A system for estimating a tire load of a tire includes a pressure sensor configured to generate a tire pressure signal; an acceleration sensor configured to generate a tire acceleration signal; a temperature sensor configured to generate a tire temperature signal; and at least one processor configured to calculate a duration of a contact patch based on the tire acceleration signal, calculate a vehicle speed based on the tire acceleration signal, determine at least one system model coefficient based on the tire pressure signal and the tire temperature signal, and calculate the tire load of the tire using a linear system model that relates tire pressure, the duration of the contact patch, and the vehicle speed to the tire load of the tire, where the linear system model further includes the at least one system model coefficient for calculating the tire load of the tire.

An apparatus for providing tire information is provided. The apparatus includes a detector that detects driving information as a vehicle is being driven and a controller that calculates a relative speed of a tire of the vehicle and a resonance frequency of the tire based on the driving information. The controller then compares the calculated relative speed and the calculated resonance frequency with a previously learned determination reference value to determine whether the tire is deflated.

An apparatus and a method for monitoring a tire pressure of a vehicle are provided. The apparatus for monitoring a tire pressure of a vehicle according to the present disclosure includes a first sensor configured for measuring a tire pressure of one of first to fourth wheels of the vehicle, a plurality of second sensors configured for respectively measuring wheel speeds of the first to fourth wheels, an analysis device configured for analyzing tire pressures of the first to fourth wheels based on a measured value from the first sensor and measured values from the second sensors, and a controller configured for determining a tire in a low-pressure state based on the tire pressure analysis results of the first to fourth wheels.

The invention concerns a tire damage detection system (1,1A) that includes an acquisition device (11), a processing system (12,12A) and a notification device (13,13A). The acquisition device (11) is installed on board a motor vehicle (2) equipped with two or more wheels fitted with tires, is coupled to a vehicle bus (20) of the motor vehicle (2), and is configured to acquire, from the vehicle bus (20), signals indicative of speeds of the motor vehicle (2) and of a wheel of said motor vehicle (2) and output quantities indicative of the speeds of the motor vehicle (2) and of the wheel thereof. The processing system (12,12A) is configured to store a predefined tire damage model and to receive, from the acquisition device (11), the quantities indicative of the speeds of the motor vehicle (2) and of the wheel of said motor vehicle (2), and is programmed to compute, based on the quantities indicative of the speeds of the motor vehicle (2) and of the wheel of said motor vehicle (2), a normalized wheel speed indicative of a ratio of the wheel speed to the motor vehicle speed, and detect a potential damage to a tire of the wheel of the motor vehicle (2) based on the predefined tire damage model and on the normalized wheel speed. The notification device (13,13A) is configured to, if a potential damage to the tire of the wheel of the motor vehicle (2) is detected by the processing system (12,12A), signal the detected potential damage to a user (3) associated with the motor vehicle (2). In particular, according to the present invention, the processing system (12) is a cloud computing system (12A) that is wirelessly and remotely connected to the acquisition device (11), while the notification device (13) is an electronic communication device (13A) associated with the user (3) and remotely connected to the cloud computing system (12A) via one or more wired and/or wireless networks.

A method for efficiently estimating a degree of wear of a tire in which a normalized deformation speed index is set as a wear measure. The normalized deformation speed index is obtained by normalizing an index of a deformation speed near an edge of a tire contact patch, the index being calculated from magnitudes of peaks appearing in a radial acceleration waveform obtained by differentiating tire radial acceleration detected by an acceleration sensor. The degree of wear of the tire is estimated using using the wear measure, the ground contact time ratio, a worn tire approximate formula and an approximate formula when a tire is new, which have been obtained in advance and each represents a relationship between the wear measure and the ground contact time ratio obtained by running a plurality of tires having tire sizes different from each other.

A method for determining a tread depth of a tread of a tire during operation of a vehicle having the tire, a control device for a vehicle for determining a tread depth of a tread of a tire of the vehicle, and a system for a vehicle having such a control device and at least one electronic wheel unit, are provided. Provision is made to determine the tread depth based on a determined instantaneous dynamic wheel radius of a wheel, having the tire, of the vehicle and a determined instantaneous dynamic inside radius of the tire. In addition, at least one further first operating parameter of the tire, selected from the group including an instantaneous roadway gradient, an instantaneous vehicle drive mode and an instantaneous tire material expansion, is determined and taken into consideration.

A system for estimating a tire load of a tire includes a pressure sensor configured to generate a tire pressure signal; an acceleration sensor configured to generate a tire acceleration signal; a temperature sensor configured to generate a tire temperature signal; and at least one processor configured to calculate a duration of a contact patch based on the tire acceleration signal, calculate a vehicle speed based on the tire acceleration signal, determine at least one system model coefficient based on the tire pressure signal and the tire temperature signal, and calculate the tire load of the tire using a linear system model that relates tire pressure, the duration of the contact patch, and the vehicle speed to the tire load of the tire, where the linear system model further includes the at least one system model coefficient for calculating the tire load of the tire.

A steering control method and system for a vehicle may determine whether the snow chain has been mounted by comparing the number of times of vibrations of a certain peak or more detected by respective wheel speed sensors with respect to a current vehicle speed with a predetermined value, and selectively controls the operations of an AFS and a RWS according to the position of the wheel on which the snow chain has been mounted, when it is determined that the snow chain has been mounted.

A mobile machine includes a plurality of ground-engaging elements that each include a tire, and a plurality of motors, one motor coupled to each of the plurality of ground-engaging elements configured to drive movement of the plurality of ground-engaging elements. The mobile machine also includes a speed sensor coupled to each motor configured to generate speed signals indicative of an operating speed of each motor. The mobile machine includes a tire calibration system configured to receive the speed signals from each speed sensor and to identify a tire size differential across the plurality of ground-engaging elements based on the speed signals. The mobile machine includes a control system configured to generate a separate control signal for each of the plurality of motors based on the tire size differential.

A system for determining a tire pressure status in a vehicle is provided. The system includes at least one processing device, which may be arranged to: estimate values of a set of predetermined vehicle parameters; calculate a tire pressure parameter as a predetermined function of the values of the set of predetermined vehicle parameters, wherein said predetermined function has been generated by training a machine learning system, such as, for example, a neural network or a Support Vector Machine, using values of a large number of sets of predetermined vehicle parameters and associated tire pressure parameters; and determine a tire pressure status, indicating whether or not there is tire under-inflation, by comparing said tire pressure parameter with a threshold.