Vehicle Tire Research Articles

Magnetic properties of tire cord as a diagnostic parameter of car tires condition

This article presents the possibility of using the magnetic measurement method, which is an alternative method to shearography as a method of testing the condition of the cord of all-steel tires in order to determine the possibility of using the casing for the retreading process. It is an extension of the design and research work aimed at creating a prototype of a diagnostic device. As part of the activities, a prototype of the device and a version of the measuring head were developed, but a prototype of the algorithm of the measurement program was also created, which uses the physical foundations of non-destructive measurements of motor vehicle tires developed within the project. This study is related to the increasingly strict regulations and the intentions of the European Commission regarding the use of vehicles, which require an increase in the share of recycled materials, including tires. Therefore, there is a need to develop measurement methods that allow for the assessment of the quality of the casing while the used tires are still stored. This work presents the results of theoretical analyses of the possibility of using the magnetic field as a diagnostic parameter of the condition of tires

Advanced self-sensing road stud: Integrating deep learning-based speed detection and energy harvesting

Abstract This study introduces a self-powered and self-sensing vehicle speed detection sensor, representing a significant advancement in transportation. The system employs mechanical components like a slider crank, bevel gears, and one-way bearings for unidirectional rotation, converting translational motion into electrical energy upon the impact of vehicle tyres on road studs. The electrical power generation module, including a DC generator, rectifier, and battery circuit, captures and stores this energy. In addition to energy harvesting, the system integrates a deep learning model using Long Short-Term Memory (LSTM) networks to precisely calculate vehicle speed from the displacement signals of the road studs. Displacement data from an SR-04 sensor is processed and fed into the LSTM network, achieving a classification accuracy of 99.45% for vehicle speeds of 5, 10, 15, and 20 km/h. A mathematical model and MATLAB Simscape simulations were developed, followed by experimental validation using a Mechanical Testing and Sensing System (MTS) under laboratory conditions. Lab-scale testing, a maximum output power of 3.72W and an efficiency of 62.7% were recorded at 8 Hz. Field tests were performed at various vehicle speeds. A peak voltage output of 10V was recorded for a single phase of a three-phase DC generator at 15 km/h. The displacement sensor beneath the road stud was used to record the relative time signal between adjacent peaks to calculate vehicle speed. The sensor is sustainable in energy and easily installable without infrastructure changes, enhances transportation efficiency, and is useful for traffic management, road safety, and smart transportation networks.

Robust joint estimation of sideslip angle and tire lateral force for distributed drive electric vehicle

Accurate estimation of vehicle sideslip angle (SA) and tire lateral force (TLF) is essential for the effective functioning of vehicle active safety control systems. However, effective estimation of SA and TLF using low-cost on-board sensors is a major challenge. In this paper, a robust joint estimation method of SA and TLF for distributed drive electric vehicle (DDEV) is proposed. Adaptive sliding-mode observer (ASMO) is used to estimate the TLF and is used as the input to the subsequent filter. Maximum correntropy criterion (MCC) is introduced to improve the robustness of the unscented Kalman filter (UKF) under mixed Gaussian noise, and the maximum correntropy unscented Kalman filter (MCUKF) algorithm is composed to estimate SA. The effectiveness of the proposed ASMO and MCUKF joint estimation method is verified by Simulink/Carsim joint simulation experiments. The experimental results show that compared with the existing methods, the estimation method proposed in this paper effectively improves the estimation accuracy and robustness of SA and TLF under the mixed Gaussian environment, which is of great significance for the improvement of vehicle active safety.

MOSQUITO SPECIES DISTRIBUTION IN TIRES IN RURAL AND URBAN LANDSCAPES ACROSS NORTHERN KENTUCKY.

