Chen Liang

Transient dynamics of non-pneumatic tires are particularly critical for evaluating their performance in medium-speed vehicles. To study transient dynamic characteristics of the non-pneumatic tire with honeycomb spokes, a finite element (FE) model was initially established using the ABAQUS software. The validity of the FE model was demonstrated through comparing predicted and measured results. Transient simulations were subsequently performed to investigate the effects of obstacle size, rolling speed, and normal load on longitudinal and vertical dynamic responses of the tire in both time and frequency domains, apart from its local deformation characteristics. The results showed significant growth in peak longitudinal and vertical forces with an increase in obstacle radius and normal load. The resonance frequencies in axle forces, however, were slightly affected by these parameters. Besides, the speed revealed notable effects on both time and frequency domain response characteristics, particularly the variation in resonance frequencies of the longitudinal forces when the velocity was increased from 20 to 50 km/h. In addition, the honeycomb tire exhibited qualitatively inferior enveloping performance than its pneumatic counterpart. These results could help deepen the understanding of the transient dynamic behavior of honeycomb tires under real-world driving conditions and offer essential guidance for optimizing tire designs for practical applications.

Inappropriate manual braking maneuvers can cause severe pitch motion of the vehicle, leading to significant ride discomfort during the terminal braking stage. To address this gap in existing braking control research, this study proposes a novel intelligent braking controller that integrates braking comfort and safety objectives within a model predictive control (MPC) framework. The novelty of the controller lies in its ability to automatically regulate braking torque in the low-speed phase to suppress pitch-induced oscillations while ensuring safety, and in its ease of integration into brake-by-wire systems without requiring additional hardware. Performance measures for braking comfort and safety were determined from field tests using both “comfortable” and “uncomfortable” braking strategies. The controller, consisting of a predictive model, rolling optimization, and feedback correction, was evaluated through numerical simulations. Results showed up to 75% reduction in peak oscillation amplitude and 91.6% reduction in jerk, while keeping the increase in stopping distance below 0.15 m, across varying vehicle masses and road slopes. These findings demonstrate the practical significance of the proposed controller as a cost-effective and easily deployable solution for improving braking comfort in modern intelligent vehicles.

Tire durability has been an essential part of passenger and vehicle safety, which usually requires years of road services to test relevant performance. The tire oven aging test has been widely accepted as an accelerated laboratory test to induce large thermal oxidation of rubber compounds with mechanical degradations under high temperatures. Then, the oven-aged tires are tested on rolling drums to compare the durability hours and failure locations. As an assembly of various components with different structures and formulations, tire aging and durability tests are complicated issues incorporating oxygen permeation, consumption, and mechanical degradation. Therefore, it calls for a predictive workflow and model to evaluate the oven aging extent and corresponding durability performance. Based on the computed local oxygen consumption of tires, this article assigns the aged property to each element in a tire FEA (Finite Element Analysis) model by building the quantitative correlations between compound oxygen consumption and degraded mechanical properties. Subsequently, tire mechanics simulations are conducted with SEDG (Strain Energy Density Gradient) to evaluate and compare the endurance of oven-aged tires with different inner liner structures and formulations.

Vehicle traffic noise has become an important factor in urban noise pollution. With the increase in the number of new-energy vehicles, the current situation of tire/road noise as one of the main noise sources of automobiles is becoming increasingly prominent. Tire noise prediction is the basis for optimizing the design of low-noise tires, providing a reference basis for tire design with low-noise performance. This paper used deep learning methods to predict the noise performance of TBR radial tires. We obtained descriptive statistical features of tire structure and tread pattern images as input to the model, and used measured tire/road noise as output, then we constructed a multi-modal tire noise dataset. Comparing the prediction performance of three pre-trained transfer models such as Resnet18, VGG16, and Inception V3 on the tire pattern images, the Resnet18 had the best prediction effect. Resnet18 was selected as a feature extractor to extract image features, which fuse with the tire structural features at the feature level. The experiment constructed the TLMF-TRNP model to predict tire noise. The experimental results of the TLMF-TRNP model indicated that RMSE, MAE, and R ² were 0.1337, 0.0948, and 0.9864 respectively, achieving ideal prediction accuracy on a small-scale tire noise dataset and controlling the absolute error of the test tires within ±0.4 dB effectively. An accurate tire noise prediction model will provide a theoretical basis for tire design with low noise tires.

