Radial Tire Research Articles

The Tyres of Change: Remittances as a Wheel of Development in Pirot, Serbia

This article explores the agency of Yugoslav migrant workers ( Gastarbeiter) and their visions of development, focusing on the establishment of a so-called remittance factory (a manufacturing facility founded primarily using the earnings of citizens working abroad, known as remittances) in the town of Pirot in today’s Serbia. The factory, ‘Tigar’, a major producer of radial Tyres since 1972, became the ‘wheel of development’ in Pirot during the socialist era. The social effects of Gastarbeiter remittances, including changes in gender roles and community cohesion, will also be explored. While Yugoslav migration theorists have primarily critiqued the irrational expenditure of Gastarbeiter savings, my research reveals that, when examined at the micro-level, Gastarbeiter demonstrated prudent investment behaviour, utilising their savings purposefully to contribute to local development upon their return. Through the use of different historical sources (documentary evidence, newspapers and oral history), this article will contribute to a deeper understanding of the complex dynamics of migration, remittance behaviour and development in socialist Yugoslavia. It will underscore the importance of recognising the agency of Gastarbeiter as one of the key contributors to the development of ‘Tigar’ factory, which still operates today, now as part of the French-owned Michelin group. Despite the article’s focus on a single case study, the same research approach can be applied to similar cases, not only in Southeast Europe but also in other emigration regions.

Application of wet carbon black masterbatch in green mining radial tires

AbstractIn the context of environmental protection and energy consumption reduction, reducing the rolling resistance of mining machinery tires is one of the important methods to achieve the goal of green mining. This study probes the effects of wet mixing with a wet carbon black masterbatch on the rolling resistance and grounding performance of wide‐body vehicle tire treads by investigating the cross‐linking structure, rubber–filler (R–F) interaction force, and physicomechanical properties of the wet mixing rubber compounded with a wet carbon black masterbatch. The results indicate decreases in the maximum torque‐minimum torque difference, cross‐link density, and R–F interaction of the wet mixing rubber and increased filler–filler (F–F) interaction and carbon black dispersion. Meanwhile, the tensile elongation of the wet mixing rubber increases, its DIN abrasion property improves, and its Tanδ decreases at 60°C. A numerical method to estimate tire steady‐state rolling resistance is also developed. Finite element simulation analysis reveals that the steady‐state rolling resistance of the wet mixing rubber is reduced by 7.04% at 100% standard load, and its grounding performance is enhanced. By proposing a method to reduce the rolling resistance of tires, this study also provides a reference for the development of wide‐body vehicle tires.Highlights Explored the filler interaction of wet mixing rubber. Explained the low energy loss of wet mixing rubber. Proposed a new finite element method for calculating tire rolling resistance.

Comparative study on rolling resistance force in tire-ice interaction with a variation of tread rubber compound

Abstract The complex phenomenon involved in the tire-ice interaction can be better understood by studying the tire and ice properties. A significant force at the contact patch is the rolling resistance force. To study the effect of tire characteristics on rolling resistance forces, data collected from a free-rolling tire can be used as there is no tractive or braking torque applied to the wheel and thus the data representing the longitudinal forces is only related to resistive forces viz. friction and rolling resistance force. Although a lot of research and literature has been developed for tire-ice interaction over the years, there is a significant lack of work in the subsection of free-rolling tires specifically to study the effect of ice parameters on rolling resistance forces. To fulfill the aim of this study, several sets of experiments for 16 winter tires of 8 different rubber compounds in free-rolling conditions were conducted. The experimental data was compared with predictions of 4 well-known formulations from the literature. Based on the findings and the relative error between the predicted and measured values, it was proposed that the high error percentage could be due to the variation in the viscoelastic properties of the tread rubber. The longitudinal force generated during those tests would thus be a combination of frictional forces due to adhesion between the tread rubber and its viscoelastic nature in addition to the contribution from the remaining sections of the tire. The data collected from the experiments and results from implementing the existing models to obtain frictional force will further help in analyzing the relation between the rolling resistance force with variation in normal load, inflation pressure, and change in camber angle once a generic formulation considering the rubber compound effects is incorporated. Another significant finding of this work is that formulations in literature used for finding the rolling resistance coefficient of radial passenger car tires were found to highly underestimate the coefficient when compared to the equivalent coefficient of friction found from experimental results. The future scope may include the development of a model which will incorporate the viscoelastic properties, especially the loss moduli and loss tangent to evaluate the coefficient of friction and rolling resistance force in the free-rolling condition of a winter tire on ice as the rolling resistance losses are found to be highly correlated to these two properties.