Discarded vehicle tires can be found in habitats spanning a human land-use gradient from rural to urban and create an ideal artificial container habitat for mosquito larval development. The purpose of this study was to examine mosquito species composition in discarded vehicle tires in rural and urban habitats. Discarded tires were placed at 6 rural and 6 urban forested sites and sampled weekly for juvenile mosquitoes. Adult traps were also placed at these sites and were sampled weekly. There was no significant difference between the total number of juvenile mosquitoes collected from tires in urban sites compared to rural sites, but significantly more Aedes triseriatus and Ae. albopictus juveniles were found in urban sites compared to rural sites. This study also found that significantly more adult mosquitoes were collected in urban sites compared to rural, but there were no significant differences found between sites when comparing individual species. The results of this study suggest discarded vehicle tires are important mosquito larval habitats across human-land-use gradients and that Ae. triseriatus may be more common in urban areas than previously thought.

Research on intelligent optimal allocation control strategy for stability and braking of heavy tyre blowout vehicle

The traditional control strategy mainly compensates and corrects the driving state of heavy vehicles with a tyre blowout, and rarely considers the need for emergency braking. It is also difficult to effectively coordinate the problems of lateral yaw, slip and tailspin, and longitudinal braking performance degradation. For this, an intelligent optimization allocation control strategy combining stability control and braking control is innovatively designed in this article. The joint simulation model for heavy tyre blowout vehicles is built based on the Dugoff tyre blowout model and the TruckSim vehicle model. A linear quadratic form regulator stable control based on the particle swarm optimization algorithm optimization is used to dynamic equilibrium of the additional yaw moment generated by the vehicle tyre blowout. A logic threshold braking control based on adaptive adjustment is adopted to achieve an ideal braking effect for the vehicle. In order to simultaneously consider the stability and braking performance of vehicles with blowout tyre, a braking force distribution strategy and a fuzzy optimization allocation algorithm are proposed to achieve coordination of lateral and longitudinal control strategies. The results indicate that intelligent optimized allocation control can effectively correct the deviation trajectory of a heavy tyre blowout vehicle, enabling it to achieve rapid braking while maintaining stability.

Recycled Carbon Black/High-Density Polyethylene Composite from Waste Tires: Manufacturing, Testing, and Aging Characterization

This study addresses the global issue of recycling used vehicle tires, typically burned out or trimmed to be reused in playground floors or road banks. In this study, we explore a novel environmentally responsive approach to decomposing and recovering the carbon black particles contained in tires (25–30 wt.%) by vacuum pyrolysis. Given that carbon black is well known for its UV protection in plastics, the objective of this research is to provide an ecological alternative to commercial carbon black of fossil origin by recycling the carbon black (rCB) from used tires. In our research, we create a composite material using rCB and high-density polyethylene (HDPE). In this article, we present the environmental aging studies carried out on this composite material. The topographic evolution of the samples with aging and the oxidation kinetics of the surface and through the thickness were studied. The Beer–Lambert law is used to relate the oxidative index to the characteristic depth of the samples. The UV photons are observed to penetrate up to 54% less with the addition of 6 wt.% of rCB compared to virgin HDPE. In this work, the addition of rCB as filler for HDPE used for outdoor applications has demonstrated to be an antioxidant for UV protection and a good substitute for commercial carbon black for industrial goods.

A Study on the Mid-frequency Tire-Sourced Cabin Noise in Electric Vehicles

ABSTRACT This study investigates and provides a framework for addressing a reported tire- sourced cabin noise in the mid-frequency range of 300–500 Hz for an electric vehicle (EV). Noise, vibration, and harshness (NVH) of EVs present new challenges compared with internal combustion engine vehicles because of significant design changes between the two vehicle types. In turn, the tire–road interaction noise becomes a more significant source of cabin noise in EVs. In this regard, some prominent EV manufacturers recently reported relatively high measured cabin noise, particularly in the mid-frequency range of 300–500 Hz. Identifying the root cause(s) of noise in that range is a challenging task, as both tire structure–borne and airborne sources are contributors in that frequency range of elevated noise. The current work presents the results of an experimental modal analysis to provide insight into some potential sources of the reported noise for an all-season tire/wheel assembly designed for an EV. The subsequent parametric simulations, conducted via the tire–vehicle finite element model, evaluate some of the mitigation solutions for the reported noise.

