Tire Temperature Research Articles

Analysis of Tire-Road Interaction: A Literature Review

This paper presents a comprehensive literature review of the most popular and recent work on passenger and truck tires. Previous papers discuss a huge amount of work on the modeling of passenger car tires using finite element analysis. In addition, recent works on tire–road interaction and the validation of tires using experimental measurements have been described. Moreover, the history of the tire-road contact algorithms is explained. In addition, friction modeling that is implemented in tire–road interaction applications are discussed. Also, a summary of current state-of-the-art research work definitions and requirements of the tread rubber compound are covered from previous studies using various literature reviews and hyper-viscoelastic material models that are implemented for the tread top and the tread base rubber compound. Furthermore, the effect of tire temperature from previous works is presented here. Finally, this literature review also highlights the shortcomings of recent research work and describes the areas lacking in the literature.

Analysis of effect on temperature field of tire curing process by initial temperatures and condensate discharging

To improve the heat transfer efficiency and temperature distribution uniformity of steam-heating vulcanization processes, a 3D simulation model was established by Solidworks and transient simulation studies were carried out by Fluent 2021 R1. The effects of four initial tire temperatures and five condensate discharging schemes on the heat transfer efficiency and temperature distribution uniformity were investigated. The study finds that: (1) At the end of the stage of filling the capsule with high-temperature and high-pressure steam, the temperature of the lower mold sidewall is 152.08 °C which is significantly higher than that of the lower mold bead with 128.03 °C, the lower mold shoulder with 115.00 °C, and the lower mold crown with 109.57 °C. (2) With the initial tire temperature increasing from 25 °C to 55 °C, the final temperatures at the lower mold crown and the upper mold sidewall are increased by 12.00 °C and 2.27 °C, respectively, indicating that the increase in the initial temperature helps to raise the temperature at difficult vulcanization locations of the tire. (3) It is recommended to carry out condensate discharging when the volume fraction of condensate at the lower mold sidewall is 0.2 %∼0.3 %, which improves the temperature uniformity in the steam-heating vulcanization process.

Monitoring overloaded trucks with infrared thermal imaging of tire sidewall

Overloaded trucks have long posed a threat to the road safety. To assess truck payload more effectively, this study focus on tire temperature data obtained through infrared thermal imaging. It is feasible to analyse the payload by monitoring one single representative tire. Tire sidewall surface is the best area for data extraction. Truck overload caused significant increase of gas temperature in tires, as well as external temperature. The internal temperature can be calculated with real gas equation of state. By studying the relationship between internal gas temperature of tire and payload, it is demonstrated that monitoring the temperature of tire sidewall surface is an innovative, remote, and real-time method to assess the payload situation of moving trucks.

Design and Implementation of Tire Pressure and Temperature Monitoring System for Hatchback and Multi-Purpose Vehicle Based on IoT

Tire Pressure Monitoring Systems (TPMS) have developed into an essential element in vehicles to improve safety and driving experience. In general, TPMS systems rely on special hardware to collect and transmit tire pressure data to the vehicle's on-board computer and this data can only be viewed by the driver and passengers in the vehicle. In this study, we developed a remote tire pressure and temperature monitoring system using IoT technology. The MQTT protocol facilitated communication between the cloud server and controller, while the system uses Docker container to simplify program integration. The results revealed the optimal standard deviation for tire pressure in hatchback vehicles to be 2.24, and for Multi-Purpose Vehicles (MPVs), it was 2.97. For tire temperature, the best standard deviation in hatchback vehicles was 1.93, compared to 1.05 in MPVs. This system effectively monitors tire pressure and temperature changes in real time, accessible remotely via smartphones and computers.

Thermoelectric energy extraction in motion scenarios: Self-powered temperature and pressure detector in an automobile tire

Worldwide, there's a push for carbon reduction through energy conservation. Yet, the potential of employing thermoelectric technology to recover waste heat from moving vehicles remains largely unexplored. This study employs precise simulations to analyze temperature distribution in car tires, unveiling possibilities for energy recovery. At 20 ℃ and 120 km/h, tire temperature peaks at 91.2 ℃ due to friction and rubber deformation. A micro thermoelectric generator (micro-TEG) on the wheel hub, serving as a heat sink, reveals a 3.9 ℃ effective temperature difference. A roadmap, considering factors like ambient temperature, speed, and TE leg size, guides exploration of micro-TEG's maximum power. This leads to a designed module with 8 micro-TEG units (weight: 5.3 g, area: 16 × 4 mm2, fill factor: 20 %, TE leg: 0.4 × 0.4 × 1.2 mm3) in series. Exposed to a 20 ℃ temperature difference, it shows open circuit voltage and maximum power of 1.47 V/1.41 V and 12.06 mW/11.58 mW in flat and curved states. Rigorous testing confirms stability. The 8.96 g module integrates with energy management and Bluetooth circuits. During simulated driving, mobile software records signals with over 94 % consistency. This advances dynamic waste heat recovery, enabling passive tire sensing and innovative links to the Internet of Things (IoT), contributing to field progress.