Comparison of Radial Ply and Cross Ply Tire in Terms of Achieved Rolling Resistance and Soil Compaction in a Soil Test Channel

Many literature sources state that radial ply tires achieve lower rolling resistance values than cross ply tires. From a certain point of view, radial ply tires are gentler on the ground than cross ply tires. The effort was therefore to experimentally verify this statement for two radial ply and cross ply tires similar in shape and size. The work deals with the diagnostics of rolling resistance levels achieved by radial ply and cross ply tires on selected forest soil under the laboratory conditions of a soil test channel. BKT 210/95 R16 Agrimax RT 855 and Özka 7.50-16 8PR KNK 50 were chosen as radial ply and cross ply tires, respectively, and had approximately the same dimensions. The soil in the soil test channel can be characterized as a loamy sand with an average moisture content of 30% and an initial bulk density of 1445.07 kg·m−3. Another monitored parameter was the diagnostics of changes in soil density caused by tire movement in order to assess the degree of soil compaction. From the results of the work, it follows that there is no statistically significant difference between radial ply and cross ply tires in terms of the achieved levels of rolling resistance on the soil. The observed tires also caused intense compaction of the soil in the soil test channel, especially at higher tire pressures and higher vertical loads. The analysis of the results also shows that changes in tire pressure in both tires cause more energy loss and soil compaction than changes in the vertical load.

Numerical Study of Tangential Traction Mechanism between Pattern Blocks of Agricultural Radial Tires and Soft Soil.

With the increasing requirements of agricultural machinery, the study of the contact relationship between the tire-soil interface and the improvement of traction efficiency has gradually become a main concern. In this study, the pattern on the agricultural tire was simplified into single-pitch pattern blocks. The pattern blocks were made of rubber material that was highly resistant to abrasion and bending. The experiment was carried out by pressing the three types of patterned block construction into the soil and the pure sliding under the soil. The simulation used the Coupled Eulerian-Lagrangian Method (CEL) to verify the experimental results. We found that the herringbone pattern block was subjected to the highest stress for the same depth of downward pressure. The horizontal force generated by the pure sliding was also the highest. The results showed that the numerically simulated and experimentally measured data exhibited similar trends and average values. In addition, the increase in the contact area between the tire and the soil reduced the compaction and sinking of the soil. The herringbone pattern structure not only had a large contact area but also produced the most significant shear force on the soil. Thus, it may generate greater traction in actual operations.

Unlocking the potential of lignin: Towards a sustainable solution for tire rubber compound reinforcement

This study tackles the persistent challenge of producing highly reinforced lignin-rubber composites, emphasizing the transformation of agro-industrial residues into value-added products. To address this challenge, we introduce a novel approach termed “in-situ surface modification utilizing a thermo-chemo-mechanical approach” which incorporates the utilization of biomass-derived kraft lignin and a thermally stable organofunctional surface modifier, specifically (3-aminopropyl) triethoxysilane. The resulting material exhibits unprecedented tensile strength (∼15 MPa) along with ∼300 % elongation at break, while typical gum rubber offers 1–2 MPa tensile strength. Additionally, for the other tensile properties like 100 %, and 200 % tensile modulus, the improvement is 7-fold (∼5.6 MPa) and 10-fold (∼11.3 MPa), respectively. Furthermore, this composite presents a higher degree of reinforcement than a passenger car radial (PCR) tire model compound (tensile strength ∼14.5 MPa, 100 % tensile modulus ∼2.2 MPa, and 200 % tensile modulus ∼5.6 MPa) comprised of silica and polysulfide-based coupling agent, with exactly a similar loading of filler. The dynamic mechanical and stress relaxation behavior of the composites are critically discussed concerning the dispersion of the lignin in the sSBR/BR rubber matrix. The morphological orientation and involved chemical interaction in the presence of a surface modifier are also studied in detail. Tear fatigue analysis using pure shear specimens indicates superior fracture toughness at a lower tearing energy regime compared to silica-filled PCR tire compounds. Overall, this study showcases the potential of lignin-reinforced elastomers, offering a promising route for sustainable engineering materials and commercial viability.

