Browse Topic: Tires
A futuristic vehicle chassis rendered in precise detail using state-of-the-art CAD software like Blender, Autodesk Alias. The chassis itself is sleek, low-slung, and aerodynamic, constructed from advanced materials such as high-strength alloys or carbon-fibre composites. Its polished, brushed-metal finish not only exudes performance but also emphasizes the refined form and engineered details. Underneath this visually captivating structure, a sophisticated system of self-hydraulic jacks is seamlessly integrated. These jacks are situated adjacent to the four shock absorber mounts. These jacks are designed to lift the chassis specifically at the tyre areas, and the total vehicle, ensuring that underbody maintenance is efficient and that, in critical situations, vital adjustments or emergency lifts can be performed quickly and safely. The design also incorporates an intuitive control system where the necessary buttons are strategically placed to optimize driver convenience. Whether
This SAE Standard applies to all combinations of pneumatic tires, wheels, or runflat devices (only as defined in SAE J2013) for military tactical wheeled vehicles only as defined in SAE J2013. This applies to original equipment and new replacement tires, retread tires, wheels, or runflat devices. This document describes tests and test methodology, which will be used to evaluate and measure tire/wheel/runflat system and changes in vehicle performance. All of the tests included in this document are not required for each tire/wheel/runflat assembly. The Government Tire Engineering Office and Program Office for the vehicle system have the responsibility for the selection of a specific test(s) to be used. The selected test(s) should be limited to that required to evaluate the tire/wheel/runflat system and changes in vehicle performance. Selected requirements of this specification shall be used as the basis for procurement of a tire, wheel, and/or runflat device for military tactical wheeled
This SAE Recommended Practice (RP) describes a test method for determination of heavy truck (Class VI, VII, and VIII) tire force and moment properties under straight-line braking conditions. The properties are acquired as functions of normal force and slip ratio using a sequence specified in this practice. At each normal force increment, the slip ratio is continually changed by application of a braking torque ramp. The data are suitable for use in vehicle dynamics modeling, comparative evaluations for research and development purposes, and manufacturing quality control. This document is intended to be a general guideline for testing on an ideal machine. Users of this RP may modify the recommended protocols to satisfy the needs of specific use-cases; e.g., reducing the recommended number of test loads and/or pressures for benchmarking purposes. However, due care is necessary when modifying the protocols to maintain data integrity.
To evaluate the performance evolution patterns of road structures under natural environmental conditions and loading, data were collected from the RIOHTrack system. Pavement deflection, smoothness, and skid resistance were selected as evaluation indicators. The performance evolution characteristics over 50 million load cycles were analyzed to investigate the impact of different structural configurations on service performance. The study results are summarized as follows: The deflection basin area exhibits significant annual cyclic fluctuations, indicating that ambient temperature significantly affects pavement deflection. The initial rapid decrease in texture depth was attributed to the compaction of the surface layer under traffic loading, leading to a reduction in texture depth. Differences in tire and subgrade stiffness can cause variations in texture depth across various scenarios. Circular pavement structures' smoothness can be categorized into three classes; however, even within
This SAE Recommended Practice describes the classification of off-road tires and rims designed specifically for forestry machines (refer to SAE J1116), defines related terminology in common use, and shows representative construction details of component parts.
This study introduces an innovative intelligent tire system capable of estimating the risk of total hydroplaning based on water pressure measurements within the tread grooves. Dynamic hydroplaning represents an important safety concern influenced by water depth, tread design, and vehicle longitudinal speed. Existing intelligent tire systems primarily assess hydroplaning risk using the water wedge effect, which occurs predominantly in deep water conditions. However, in shallow water, which is far more prevalent in real-world scenarios, the water wedge effect is absent at higher longitudinal speeds, which could make existing systems unable to reliably assess the total hydroplaning risk. Groove flow represents a key factor in hydroplaning dynamics, and it is governed by two mechanisms: water interception rate and water wedge pressure. In both the shallow water and deep water cases, the groove water flow will increase as a result of increasing the longitudinal speed of the vehicle for a
This paper presents an analytical approach for identifying suspension kingpin alignment parameters based on screw axis theorem and differential calculation model. The suspension kingpin caster and inclination alignment parameters can produce additional tire force, which affects vehicle handling dynamics. In wheel steering process, the multi-link suspension control arms lead to movement of the imaginary kingpin, which can cause change in suspension kingpin alignment parameters. According to the structure mechanism of commercial vehicle multi-link independent suspension, the kinematics characteristics of imaginary kingpin were analyzed based on the screw axis theorem. The angular velocity and translation velocity vectors were calculated. In order to avoid the influence of bushing deformation, the unique differential identification model was established to evaluate the suspension kingpin alignment parameters, and the identification results were compared with the ADAMS/Car data. The
A test and signal processing strategy was developed to allow a tire manufacturer to predict vehicle-level interior response based on component-level testing of a single tire. The approach leveraged time-domain Source-Path-Contribution (SPC) techniques to build an experimental model of an existing single tire tested on a dynamometer and substitute into a simulator vehicle to predict vehicle-level performance. The component-level single tire was characterized by its acoustic source strength and structural forces estimated by means of virtual point transformation and a matrix inversion approach. These source strengths and forces were then inserted into a simulator vehicle model to predict the acoustic signature, in time-domain, at the passenger’s ears. This approach was validated by comparing the vehicle-level prediction to vehicle-level measured response. The experimental model building procedure can then be adopted as a standard procedure to aid in vehicle development programs.
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