Characteristics and chemical treatment of carbon black from waste tires pyrolysis

The aim of this paper is to develop tires cracking carbon black with low ash content. The thermal decomposition characteristics of tires were investigated by thermogravimetric analysis, and the effects of pyrolysis variables on the yield, ash content and structure of pyrolytic carbon black were discussed by the laboratory tube furnace. Aiming at the phenomenon of high ash content in pyrolytic carbon black, the effect of acid and alkali solvent treatment on ash removal rate and the surface structural properties of carbon black were investigated. The experimental results show that the decomposition temperature of waste tire is between 300 °C and 500 °C, the yield of pyrolysis carbon black is 38%, and the ash content of carbon black is 19%, and the pyrolysis temperature has a significant effect on the surface impurity structure of carbon black. The carbon black was further treated with acid/alkali to optimize its surface properties, and the experimental results showed that acid treatment is more conducive to ash removal than alkali treatment. Under optimal conditions, when the concentration of HF solvent is 2 mol/L and the treatment time is 180 min, the ash content of carbon black can be reduced to 6.36%. At the same time, acid treatment also increases the microstructure of carbon black surface. The research in this paper provides basic data support for the research of carbon black preparation of waste tires.

A semi-physical thermodynamic transient rolling resistance model with nonlinear viscoelasticity

Rolling resistance dictates a large part of the energy consumption of trucks. Therefore, it is necessary to have a sound understanding of the parameters affecting rolling resistance. This article proposes a semi-physical thermodynamic tyre rolling resistance model, which captures the essential properties of rolling resistance, such as transient changes due to temperature effects and the strain-amplitude dependency of the viscous properties. In addition, the model includes cooling effects from the surroundings. Both tyre temperature and rolling resistance are obtained simultaneously in the simulation model for each time step. The nonlinear viscoelasticity in rubber is modelled using the Bergström–Boyce model, where the viscous creep function is scaled with temperature changes. The cooling of the tyre is considered with both convective and radiative cooling. Moreover, the article explains different material parameters and their physical meaning. Additionally, examples of how the model could be used in parameter studies are presented.

A Co-Simulation Platform with Tire and Brake Thermal Model for the Analysis and Reproduction of Blanking

In the world of motorsports engineering, improving brake performance is a crucial goal. One significant factor that affects this performance is the increase in brake disc temperature due to reduced cooling airflow, a phenomenon called “blanking”. This temperature increase also impacts the rim and the air inside the tire, causing changes in tire temperature and pressure, which affects the vehicle’s performance. Properly adjusting the brake blanking can be essential to keep the tire running at the right temperature, resulting in maximization of the performance on track. To address this complex problem, this study describes the problem of cooling brake discs, and this problem is then used as an opportunity to introduce a new variable in order to optimize the performance of the vehicle. By changing the thermal evolution of the brake disc, through the blanking, it can change a large percentage of heat that heats the tire. When combining an existing brake model in the literature with a tire thermal model in a co-platform simulation, it was seen that it is possible to work these two models together with the aim of being able to obtain the prediction of the optimal blanking value to be adopted before proceeding on track, thus saving time and costs.

Design and Implementation of Intelligent Tire Detection System Based on Esp8266 IoT Platform and Deep Learning Technology