Utilizing Selected Machine Learning Methods for Conicity Prediction in the Process of Producing Radial Tires for Passenger Cars

This article presents the current state and development directions of the tire industry. One of the main requirements that a tire must meet before it can leave the factory is achieving values of quantities describing uniformity at a defined level. Of particular importance areconicity and the components of the tire with the greatest impact on its value. This research is based on the possibility of using an ANN to meet contemporary challenges faced by tire manufacturers. In order to achieve a satisfactory level of prediction, we compared the use of a multi-layer perceptron and decision trees XGBoost, LightGbmRegression, and FastTreeRegression. Based on data analysis and similar examples from the literature, metrics were selected to evaluate the models’ ability to solve regression problems in relation to the described problem. We selected the best possible solution, standing at the top of the features covered by the criterion analysis. The proposed solutions can be the basis for acquiring new knowledge and contributions in the field of the computational analysis of industrial data in tire production. These solutions are characterized by the required accuracy and efficiency for online work, and they also contribute to the creation of the best fit elements of complex systems (including computational models). The results of this study will contribute to reducing the volume of waste in the tire industry by eliminating defective tire parts in the early stages of the production process.

A Robust Design for the Omnibus SPRT Control Chart Under Skewed Data Distributions

Control charts are widely used in manufacturing industries to ensure that production levels are stable and satisfactory. Recently, the omnibus sequential probability ratio test (OSPRT) control chart was developed for the purpose of monitoring the mean and variability of a process simultaneously. As the OSPRT chart was proposed for the first time in literature, its development relied entirely on the assumption that data follow the Normal distribution. Nonetheless, researchers are frequently reminded that the quality characteristics of manufacturing processes do not necessarily follow the Normal distribution, e.g., strengths of glass fibres, and lifetimes of products. In this paper, we investigate the extent to which the performances of the OSPRT chart designed for the Normal model deteriorate, in situations where the data distributions are Gamma and Lognormal. Results show that the in-control average run length (ARL) and standard deviation of the run length of the OSPRT chart designed for the Normal distribution deteriorate rapidly as skewness increases. To address this issue, we propose a robust design for the OSPRT chart by adjusting its control limits, known as the skewness correction method. It is shown that the skewness-corrected OSPRT chart enjoys a guaranteed in-control ARL, with a justifiable degradation in its out-of-control performances. Besides, we also show some insights into selecting the charting parameters for the skewness-corrected OSPRT chart in order to achieve an optimum out-of-control ARL performance over various shift sizes. The paper wraps up with an illustrative example of the skewness-corrected OSPRT chart for monitoring the weights of radial tyres.

Evaluation of the Changes in Dimensions of the Footprint of Agricultural Tires under Various Exploitation Conditions

This paper presents an innovative method to determine the impact of agricultural wheels on soil. The experiment was conducted under controlled conditions, and the parameters of the tire footprints on the soil were analyzed. The tested parameters were the width, length, and depth of the footprint, the cross-section area of the tire, and the area of the footprint. All parameters were determined using the 3D scanning method. Two types of tires, two levels of vertical load, and three levels of inflation pressure were used. The aim of the research was to demonstrate differences in changes in the footprint parameters as a result of changes in the operational parameters of the tires. It was found the bias-ply tire was less responsive to changes in the width and length of the footprint than the radial tire. Moreover, it was shown that radial and bias-ply tires achieved similar values for the footprint area but in the case of bias-ply tires, there was a much greater footprint depth. This means that the side parts of the footprint of bias-ply tires have a more vertical profile, so they carry the vertical loads to a lesser extent.

