A circumferential main groove detection method for detecting, by a computer, a position of a circumferential main groove of a tire from 3D data of a tread surface of the tire, the method including: a cross-sectional data extracting step of extracting, at a plurality of places in a tire circumferential direction, cross-sectional data of the tread surface along one direction inclined with respect to the tire circumferential direction; an area dividing step of dividing the cross-sectional data respectively into a plurality of areas along one direction; an evaluating step of evaluating relative unevenness in the areas; and a circumferential main groove identifying step of overlaying evaluation results of divided areas at an identical position in the tire circumferential direction and identifying the position of the tire circumferential main groove.

A tire deterioration inferring (estimating) method uses a tire deterioration inferring device placed on the inner surface of a tire. The method has: a deformation velocity measurement step of measuring a tire deformation velocity, which is the deformation velocity of the tire while the tire is rotating, and obtaining time-series changes in the tire deformation velocity; a calculation step of calculating peak values of the tire deformation velocity from the time-series changes in the tire deformation velocity; and an inference step of inferring the degree of the deterioration of the tire by using a first peak value, which is a peak value of the tire deformation velocity before and at the stepping of the tire or at and after the kicking of the tire, the first peak value being in the time-series changes in the tire deformation velocity.

A tire can include a first magnetic body disposed at a predetermined position in a tread portion, a magnetic sensor disposed radially inward of the first magnetic body, and a second magnetic body disposed closer to the magnetic sensor than the first magnetic body is. At a position where the magnetic sensor is disposed, a direction of a magnetic force line emitted by the first magnetic body and a direction of a magnetic force line emitted by the second magnetic body can be different from each other.

There is provided a computerized system comprising a processing unit and associated memory configured to obtain a three-dimensional dataset informative of at least part of a tread of a tire, and determine, using the three-dimensional dataset, data informative of tread depth of the tire.

A vehicle includes a first wheel, a second wheel, and a controller. The first and second of wheels have first and second tires, respectively. The controller is programmed to receive inputs indicative of tire tread wear of the first and second wheels. The controller is further programmed to, in response to a command to adjust torques of the first and second wheels to first and second desired torque values, respectively, and a difference between a tire tread wear of the first wheel and a tire tread wear of the second wheel exceeding a threshold, adjust the torque of the first electric machine to less than the first desired torque value and adjust the torque of the second electric machine to greater than the second desired torque value.

A method and system are provided for estimating tire tread depth, the method comprising: obtaining an image of the tire informative of tread and grooves embedded therein, wherein the image is acquired by an imaging device from a first angle relative to a horizontal direction perpendicular to tread surface, and the tire is illuminated by an illumination device from a second angle relative to the horizontal direction, causing a shadow section and an illuminated section at the bottom and/or sidewall of a groove, the first angle being smaller than the second angle, such that the image captures the illuminated section and at least part of the shadow section; performing segmentation on the image to obtain image segments corresponding to the illuminated section and the at least part of the shadow section; and estimating the tread depth based on the image segments, the groove width, and the second angle.

A tire wear state estimation system includes at least one tire that supports a vehicle. A sensor is mounted on the tire and measures tire parameters. At least one sensor is mounted on the vehicle and measures vehicle parameters. Each one of a plurality of sub-models receives selected tire parameters from the tire mounted sensor and selected vehicle parameters from the vehicle mounted sensor. Each one of the sub-models generates a sub-model wear state estimate, and a model reliability is determined for each one of the sub-models. A supervisory model receives the wear state estimate from each sub-model and the model reliability for each sub-model, and generates a combined wear state estimate for the tire.

A contactless tire inspection apparatus for tire tread depth measurement using 3D reconstruction includes a driver side (DS) measurement device (MD) and a passenger side (PS) MD. The DS MD includes a DS light source configured to, responsive to receiving a trigger signal (TS), project a first structured illumination (SI) onto a DS tire of a vehicle and at least one DS camera configured to, responsive to receiving the TS, capture DS image(s) of the first SI projected onto the DS tire for 3D reconstruction. The PS MD includes a PS light source configured to, responsive to receiving the TS, project a second SI onto a PS tire of the vehicle and at least one PS camera configured to, responsive to receiving the TS, capture PS image(s) of the second SI projected onto the PS tire for 3D reconstruction when the at least one DS camera captures DS image(s).

A computer-implemented method as disclosed enables predicting of vertical loads on a vehicle tire. Thermal characteristics for a particular vehicle-tire combination are retrievably stored, the thermal characteristics determined as corresponding to a range of temperature values further correlated with a plurality of operating conditions, and the plurality of operating conditions comprising at least a vertical load. A model for predicting transient temperature behavior is generated (e.g., empirically trained) based on one or more tire-specific time constants. During operation of the vehicle-tire combination and responsive to at least a first temperature value, a computing device residing on the vehicle or otherwise cloud-based in nature is configured to determine a predicted vertical load based on a predicted second temperature value from the model and further based on the retrievably stored one or more thermal characteristics.

A system and method are provided for Bayesian updating of distributions of factors that affect tire wear. Information is accumulated in data storage regarding probability distributions corresponding to each of a respective plurality of tire wear factors. Vehicle data comprising movement data and location data collected in association with a vehicle is transmitted from the vehicle to a centralized (e.g., cloud) computing device or network. At least one observation corresponding to one or more of the plurality of factors is generated based on the transmitted vehicle data. A Bayesian estimation is then generated of a tire wear status at a given time for at least one tire associated with the vehicle, based at least on the at least one generated observation and the stored information regarding probability distributions. The predictions accordingly carry a measure of uncertainty, and Bayesian inference can be used to update distributions based on the observations.