Rubber mixing is an important link in the production of rubber products. Computational fluid dynamics (CFD) simulation is often used to explore the effect of rubber mixing parameters on rubber mixing effect. Previous CFD-based rubber mixing simulation studies did not consider the impact of using 2D or 3D numerical calculation models on the numerical simulation results. In order to investigate the differences between 2D and 3D numerical computational models in rubber compounding CFD simulation problems, in this paper, we compare and analyze the results obtained from 2D and 3D computational models under different rotational speed conditions to investigate the differences between the models in the numerical simulation of rubber compounding. Three different experimental speeds of the rubber mixer—39, 44, and 49 r/min—were set during the study using 2D and 3D asynchronous rotor models with a speed ratio of 1.15, respectively. The rubber was processed using the Bird–Carreau model. The phase interface between rubber and air was calculated using the volume of fluid (VOF) method. The numerical simulation results of different models show that the rotational speed set to 49 r/min shows the best dispersion distribution effect; the mixing effect and speed change rule obtained by the 2D model are consistent with the results obtained by the 3D model. The performance of the results of the two models is consistent when exploring the numerical simulation of rubber compounding.

The co-extrusion process is widely used to produce composite tire treads with better performance. This study investigated the rubber co-extrusion flow process and quality influencing factors of tri-composite tire tread through numerical simulation and experimental methods. Here, RPA 2000 rubber processing analyzer was used to carry out rheological tests on the three rubber materials, the PTT viscoelastic constitutive model was fitted, and the fitting curves were in good agreement with the test data. Then, a three-dimensional viscoelastic numerical simulation model of the tri-composite tread co-extrusion process was established using Ansys Polyflow software. The parameter evolution technique is adopted in the model establishment to improve the calculation convergence. In addition, a global remeshing function is used to avoid excessive mesh deformation. A co-extrusion experiment is conducted to verify the model’s accuracy using a tri-screw extruder. The extruded tread size error rate between the experiment and simulation is less than 6%. The variation of the velocity field, pressure field and shear rate field during extrusion is analyzed, and the formation mechanism of die swell is explained simultaneously. Finally, the influence of process parameters (inflow rate and traction speed) and die structure (convergence angle and thickness) on the extruded tire tread shape and quality was investigated, which can provide theoretical guidance for improving tread quality and production efficiency. Furthermore, the numerical simulation method can assist the design of the die plate in enhancing the efficiency of the die plate design.

The contact between the tire and the road surface causes tread deformation, and using traditional methods to measure tire tread deformation is difficult and time-consuming. Therefore, based on the principle of the digital image correlation method, this paper develops a binocular vision measurement system and realizes the measurement of tire tread deformation through the test bench for tire ground pressure distribution measurement. The related programs of the measurement system, including camera calibration, image matching, and strain fitting, are proposed. The deformation measurement accuracy of the test bench is validated by the sprayed speckle rubber sheet test, and the relative error of the theoretical value and measurement value is within 2%. The tire tread deformation test under static loading conditions was carried out using the test bench, and the tread strain distribution in the contact area was obtained. The analysis of the test results shows that the strain distribution in the contact patch is axisymmetric under static loading conditions. The longitudinal (tire rolling direction) deformation of the tread at the leading edge and the trailing edge area of the contact patch has the largest strain, while the deformation of the shoulder area on both sides of the contact patch is relatively small. For lateral (tire axial direction) deformation, the leading edge and the trailing edge areas of the contact patch are less deformed, and the strain distribution is approximately axisymmetric. The shoulder area of the contact surface has a larger deformation. The tire’s outer shoulder area has a larger deformation than the inside shoulder area, which may be due to the asymmetric tread structure of the tire. For the vertical deformation of the tread, the central area of the tread has the smallest strain, while the surrounding area has a much larger vertical strain.

As an important part of vehicle safety, tire durability has been paid close attention to which results from various factors including high temperature thermal oxidation of rubber compounds. In tire laboratories, an oven aging test is usually employed to induce severe thermal oxidation under a temperature up to 65°C. However, it is extremely difficult to perform real-time measurement of rubber oxygen consumption under high temperature to study the whole process. Therefore, with experimental property measurement of rubber compound as input, a tire Finite Element Analysis model based on Fick’s Law and Diffusion Limited Oxidation was built to simulate the tire oven aging process. The model outputs both global and local oxygen consumption of a tire which was then correlated with experimental durability hours. The result shows a positive effect of reduced global oxygen consumption on tire durability up to a threshold value below which tire durability is not strongly dependent on oxygen consumption. Local oxygen consumption of several key components including tread, belt, carcass, sidewall, and innerliner was also correlated with experimental tire durability hours and exhibits different patterns due to its unique locations and material properties.