rates and are found to be valid in the tread center area.

1998 - Tyre Wear Modelling for HDM-4
 185.09 KB

Report describing tyre consumption model, particularly congestion effects

1998 - Tyre Wear Modelling for HDM-4
 50 KB

Report describing mechanistic tyre model

1998 - Predicting Tyre Diameter
 59.99 KB

Memo describing how tyre diameter is predicted

1998 - Predicting the Volume of Wearable Rubber
 50 KB

Development of the model for predicting rubber volume

1998 - NZ - Tyre Wear Modelling for HDM 4
 162.26 KB

This study has aimed to determine an appropriate formulation for the calculation of tyre wear in HDM 4. In particular, a method has been proposed for calculating the increased tyre wear which occurs in congested traffic conditions, compared to free flowing traffic conditions at the same mean speed on a homogeneous section of road.

1998 - NZ - Tyre Modelling for HDM-4
 472.08 KB

Report from NZ on mechanistic tyre modelling.

1998 - Japan - Model to Predict Treadwear
 408.95 KB

How to predict tire traction and wear.

1998 - France - Evaluation of Tire Wear Performance
 320.04 KB

Evaluation of tire consumption.

1996 - Sweden - Modeling Tyre Consumption
 779.1 KB

Paper proposing mechanistic modelling of tyre consumption.
This report presents the results of a research project to investigate the suitability of fixed slip friction meters for on-road determination of pavement surface arasiveness. It was intended that this would involve establishing a degree of correlation between tyre abrasion and the road surface friction coefficient, as measured by Central Laboratories' Findlay Irvine GripTester.

1995 - Sweden - Swedish Tire Research
 791.39 KB

Paper summarizing Swedish tire modelling research.

1995 - Sweden - Swedish Research on Tire Consumption
 480.58 KB

Paper proposing mechanistic modelling of tyre consumption.

1995 - Sweden - Memo on Tyre Modelling
 248.95 KB

Paper proposing mechanistic modelling of tyre consumption.

1981 - Shallanmach - Tire Traction and Wear
 1.31 MB

How to predict tire traction and wear.