Development of a Matrix for Seismic Isolators Using Recycled Rubber from Vehicle Tires.

Over recent decades, numerous strong earthquakes have caused widespread devastation, including citywide destruction, significant loss of life, and severe structural damage. Seismic base isolation is a well-established method for mitigating earthquake-induced risks in buildings; however, its high cost often limits its implementation in developing countries. Simultaneously, the global rise in vehicle numbers has led to the accumulation of discarded tires, intensifying environmental challenges. In response to these issues, this study investigates the development of a seismic isolator matrix using recycled rubber from vehicle tires, proposed as a sustainable and cost-effective alternative. Ten recycled rubber matrices were experimentally evaluated for their physical and mechanical properties. The matrix with optimal granulometry and binder content, demonstrating superior performance, was identified. This optimized matrix underwent further validation through compression and cyclic shear tests on reduced-scale prototypes of fiber-reinforced isolators, which included five prototype designs, two of which featured flexible reinforcement. The best-performing prototype comprised a recycled rubber matrix with 15% binder and glass fiber, exhibiting vertical stiffness and damping characteristics superior to those of natural rubber. Specifically, this prototype achieved a damping ratio of up to 22%, surpassing the 10% minimum required for seismic isolation, along with a vertical stiffness of 45 kN/mm, critical for withstanding the vertical loads transferred by buildings. These findings suggest that the recycled tire rubber matrix, when combined with glass fiber, is a viable material for the production of seismic isolators. This combination utilizes discarded materials, contributing to environmental sustainability.

Open-structured silica network based on silane-terminated telechelic polybutadiene for electric vehicle tires

The shift towards electric vehicles (EVs) is essential for a sustainable future. Tire manufacturers face challenges including accommodating extra weight, managing instant torque, reducing noise, and improving driving range. Meeting these demands involves substantially reducing the rolling resistance of tire tread composites while simultaneously enhancing their mechanical stiffness and wear resistance. To overcome these issues, an open-structured silica network based on silane-terminated liquid-like telechelic polybutadienes was introduced into rubber composites. This unique network consists of silica aggregates that are chemically bound together, but exhibit physical separation, enabling rubber chains to permeate. The infiltrated polymer chains were tightly constrained by the network, resulting in a notable increase in the crosslink density and mechanical strength of the composite. Furthermore, the tan δ values at 60 °C showed a notable decrease as a result of diminished interparticle friction caused by isolated silica structures and reduced mobility of polymer chains within the network. These findings provide the tire industry with crucial insights for the development of energy-efficient and durable tires for EVs. By addressing these specific requirements of EVs, our study paves the way for more sustainable tires and contributes to the broader adoption of EVs in a sustainable future.

New Energy Vehicle Tire Defect Detection Algorithm Based on Improved YOLOv8

Aiming at the traditional tire defect detection is difficult to meet the practical application requirements, a defect detection algorithm based on YOLOv8 is constructed. Firstly, the GAM attention mechanism is added to the backbone to improve the feature expression of tire defects and improve the detection efficiency. Secondly, the SPPF is replaced by SimSPPF to effectively capture multi-scale features. Finally, the CIoU loss function is replaced by Wise-IoU to improve the convergence ability of the model. The experimental results show that the constructed improved models P, mAP0.5 and mAP0.5:0.95 reach 86.4%, 88.2% and 46.9%, respectively, which are improved by 2.7%, 2.3% and 0.9% compared with the original YOLOv8n model. The algorithm can better improve the problems faced by traditional new energy vehicle tire defect detection.