An Improved YOLOv5 Algorithm for Tyre Defect Detection

In this study, a tyre defect detection model is improved and optimized under the YOLOv5 framework, aiming at radial tyre defects with characteristics such as an elongated shape and various target sizes and defect types. The DySneakConv module is introduced to replace the first BotteneckCSP in the Backbone network. The deformation offset of the DySneakConv module is used to make the convolutional energy freely adapt to the structure to improve the recognition rate of tyre defects with elongated features; the AIFI module is introduced to replace the fourth BotteneckCSP, and the self-attention mechanism and the processing of large-scale features are used to improve the recognition rate of tyre defects with elongated features using the AIFI module. This latter module has a self-attention mechanism and the ability to handle large-scale features to solve the problems of diverse tyre defects and different sizes. Secondly, the CARAFE up-sampling operator is introduced to replace the up-sampling operator in the Neck network. The up-sampling kernel prediction module in the CARAFE operator is used to increase the receptive field and allow the feature reorganization module to capture more semantic information to overcome the information loss problem of the up-sampling operator. Finally, based on the improved YOLOv5 detection algorithm, the Channel-wise Knowledge Distillation algorithm lightens the model, reducing its computational requirements and size while ensuring detection accuracy. Experimental studies were conducted on a dataset containing four types of tyre defects. Experimental results for the training set show that the improved algorithm improves the mAP0.5 by 4.6 pp, reduces the model size by 25.6 MB, reduces the computational complexity of the model by 31.3 GFLOPs, and reduces the number of parameters by 12.7 × 106 compared to the original YOLOv5m algorithm. Experimental results for the test set show that the improved algorithm improves the mAP0.5 by 2.6 pp compared to the original YOLOv5m algorithm. This suggests that the improved algorithm is more suitable for tyre defect detection than the original YOLOv5.

Analysis of Vibration Characteristics and Influencing Factors of Complex Tread Pattern Tires Based on Finite Element Method

The vibration of the tires significantly impacts a vehicle’s ride comfort and noise level; however, the current analysis of tire vibration characteristics often involves excessive simplification in their models, leading to a reduction in model accuracy. To analyze the tire vibrational properties and the influence of its design and service conditions, a combined modeling technology was developed to construct a three-dimensional (3D) finite element model of a 205/55R16 specification radial tire with intricate tread patterns. The accuracy and reliability of the simulation model was verified through vibration modal tests. Based on the vibration mode theory, the Lanczos method provided by ABAQUS was adopted to analyze the modal characteristics of the tire under free inflation and grounded conditions, and the effects of different inflation pressures, loads, operating conditions, and belt cord angles on the tire vibration characteristics were analyzed. The results indicate that grounding constraints will suppress the low order radial modal frequency of the tire and enhance the lateral modal frequency. The higher the order of the tire vibration mode, the greater the impact of inflation pressure. As the operating conditions change, the modal frequencies of all directions have the same trend of change, and as the ground load increases, the tire is prone to misalignment at lower lateral frequencies. The radial and lateral grounding modes of the tire are slightly affected by the change of the cord angle in the belt layer, but the circumferential grounding frequency decreases as the belt layer angle increases. These research findings offer a crucial foundation for the structural design of complex tread pattern tires, and also serve as a reference for addressing vibration and comfort issues encountered in the tire matching process.

Finite Element Modeling of Steel Cord in Engineering Radial Tires Using Parametric Equations

Finite Element Modeling of Steel Cord in Engineering Radial Tires Using Parametric Equations

Exploring experimental and finite element analysis to examine nano zinc oxide as a replacement for rubber‐grade zinc oxide in passenger car tire bead filler compounds

AbstractThe investigation demonstrates the potential of nano zinc oxide as a substitute for conventional rubber grade zinc oxide in the bead filler compound of passenger car tires, aimed at reducing heat generation while preserving mechanical and reinforcement properties. Experimentation showed that introducing nano zinc oxide increased compound viscosity, indicating enhanced filler networking. Cure rates accelerated due to the higher surface area of nano zinc oxides, while the Payne effect indicated improved dispersion levels in experimental compounds. Notably, the variant with four parts per hundred rubber of nano zinc oxide exhibited mechanical properties akin to the control, alongside a 28% reduction in tan δ and improvements in hysteresis loss ratio and specific heat values. Morphological analysis confirmed superior dispersion in experimental compounds. Finite element analysis demonstrated decreased temperature generation and a reduced percentage contribution of the bead filler to overall heat energy in tires, leading to a 3% drop in rolling resistance. These findings suggest that nano zinc oxide can effectively replace conventional zinc oxide, enhancing fuel economy in tires, thereby offering a green initiative to reduce fuel consumption in passenger car radial tires through improved hysteresis at the bead area via bead filler compound modification.Highlights Nano zinc oxide replaces rubber grade zinc oxide reducing heat generation. Nano zinc oxide improves compound viscosity, enhancing filler networking. Variant with four parts per hundred rubber of nano zinc oxide matches control's mechanics, with 28% lower tan δ. Morphological analysis confirms dispersion, coupled with aggregation. Simulation shows lower temperature generation and 3% less rolling resistance.