<p>傳統上，市售的胎壓偵測系統(TPMS)僅能透過測量胎壓、胎溫來判斷輪胎狀態，無法即時檢測如：輪框變形、胎面異常剝離、輪胎附著異物、異常抖動及打滑等的輪胎異常狀況，若駕駛有所疏忽，將造成嚴重的危害。因此，我們研究設計一套智慧輪胎系統，透過量測輪胎運行間的慣性感測資訊，包含：三軸加速度、角速度、絕對方向，再結合 AI 演算法之辨識技術，動態檢測出輪胎異常狀況，並實作設計下述物聯網平台元件 : 1.安裝於輪框上之硬體裝置，可偵測輪胎行進間之異常數值，2.具即時監測與異常提醒、維修保養建議、車友討論平台等功能之手機應用程式，3.基於深度學習神經網路技術辨識各式輪胎異常狀況，4.建立跨平台智慧輪胎網頁介面供職業車隊管理停車場。經實驗測試結果，本系統的 AI 判讀準確率高達 99.17%。</p> <p> </p><p>The tire pressure monitoring system (TPMS) sold on the market can only judge the tire status by measuring the tire pressure and tire temperature, and cannot detect such things as: wheel frame deformation, abnormal tread peeling, foreign objects attached to the tire, abnormal vibration and skidding, etc. If the tire is abnormal, if the driver is negligent, it will cause serious harm. Therefore, we design a set of smart tire system, through the measurement of inertial sensing information during tire operation, including: three-axis acceleration, angular velocity, absolute direction, combined with the identification technology of AI algorithm, dynamically detect abnormal tire conditions, and Realize the design of the following IoT platform components: 1. The hardware device installed on the wheel frame can detect abnormal values during tire travel. 2. It has real-time monitoring and abnormal reminders, maintenance suggestions, and a discussion platform for riders, etc. Functional mobile phone application, 3. Based on deep learning neural network technology to identify various tire abnormalities, 4. Establish a cross-platform smart tire web interface for professional fleets to manage parking lots. According to the experimental test results, the AI interpretation accuracy rate of this system is as high as 99.17%.</p> <p> </p>

A data-driven framework for forecasting transient vehicle thermal performances

Transient vehicle dynamics are deeply affected by the spatial distribution of tire temperature, heat generation, and heat dissipation capacity. However, the tire testing process involves numerous parameters, adding the complexity to monitoring the tire’s thermal properties variation. To address this issue, this paper proposes a data-driven framework that combines the well-known Magic Formula with scaling factors and a long- and short-term memory (LSTM) neural network. The framework forecasts tire thermal properties and functionality under given conditions by learning from time-series data on tire operating conditions and mechanical characteristics. It predicts future spatially varying thermal properties of the tire, including temperatures, heat generation, and heat dissipation. This is achieved with a high degree of forecasting ability quantified by train size/test size ratios equaling 22 and 38% with an impressive Relative Root Mean Square Error (RRMSE) around 1−2%. Here, this framework is applied to quantify the impacts of various operating conditions, including vertical load, slip angle, and vehicle speed, on heat transfer for three crucial radial positions on the tire. Our results show that the vertical load is the primary influencing parameter among all operating conditions. The knowledge about transient tire dynamics will be advantageous to their performance optimization.

Temperature monitoring of vehicle brake drum based on dual light fusion and deep learning

The braking system of a vehicle is the most crucial component for ensuring the safety on the road. Moreover, the extraction of temperature field data from a vehicle's tires plays a crucial role in vehicle condition monitoring. Nevertheless, the conventional infrared thermal imaging detection method necessitates manual recognition of the tire components and marking of each temperature point one by one in the infrared image. To address this issue, a method combination with dual-light fusion and deep learning is proposed to implement automatic monitoring for vehicle brake drum temperature. Firstly, we propose a late-end multimodal fusion algorithm based on the YOLOv5 network to integrate visible light and infrared thermal imaging This algorithm allows for feature extraction from both modalities and performing decision-level image fusion, thereby improving the robustness of automatic vehicle and tire detection. Additionally, we employ a semantic segmentation network to accurately segment the tires, extract the relevant visible pixel information, and obtain the temperature field matrix from the infrared images while eliminating extraneous background details. Subsequently, a three-dimensional model of tire’s temperature field is constructed obtaining the dynamics of tire temperature during the vehicle operation. Through experimentation, we demonstrate the efficacy of our proposed method in achieving all-weather roadside vehicle classification and tire temperature monitoring, which provides technical and theoretical support for the active risk prevention and control in road transportation.

Rubber Comprehensive Constitutive Equation and the Prediction of Tire Temperature and Rolling Resistance

ABSTRACT Cooler running tires with a reduced rolling resistance is a consideration for both tire makers and automotive original equipment manufacturers. To investigate the mechanics of energy loss and temperature rise, a nonlinear viscoelastic model suitable for numerical analysis of rolling tires is developed and demonstrated. The rubber compounds are represented as nonlinear viscoelastic materials with temperature and frequency, strain, and strain history–dependent response. Several applications to different tire designs are provided to demonstrate the impact of this new material constitutive law in improving the quality of the numerical predictions over other methods. One application is a rolling tire model that was used to delineate the tire temperature distribution and the resultant rolling resistance for different three-dimensional tread patterns.