Study on vehicle state and tire–road friction coefficient estimation based on maximum correntropy generalized high-degree cubature Kalman filter

To cope with the challenges of inadequate precision and weak robustness of tire–road friction coefficient (TRFC) and vehicle state estimation under mixed Gaussian noise circumstances, this research puts forward a method combining maximum correntropy criterion (MCC) and generalized high-degree cubature Kalman filter (GHCKF). A coupled lateral and longitudinal vehicle model and the Dugoff tire model are established. The vehicle mass is estimated using the recursive least squares approach based on a forgetting factor (FFRLS). Low-cost onboard sensors are utilized to design observers for vehicle state and TRFC. The observers’ effectiveness is tested by Carsim/Simulink co-simulation tests under the conditions of sine steering input and steering wheel angle step input. The research results indicate that in handling mixed Gaussian noise environments, maximum correntropy generalized high-degree cubature Kalman filter (MCGHCKF) method outperforms maximum correntropy cubature Kalman filter (MCCKF), GHCKF, and cubature Kalman filter (CKF) methods concerning robustness and estimation accuracy, providing stable and reliable support for systems of vehicle active safety control.

Sound Source Localization at the Rolling Tire

A vehicle's tire rolling on pavement causes complex noise generating mechanisms which are a dominant sub-source of vehicle traffic noise. For the quantification of noise levels due to these tire-pavement interactions, standardized acoustic measurement methods exist, such as the Close-Proximity (CPX) method. These methods require microphones mounted near a rolling tire. However, they do not provide insight in the distribution and amplitudes of present sound sources. In this contribution, we aim at identifying the dominant sound sources of the rolling tire at discrete frequencies. This is accomplished by an inverse method combining microphone array measurements and Finite Element (FE) simulations. The microphone measurements were recorded on Austrian highways with a large measurement trailer built for research purposes. With the considered inverse method, not only the amplitudes of the dominant sound sources but also their phases can be identified. With these identified sources and a validated FE model of the measurement trailer, the sound pressure field within the trailer may be computed. The thereby calculated sound pressure is compared to measurements at the CPX microphone positions and other locations within the trailer.

Optimized road noise asphalt pavements - The types of noise-reducing road surfaces

The noise has long been recognized as a stress factor for humans. A high level of noise has many negative influences on health such as: difficulty to concentrate, stress, health issues for the ears, and also has a damaging effect on the cardiovascular and endocrine systems. Road traffic is main source of total noise, especially in conurbations. In order to effectively reduce noise emissions, surface courses can be installed as road surfaces that generate particularly little noise in interaction with the vehicle tire. This paper delas with different types of noise-reducing road surfaces.

A customised ConvNeXt-SCC network: integrating improved principal component analysis with ConvNeXt to enhance tire crown defect detection

ABSTRACT Defects such as bubbles and rubber shortages occasionally occur during vehicle tire production. Tiny defects in the crown gradually expand under load, ultimately causing tire failure. However, machine-vision-based crown defect detection faces challenges like limited datasets, varying groove patterns, low colour contrast, and small defect sizes. Therefore, this article integrates principal component analysis (PCA) and deep learning techniques for the visual detection of tire crown defects. A dataset of tire crown defects suitable for deep learning was constructed using an improved-PCA method and composite sampling. We propose the ConvNeXt-Shallow Conv CBAM (ConvNeXt-SCC) model, which includes an improved convolutional block attention module (CBAM) in a shallow stacked structure. And we propose an efficient and accurate method called Improved Selective Search (ISS) to detect and locate tire crown defective regions. The ISS pre-selected box generation method, enhanced with a priori knowledge filtering module, was used alongside a classification model to achieve online inference detection of large-size tire crown images. The experimental results show that the performance indices of the proposed ConvNeXt-Shallow Conv CBAM (ConvNeXt-SCC) model significantly improve compared to the original ConvNeXt-T. The defect detection and localisation method based on ISS meets the online inspection requirements of tire production.

Pressure Based Power Generation System

The growing global population and technological advancements are leading to a sharp increase in energy demand. Simultaneously, energy is being wasted across various domains, particularly in transportation. Harnessing this lost energy and converting it into usable forms is critical for sustainability. This paper presents a novel system for generating power using the pressure exerted by tires of electric vehicles (EVs) via piezoelectric transducers. The generated energy is then wirelessly transmitted to charge EVs, utilizing resonant inductive coupling. This system not only helps recover energy from everyday driving but also offers a potential solution to energy wastage. Experiments demonstrate the feasibility of this approach, with power transmission efficiencies exceeding 90% at moderate distances. Key Words: pressure-based power generation, piezoelectric transducers, wireless power transfer, electric vehicles, resonant inductive coupling, energy harvesting.