Effects of road- vs. field-recommended tyre inflation pressures and small variations in soil moisture content on traffic-induced soil compaction during seedbed preparation

Soil compaction has become one of the most common forms of soil degradation, with associated negative effects on the functioning of agricultural soils. Decades of research have led to publication of several practical measures that mitigate risk of soil compaction, yet adoption among European farmers remains limited. To improve adoption by farmers, experiments under practical conditions using common operations should be performed. A field experiment was set up to evaluate the effects of road- (200 kPa) vs. field- (140 kPa and 100 kPa) recommended tyre inflation pressure and soil moisture content (0.24 g g−1 vs. 0.22 g g−1) on traffic-induced compaction of a silt loam soil during seedbed preparation. The various tyre inflation pressures were tested using two tyre types (standard radial tyre at 200 kPa and 140 kPa; VF tyre at 100 kPa) of similar dimensions mounted onto the same tractor. Variation in experimental soil moisture content was achieved by performing the seedbed preparation on two dates in spring (early, March 30th, vs. late, April 14th). In this one-year study, reducing the standard-tyre inflation pressure from road- (200 kPa) to field-recommended (140 kPa) pressure did not prevent soil compaction. The use of VF tyres at field-recommended (100 kPa) tyre inflation pressure resulted in significant reductions in vertical contact stress and mean normal stress as compared to 200 kPa. Although non-significant, the pressure reduction from 200 kPa to 140 kPa did result in a 4 % increase in in-track dry matter sugar beet yield while a reduction from 200 kPa to 100 kPa resulted in an 11% increase. Lower tyre inflation pressure showed no significant effect on fuel consumption and penetration resistance. Seedbed preparation under slightly drier (0.22 g g−1) soil conditions negatively affected fuel consumption (+11 %) and resulted in an in-track dry matter sugar beet yield increase of 11 %. For both tested prevention strategies, the impact of soil compaction was better observable by sugar beet yield than by most of the measured soil physical parameters.

Tire mode shape categorization using Zernike annular moment and machine learning classification

This research proposes a framework for categorizing the radial tire mode shapes using machine learning (ML) based classification and feature recognition algorithms, advancing the development of a digital twin for tire performance analysis. Tire mode shape categorization is required to identify modal features in a specific frequency range to maximize driving performance and secure safety. However, the mode categorization work requires a lot of manual effort to interpret modes. Therefore, this study suggests an ML-based classification tool to replace the conventional categorization process with two primary objectives: (1) create a database by categorizing the tire mode shapes based on the identified features and (2) develop an ML-based surrogate model to classify the tire mode shapes without manual effort. The feature map of the tire mode shape is built with the Zernike annular moment descriptor (ZAMD). The mode shapes are categorized using the correlation value derived by the modal assurance criteria (MAC) with all ZAMD values for each tire mode shape and subsequently creating the appropriate labels. The decision tree, random forests, and XGBoost, the representative supervised-learning algorithms for classification, are implemented for surrogate model development. The best-performed classifier can categorize the mode shapes without any manual effort with a high accuracy of 99.5%.

ARTIFICIAL INTELLIGENCE APPLIED TO QUALITY DEFECTS CLASSIFICATION FOR TYRES

The manufacture of radial tires is complex, and for this reason some defects inevitably end up appearing in the production process. Currently the commonly used defect detection is manual detection, among these techniques are ultrasound testing, thermal detection, X-ray detection, digital holography, among others. The X-ray or technical radiography allows the analysis of all the internal components of the tire, such as the bead structure and the different layers of rubber and cords, whether metallic or textile. The task of detecting defects using X-ray images is done manually, which causes loss of time and costs for the company. Furthermore, it is a subjective, inefficient, time-consuming and even biased process as it requires a high level of concentration and focus. The objective of this work is the digitization of the conventional process of analysis of quality failures in metallic radial tires using algorithms developed with Artificial Intelligence resources, capable of identifying and classifying defects present in X-Ray images. This work presents a brief introduction about what the tire is, as well as the development of the proposed algorithm, using classic image segmentation techniques with a Computer Vision library and two different convolutional neural network structures. Through the comparison, it was verified that the algorithm based on U-Net obtained more relevant results, however, the algorithm based on Mask R-CNN was also promising and could be useful in new works, with a larger database and different settings parameters.

