A system and method are provided for estimating and applying vehicle tire traction. Vehicle data (e.g., movement and location-based data) and tire sensor data are collected at a vehicle and transmitted to a remote computing system (e.g., cloud server). A wear status is determined, and traction characteristics determined for at least one tire, based at least on the vehicle data and the determined tire wear status. The predicted tire traction characteristics are transmitted from the remote computing system to an active safety unit associated with the vehicle, or a fleet management system, wherein the recipient is configured to modify vehicle operation settings based on at least the predicted tire traction characteristics. A maximum speed for the vehicle may be defined by the recipient, or a minimum following distance where, e.g., the vehicle is one of multiple vehicles in a defined platoon.

Provided is a rotation speed correction apparatus configured to correct a rotation speed of a driving wheel tire mounted on a vehicle, and includes a comparative value calculation unit, a torque obtainment unit, and a rotation speed calculation unit. The comparative value calculation unit calculates a comparative value between a rotation speed of the driving wheel tire and a rotation speed of a following wheel tire mounted on the vehicle on the basis of the rotation speeds of the driving wheel tire and the following wheel tire. The torque obtainment unit obtains a wheel torque. The rotation speed calculation unit identifies a linear relationship between the comparative value and the wheel torque, and on the basis of the rotation speed of the following wheel tire and the linear relationship, calculates a rotation speed of the driving wheel tire in which influence of slippage has been eliminated.

Disclosed are a method and a system for monitoring the pressure of a tire. The system measures frequencies of multiple tires mounted on the vehicle, sets a first average frequency for a normal pressure state and a second average frequency for determination of a low pressure state, wherein the first average frequency is calculated by accumulating the measured frequencies for each speed interval in a stop mode and the second average frequency is calculated by accumulating the measured frequencies for each speed interval in a driving mode, calculates low-pressure probabilities for each speed interval of the tire by using the second frequency, a predetermined low-pressure reference frequency, and a predetermined frequency determination interval for determining low-pressure, and determines whether each tire is at low pressure state by aggregating the low-pressure probabilities for each speed interval of the tire.

Various embodiments of a smart non-pneumatic tire and methods for generating a mean vibration characteristic of the smart non-pneumatic tire are described. In one embodiment, a method for measuring the mean vibration characteristic includes receiving tire-road contact acceleration data from an accelerometer that is secured near a tire-surface contact region, where the tire-road contact acceleration data includes data captured by the accelerometer over a duration of time while a tread along an outer periphery of a sector of the tire contacts a surface. The method further includes receiving velocity data for the tire and load data for the tire over the duration of time. The method further includes generating a mean vibration characteristic based on the above-mentioned data. The method also includes changing a stiffness of spokes of the tire based on the generated mean vibration characteristic in some cases.

A system and method are provided for estimating progression in vehicle tire wear. A tread depth is stored at a first (e.g., initial or unworn) stage for a given tire, along with a first set of modal frequencies for the tire. At a later (e.g., worn) stage, for example in concert with a controlled excitation of tire structural modes, a second set of corresponding modal frequencies are sensed for the tire, and a tire wear status of the tire is determined at the second stage based on a calculated frequency shift between at least one corresponding modal frequency from each of the first and second sets. In one example, an initial mass of the tire is stored, and a change in mass is calculated based on the calculated frequency shift. Alternatively, a correlation of modal frequency shift may be performed with respect to tread depth for a given tire.

The invention relates generally to tire monitoring systems for collecting measured tire parameter data during vehicle operation and, more particularly, to a system and method for estimating tire wear state and inflation pressure based upon such measurements.

A vehicle and method for controlling the same are provided to provide more reliable tire pressure information than the existing tire pressure detecting system using a method of calculating a wheel frequency once every predetermined reference vibration count. The vehicle includes a sensor unit that measures a wheel speed and a controller that divides a vibration count of wheel derived based on the wheel speed by a predetermined reference vibration count to calculate at least one frequency. The at least one frequency is analyzed to derive a state of pressure of a tire mounted on the wheel, and the tire pressure state to be output is adjusted to then be output.

A tire pressure decrease detection apparatus comprising a rotation speed information detection unit for detecting rotation speed information of wheels of a vehicle, a resonance frequency estimate unit for time-series estimating a torsional resonance frequency of the rotation speed information from the rotation speed information obtained by the rotation speed information detection unit, and a judgment unit for judging a decrease in pressure of tires installed in the wheels based on the estimated torsional resonance frequency. The resonance frequency estimate unit includes a noise removal unit for removing a noise superimposed on a wheel speed signal serving as the rotation speed information for each of the wheels with using an active noise control technology.

A system and method are provided for efficiently estimating vehicle tire wear. Vehicle kinetics (first) data are provided via one or more sensors associated with the vehicle and/or at least one associated tire. The vehicle kinetics data are locally processed to compress or otherwise generate second data as a reduced subset thereof, said second data representative of the first data and comprising any one or more predetermined wear-specific features extracted therefrom. The second data are selectively transmitted via a communications network to a remote computing system, which processes the second data to estimate a wear characteristic for the at least one tire. Alternatively, the second data processed to generate third data as a reconstruction of the first data, and the third data and the any one or more extracted features are processed to estimate a wear characteristic for the at least one tire.

The present invention relates to an apparatus and a method for monitoring a tire pressure using a speed section. The tire pressure monitoring apparatus using a speed section of the present invention includes a frequency measuring unit which measures frequency data for every wheel mounted on a vehicle; a frequency calculating unit which calculates a mean frequency for every speed section by accumulating the measured frequency data for every predetermined speed section to obtain a mean; a frequency calibration unit which performs the frequency calibration by calculating a deviation of the mean frequency for every adjacent speed section and comparing the calculated deviation of the mean frequency with the predetermined frequency range; and a low pressure determining unit which determines a low pressure by performing the frequency analysis in accordance with the speed section in which the frequency calibration is completed.