Vehicle Stability Control Based on Vehicle Motion State and Tire Force Estimation

The direct yaw moment control system is able to greatly enhance the vehicle stability when driving on challenging road surfaces. This paper introduces a direct control approach for managing the vehicle yaw moment, utilizing terminal sliding mode control and a Square Root Cubature Kalman Filter (SRCKF). Initially, the longitudinal and lateral forces acting on the vehicle's tires are estimated through a sliding mode observer. Subsequently, the SRCKF algorithm and the four-wheel tire force are employed to accurately estimate the yaw rate and sideslip angle. Based on these estimations, additional yaw moments are determined using the terminal sliding mode control algorithm, and a combined control of yaw rate and sideslip angle is achieved through a threshold method. A rule-based braking force distribution strategy is then implemented to ensure vehicle stability control. Simulation results demonstrate that the tire force estimations from the sliding mode observer and the vehicle yaw rate and sideslip angle estimations from the SRCKF algorithm closely align with the output results from Carsim, with an error margin of less than 15%. The braking force distribution strategy, based on the direct yaw moment control using the terminal sliding mode algorithm, effectively tracks the desired yaw rate and sideslip angle.

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.

AI-Assisted Self-Powered Vehicle-Road Integrated Electronics for Intelligent Transportation Collaborative Perception.

Collaborative perception between a vehicle and the road has the potential to enhance the limited perception capability of autonomous driving technologies. With this background, self-powered vehicle-road integrated electronics (SVRIE) with a multilevel fractal structure is designed to play a dual role, including a SVRIE device integrated into vehicle tires and a SVRIE array embedded into a road surface. The pressure sensing capability and anti-crosstalk performance of the SVRIE array are characterized separately to validate the feasibility of applying the SVRIE in a cooperative vehicle-infrastructure system. It is demonstrated that the SVRIE based on the multi-layered fractal structure exhibits maximum performance in collaborative sensing and interaction between vehicles and road information, such as vehicle motion, road surface condition, and tire life cycle health monitoring. Traditional data analysis methods are often of questionable accuracy. Therefore, a convolutional neural network is used to classify the vehicle and road conditions with accuracy of at least 88.3%. The transfer learning model is constructed to enhance the road surface identification capabilities with 100% accuracy. The accuracies of the vehicle tire motion recognition and tire health monitoring are 97% and 99%, respectively. This work provides new ideas for collaborative perception between vehicles and roadsides.

Temperature Rise of Vehicle Tire at Braking

Temperature Rise of Vehicle Tire at Braking

Koordinasi Dinas Perhubungan dan Kepolisian dalam Meningkatkan Ketertiban Berlalu Lintas di Kabupaten Malang

Indonesia is a country with a large number of land transportation users and it is necessary to organize strategies so that it runs well in order to maintain safe and secure traffic. It is hoped that the coordination carried out by the transportation service and the police will have a big impact on traffic order in Malang Regency. The aim of this research is to find out how traffic order is coordinated in Malang Regency, the method used is a case study based on interviews. The results of this research show that the communication process is direct when transportation service officers are in the field, the communication process uses Handy talkie technology, communication from this tool for one direction and one purpose. The competency of participants from the transportation service is more technical, such as checking the condition of vehicle tires, lights and wheel position, understanding vehicle routes in the district, while from the police, it is understanding legal regulations and procedures for implementing enforcement. According to the agreement and commitment, the Transportation Service has limited authority and can only carry out technical matters regarding the condition of vehicles, while the authority of the Police is to take action, therefore there is a need for coordination between the two. Determination of an agreement regarding coordination when there is an activity that requires a number of parties, a formal letter will be written based on the applicable regulations. Coordination incentives show that the implementation of tasks has been coordinated. If a violation occurs, there will be no sanctions but what has been agreed is that responsibility will return to the respective agencies. Due to feedback, the communication process is sometimes long, so the time needed to carry out traffic operations also increases.