Influence of Pressure on Tire Wear of Mining Dump Truck

The article shows the dependence of ground pressure on the number of wheels and tire inflation pressure for dump trucks, the dependence of tire pressure, tire deformation and contact patch length on tire inflation pressure and tire temperature. Currently, some of the dump trucks in Russian quarries are operated in off-road conditions on soils with low bearing capacity. Work on weak soils requires the use of vehicles with high crosscountry ability and low specific pressure on the ground. One way to improve off-road mobility is to use articulated dump trucks.

Thermomechanical Modeling of Aircraft Tire–Runway Contact for Transient Maneuvers

ABSTRACT The aircraft tire is the link between the aircraft and the runway and transmits forces and moments within the contact area. During ground maneuvers, the tire is exposed to a wide range of operating conditions. The tires support the weight of the aircraft, they ensure safe rolling during taxiing, and they transfer the required forces to the runway during takeoff and landing. Temperature development during these maneuvers is of great importance because temperature can affect both material stiffness and friction behavior as well as wear characteristics. Heat is generated inside the tire due to energy dissipation caused by the cyclic loading of the tire during rolling. In addition, heat is generated due to friction in the tire–runway contact. Experimental measurements of the temperature distribution in the entire tire are not yet possible. The tire temperatures can only be determined at selected critical spots. Simulation models can help to obtain a better understanding of the overall tire temperature distribution during transient maneuvers. In this work, the transient thermomechanical processes of a rolling aircraft tire, e.g., directly following the touchdown process or during taxiing, are modeled based on a simple physical tire model. An extended brush model is used to simulate the contact forces. The tire temperature is determined via the transient heat conduction equation in radial and circumferential directions. The mechanical and thermal models are coupled via the coefficient of friction and the sliding velocities in contact. The free model parameters are parameterized using experimental data, and the overall model is validated by measurements on the whole tire. The validated thermomechanical tire model is used for simulations or the analysis of different driving maneuvers to get a better understanding of the temperature development in the aircraft tire.

Emission Characteristics of Tyre Wear Particles from Light-Duty Vehicles

Tyre wear particle emissions have gained significant attention due to their harmful effects on the environment and human health. However, studies on tyre wear particles generated under chassis dynamometer conditions are still scarce. This study measures the instantaneous number concentrations and elemental species of tyre wear particles in different light-duty vehicle test cycles. The results show that the particle number (PN) concentrations of the US06 test cycle are much higher than those of the WLTC test cycle due to the larger and more frequent accelerations and decelerations in the former. High PN concentrations are observed during high driving speeds with rapid accelerations, while PN concentrations are much lower during low driving speed with rapid acceleration. Furthermore, tyre tread temperature is found to be related to the formation of tyre wear particles. The PN concentration in the second and third US06 test cycles are similar, indicating that once the tyre temperature exceeds the critical value, the tyres become heated to a steady state, and the PN concentrations will not be affected by the average temperature of the tyre. A low initial tyre temperature can produce high PN concentrations during the cold start phase of test cycles and prolong the time required for tyres to warm up. In addition, the particles contained a high mass fraction of Zn, which can serve as a tracer of tyre wear particles in non-exhaust particle tests of vehicles.

Rolling Tires on the Flat Road: Thermo-Investigation with Changing Conditions through Numerical Simulation

A crucial material comprising a pneumatic tire is rubber. In general, the tire, or more specifically, the hysteresis effects brought on by the deformation of the part made of rubber during the procedure, heat up the part. In addition, the tire temperature depends on several factors, including the inflation pressure, automobile loading, car speed, road tire, the environmental conditions, and the tire geometry. This work focuses on using simulations to calculate the temperature and generated heat flow distributions of a rolling tire with constant velocity using the finite element method. For the sake of simplicity, it is assumed that the only components of the tire are rubber, body-ply, bead wire, and the rim. While the other components are believed to be made of a linear elastic material, the nonlinear mechanical behavior of the rubber is characterized by a Mooney–Rivlin model. Investigations are conducted into the combined effects of vehicle loads and inflation pressure. Hysteresis energy loss is used as a bridge to link the strain energy density to the heat source in rolling tires, and their temperature and heat flow distributions may be determined by steady-state thermal analysis. Thanks to the state-of-the-art computing method, the time required for connected 3D dynamic rolling tire simulations is reduced. The simulation outcomes demonstrate that the maximum temperature in this paper is attained with high weights, high velocities, and low inner inflated pressures. Overall, the maximum temperature is increased with the rise of all three variables. Moreover, the rise of the friction coefficient between the tread and road surface moves the high-temperature area towards the tread/sidewall connection area.

