A method for determining a state of a road surface in which, a time-series waveform of tire vibration detected by an acceleration sensor is windowed by a windowing means with a time T and a feature vector X.sub.i in each time window is calculated through the extraction of a time-series waveform of the tire-vibration in each time window. Thereafter, in the calculation of a kernel function K.sub.A from the feature vector X.sub.i in each time window and a road surface feature vector Y.sub.Aj that is a feature vector in each time window calculated from a time-series waveform of tire-vibration that has been calculated in advance for each road surface state, the feature vector X.sub.i in each time window and the road-surface feature vector Y.sub.Aj are made to be vibration levels of frequency bands of 500 Hz or greater extracted from the time-series waveform in each time window.

A condition in which an abnormality can occur in a tire is accurately detected on the basis of a detection signal from an acceleration sensor used to detect a road surface state and a possibility that an abnormality has occurred in the tire is also detected. In addition, the detection result is stored as a diagnosis history. The diagnosis history or the possibility that an abnormality has occurred in the tire are notified through a notification device in a vehicle body side system so that a user is informed in advance of the possibility that an abnormality has occurred in the tire. In addition, when the diagnosis history is checked through a tool in a car repair shop, etc., the diagnosis history stored in a tire-mounted sensor is read out. Accordingly, the possibility of abnormality of the tire can be informed also in the car repair shop, etc.

A method for estimating a grip of a tire supporting a vehicle includes generating a first set of data from a tire-mounted sensor unit, generating a second set of data from the tire-mounted sensor unit and from data obtained from the vehicle, and generating a third set of data from data obtained from the vehicle and from the Internet. A grip estimation module is provided. The first, second and third sets of data are received in the grip estimation module. A friction probability distribution is calculated with the grip estimation module using the first, second and third sets of data, and the friction probability distribution is input into at least one vehicle system.

A control unit of a tire side device has a feature amount extraction part, a feature amount storage part, a change determination part, a vehicle speed estimation part, and an algorithm switching part. The change determination part determines whether or not there is a change in the road surface condition based on a present feature amount and a previous feature amount stored in the feature amount storage part, and transmits a road surface data including the present feature amount when there is a change in the road surface condition. The algorithm switching part switches based on the vehicle speed estimation by the vehicle speed estimation part whether to transmit the road surface data from the transmission unit when the road surface condition is changed, or to transmit the road surface data without determining whether or not the road surface condition is changed by the change determination part.

A computer-implemented method is provided for tire state estimation using a physics-based model rather than empirical models. During a calibration process, data is collected in data storage as correlating a first set of tire acceleration values for a given tire model to respective known values for each of a plurality of tire state variables. A physics-based tire model is generated corresponding to the given tire model and comprising one or more tire model parameters determined upon calibration and which remain constant under different conditions. During operation of the tire, measurements are collected for a second set of tire acceleration values and certain of the tire state variables (e.g., speed and inflation) via one or more tire-mounted sensors. At least one of the unmeasured tire state variables (e.g., load and/or tread depth) is estimated based on the second set of tire acceleration values and using the physics-based tire model.

Assembly comprising a vehicle (13,13a-c) having a plurality of wheels (2), each of the wheels (2) arranged to support a weight of the vehicle (13) against an underlying surface (5); a sensor (10) operable to measure a force between one of the wheels (2) and a body of the vehicle (13,13a-c); and a processor (15) configured to receive measurement data from the sensor (10). There is also provided a method for measuring conditions of a drive surface (5) and a method of operating vehicles (13,13a-d) on a road (5).

Devices, systems, and methods related to prediction of tire performance using existing CAN data to improve overall vehicle performance. Machine learning tools are applied to CAN data, for example pilot data and/or vehicle dynamics data, to predict tire performance factors for use in a vehicle control system to provide vehicle lateral guidance control.

Methods and systems for adaptively configuring a tire mounted sensor (TMS) with vehicle-provided parameters are disclosed. A vehicle control unit obtains data from vehicle sensors and other sources and transmits configuration parameters to the TMS. The TMS signal processing components are configured according to the configuration parameter to minimize the number of tire rotations needed to generate an accelerometric profile and extract a tire feature. The extracted feature is transmitted back to the vehicle control unit with the aim of minimizing the computational resources and battery consumption of the TMS.

The disclosure relates to a method for monitoring behavior of a tire of a vehicle in a rolling condition of the tire, comprising the steps of: acquiring a signal representative of an acceleration of a specified point of the tire, deriving from the signal a curve which represents a profile of the acceleration of the point during a revolution of the tire, determining a leading portion and a trailing portion of the curve, corresponding to an entry of the point into a footprint region of the tire and corresponding to an exit of the point from the footprint region of the tire, respectively, determining a first measure of a volatility of the signal in the leading portion and a second measure of a volatility of the signal in the trailing portion, and determining an indication of the behavior of the tire based on the first measure and the second measure.

A sound measurement system intended to be installed on a motor vehicle, the system comprising: a microphone, an element for supporting the microphone, mechanical means for protecting the microphone against various projections (water, dust, etc.) from the environment of the vehicle, and mechanical means for protecting the microphone from airborne noise originating from the routing of the sound wave between the source and the measurement (cavity noise) and from the environment of the measuring system (turbulence around the measuring device), the various mechanical protection means being separate or combined. A motor vehicle may be provided with such a system.