A method for pairing a measurement module with a wheel of a motor vehicle. The method is implemented by a computer and includes, for each received measured signal, determining the power of the measured signal, determining the angular orientation of each wheel and identifying, in a plurality of tables, a row and column pair including the determined power and the angular orientation of each wheel. The pairing being performed when, for a number of determined columns of each table higher than a first minimum threshold, the number of row and column pairs identified in one table is lower than a predetermined maximum threshold and the number of row and column pairs identified in the other tables is higher than a second minimum threshold.

Provided is a wheel load estimation device configured to acquire wheel speed information of each wheel included in a vehicle from a wheel speed sensor provided in the vehicle; to calculate a front-rear load ratio and a left-right load ratio based on the wheel speed information; and to calculate a wheel load ratio expressing a relative wheel load between the wheels included in the vehicle, with respect to at least one wheel of the vehicle, based on the front-rear load ratio and the left-right load ratio. The front-rear load ratio is a ratio between a load applied to a front wheel of the vehicle and a load applied to a rear wheel of the vehicle, and the left-right load ratio is a ratio between a load applied to a left wheel of the vehicle and a load applied to a right wheel of the vehicle.

An indirect tire pressure monitoring (WSB TPMS) method includes establishing a wheel speed reference value database using a vehicle speed, and correcting the real-time wheel speed through tire wear compensation, and then based on a comparative analysis of the real-time wheel speed and the wheel speed reference value, determining the degree of tire deflection deformation and tire safety, and to give an alert message prompt based on the tire pressure abnormality information.

A system for determining a tire change status in a vehicle is provided. The system includes at least one processing device and a storage device. The at least one processing device may be arranged to: calculate a value of at least one reference parameter which may be used in indirect tire pressure monitoring; store the calculated value of said at least one reference parameter in the storage device; retrieve a previously stored value of said at least one reference parameter from the storage device; determine a similarity parameter based on a similarity between the calculated value and the previously stored value of said at least one reference parameter; and determine a tire change status, indicating whether or not the tires have been re-filled or replaced, by comparing said similarity parameter with a threshold.

Embodiments provide a fail-safe device, a tire pressure measurement system, a vehicle, a tire, a method and a computer program for monitoring a first sensor of a tire pressure monitoring system. The fail-safe device includes a first input for a first signal from the first sensor. The first signal indicates a first physical quantity. The fail-safe device includes a second input for a second signal from a second sensor. The second signal indicates a second physical quantity. The fail-safe device further includes a control module to verify the first signal based on the second signal and a physical relation between the first and the second physical quantities.

Embodiments provide a fail-safe device, a tire pressure measurement system, a vehicle, a tire, a method and a computer program for monitoring a first sensor of a tire pressure monitoring system. The fail-safe device includes a first input for a first signal from the first sensor. The first signal indicates a first physical quantity. The fail-safe device includes a second input for a second signal from a second sensor. The second signal indicates a second physical quantity. The fail-safe device further includes a control module to verify the first signal based on the second signal and a physical relation between the first and the second physical quantities.

Thread depth ascertainment for vehicle tires involves a plurality of vehicles transmitting respective adaptation data to a central data processor. The data processing device forming optimization data on the basis thereof and transmitting the optimization data to the vehicles. The adaptation data are formed by the vehicles based on tire type, mileage and rotation speed of the tire and a velocity of the vehicle and at least one operating parameter of the tire, and the optimization data are used by each of the vehicles for ascertaining the tread depth of a relevant tire based on model of the ascertained tire type, wherein the model supplies the tread depth based on the rotation speed of the tire, the velocity of the vehicle and at least one operating parameter of the tire using at least one model parameter, which is determined based on the optimization data received from the central data processor.

A tire load estimation device includes: acceleration sensors; a total vehicle weight calculating device; an acceleration waveform extracting device; a differential acceleration waveform calculating device; a peak position detecting device detecting peak positions on leading and trailing edge sides in the differential acceleration waveform; a ground contact time ratio calculating device calculating ground contact and rotation times from the peak positions to calculate a ground contact time ratio; and a lord estimating device estimating the load acting on the tire from the ground contact time ratio of each tire, a maximum load capability of the tire, the total vehicle weight, and an inclination obtained in advance by approximating a maximum load capability ratio, which is a value obtained by normalizing the load with the maximum load capability, with a linear function of the ground contact time ratio.

A system includes a computer including a processor and a memory, the memory storing instructions executable by the processor to determine that a steering disturbance based on a difference between current vehicle state data and corresponding vehicle state model data exceeds a threshold, the vehicle state model including a yaw rate and a vehicle speed and, then, identify a wheel misalignment condition.

A pressure ratio between a setpoint tire pressure and an actual tire pressure for a tire of a vehicle is ascertained by the following steps: Ascertaining a wheel load which is acting on the tire. Ascertaining a dynamic tire radius of the tire. Ascertaining the pressure ratio as a function of the wheel load and the dynamic tire radius.