Truck tyre transient rolling resistance and temperature at varying vehicle velocities - Measurements and simulations

Rolling resistance is causing a significant part of the energy consumption in truck applications, especially at low-speed levels. To be able to better estimate the energy consumption or remaining driving range, the truck tyre rolling resistance must be understood well. Temperature is a vital parameter for rolling resistance estimations. This article shows truck tyre rolling resistance and temperature measurements in a climate wind tunnel and simulations of tyre temperature and rolling resistance. During the climate wind tunnel tests, tyre temperature at the shoulder and tread was measured. In addition, on-road driving was conducted with inner-liner infrared temperature measurements. Tyre temperature simulations were conducted using a thermal tyre model with speed-variable thermal inertia. The comparison of tyre temperature simulations with measured inner-liner and shoulder temperatures showed good agreement with the test data. The rolling resistance was simulated using the principle of time-temperature superposition, and a master curve for rolling resistance and a curve for tyre temperature shift were constructed. These curves were used to simulate rolling resistance at a wide range of speed levels with good agreement to the experimental results. The investigation showed that the tyre shoulder temperature is a better indicator of rolling resistance than infrared measurements from the tyre tread.

Temperature elevation of aircraft tyre surface at touchdown with pre-rotations

The runway and landing gear speed difference causes non-negligible friction at touchdown, generating vital heat to raise the tyre tread temperature. The resulting material decomposition reduces tread thickness and significantly impacts flight safety and the environment. Airline operators also need to pay the cost of frequent tyre replacement. The pre-rotation strategy has been proposed to prevent high-speed friction at touchdown. Therefore, a mathematical algorithm is established on MATLAB to simulate the tyre friction and heat generation with various pre-rotation levels. The algorithm is validated by experiments, and a transient thermos-mechanical analysis on ANSYS is used as a reference. The presenting work is one of the few that uses theoretical modelling to simulate tyre heat generation. The formulas presented therein, including Laplace's equation, make the results reliable and traceable. It can be seen that the developed algorithm is capable of calculating the tyre temperature. The pre-rotation can efficiently reduce the friction strength at touchdown. However, when the pre-rotation speed is relatively low, a slight increase in maximum tyre temperature may occur, and the specific reasons for this will be in the discussion.

기계학습을 이용한 지능형 타이어의 마모도 추정

Tire-related crashes account for a large proportion of all types of car accidents. The causes of tire-related accidents are inappropriate tire temperature, pressure, and wear. Although temperature and pressure can be monitored easily with TPMS, there exists no system to monitor tire wear regularly. This paper proposes a system that can estimate tire wear using a 3-axis accelerometer attached to the tread inside the tire. This system utilizes axial acceleration, extracts feature from data acquired with the accelerometer and estimates tire wear by feature classification using machine learning. In particular, the proposed tire wear estimation method is designed to estimate tread depth in four types (7, 5.6, 4.2, and 1.4 mm) at speeds of 40, 50, and 60 kmph. Based on the data obtained during several runs on a test track, it has been found that this system can estimate the tread depth with reasonable accuracy.

Structural and thermal investigations of rolling tires in a flat road

Rubber is an essential component of a pneumatic tire. In general, the tire, or the rubber part, is heated by the hysteresis effects caused by the deformation of the rubber part during the operation. Besides, the tire temperature depends on many factors, such as inflation pressure, vehicle loading, car speed, road tire, environment condition, and tire geometry, etc. This study focuses on the finite element approach to compute by simulating the temperature distributions of a steady-state rolling tire. For simplicity, the tire is assumed to be composed of rubber, body-ply, wire, and rim only. The nonlinear mechanical behavior of the rubber is characterized by a Mooney–Rivlin model, while the other parts are assumed to be a linear elastic material. The coupled effects of the inflation pressure and vehicle loading are investigated. Hysteresis energy loss is used as a bridge to link the strain energy density to the heat source in rolling tires. The steady-state thermal analysis may obtain the temperature distribution of rolling tires. On the other hand, an efficient computational process is being introduced to decrease the time for coupled 3D dynamic rolling simulation of the tire. The simulation results show that loading is the main factor in determining the temperature field