An algorithm for estimating the ultimate speed of vehicles on wet roads

Real-time estimation of a vehicle’s ultimate hydroplaning speed is crucial for ensuring its safety and stability, especially in rainy weather conditions. This paper proposes an algorithm for estimating the ultimate hydroplaning speed of vehicles on wet and slippery road surfaces based on finite element analysis of tire. Using the ABAQUS simulation software, a finite element model of a 205/55 R16 radial tire is established. Subsequently, a fluid-structure coupling model between the tire, water layer, and road surface is developed. The finite element method is employed to simulate and analyze the effects of tire inflation pressure, water layer thickness, vertical load, and tread wear on the vehicle’s ultimate hydroplaning speed. Simulation results indicate that an increase in tire inflation pressure and vertical load leads to an increase in the ultimate hydroplaning speed, while tread wear and an increase in water layer thickness result in a decrease. Finally, based on the simulation analysis data, a BP neural network-based estimation algorithm for the vehicle’s ultimate hydroplaning speed is proposed by combining the relationship between tire inflation pressure, tire vertical load, tread wear, water layer thickness, and ultimate hydroplaning speed. The results show that the estimated ultimate hydroplaning velocity profile has a high degree of overlap with the actual ultimate hydroplaning velocity profile, with a maximum error of no more than 5 km/h and an average percentage error of 2.31416%.

Performance Analysis of TBR Tire Curing Process

Numerical algorithms and computer programs have been developed to determine optimal cure steps in a tire curing process. A dynamic constrained optimization problem was formulated with the following ingredients: (1) an objective function that measures product quality in terms of final state of cure and temperature history at selected points in a tire; (2) constraints that consist of a process model and temperature limits imposed on cure media; (3) B-spine representation of a time-varying profile of cure media temperature. The optimization problem was solved using the complex algorithm along with a finite element model solver. Numerical simulations were carried out to demonstrate the procedure of determining optimal cure steps for a truck/bus radial tire. © 1999 John Wiley & Sons, Inc. J Apple Polymer Sic 74: 2063–2071, 1999.

Spike Device with Worm Gear Unit for Driving Wheels to Improve the Traction Performance of Compact Tractors on Grass Plots

In general, energy loss reduction via the interaction of tires with the ground improves tractor traction performance when a drawbar pull is generated. This paper is examines the driving wheels with steel spikes for a tractor equipped with modern radial tires. An improved design of the spike device that allows for the change between an active and inactive position of the spikes is presented. The traction performance of a compact articulated tractor with the spike device was tested on a grass plot with two soil moisture contents (SMC). The highest difference in the drawbar pull in the range from 14.2% to 40.5% and from 17.1% to 36.8% was reached by the spikes in the active position in comparison with the tires without spikes, which were at the slip range from 45% to 5% in the case of the low SMC when the test tractor was in the 3rd and 1st gear. The motion resistance difference between the spikes in the active position and the tires without spikes was 11.8% and 2.5% at the low and medium SMC, respectively. At the low and medium SMC, the highest tractive efficiency of 0.765 (0.721) and 0.757 (0.731) was reached by the spikes in the active position when the test tractor was in the 1st (3rd) gear in comparison with 0.736 (0.7) and 0.723 (0.708) in the case of the tires without spikes. The results indicated that the spike device allowed for the improvement of tractor tractive performance.

Numerical and experimental studies on the carcass characteristics of a radial tire

In this research, the carcass characteristics of a radial tire were analyzed by performing numerical simulations on ABAQUS software based on the single factor control variable method, and the feasibility of the proposed numerical model was verified by executing experiments on a tire uniformity testing machine. It was found that when the tire crossed the bump, the preload had positive effects on the internal energies and friction–dissipation fluctuation of the tire, but had little influence on its kinetic energy fluctuation. Tire speed was positively correlated with the fluctuation of kinetic energy, but negatively correlated with the friction–dissipation fluctuation of the tire. In addition, there was a slight correlation between the speed and the internal energy fluctuation of the tire. Moreover, the change in the tire pressure had little influence on the kinetic energy, internal energy, and friction dissipation of the tire.