Abstract: 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.

Abstract: A tire pressure monitoring system monitors the pressure in at least one tire supporting a vehicle. The system includes at least one sensor mounted on the tire for measuring a pressure and a temperature of the tire. Transmission means transmit the measured pressure data and temperature data to a processor, and a tire pressure model is executed on the processor. The tire pressure model includes a driving event extractor to extract cold pressure data from the measured pressure data, and a temperature compensator to generate a compensated cold tire pressure from the cold pressure data. A noise filter filters sensor noise and generates a filtered cold tire pressure from the compensated cold tire pressure. A detection module receives the filtered cold tire pressure and determines an air pressure leak rate of the tire, and a leak notification corresponding to the air pressure leak rate is generated.

Abstract: A tire wear estimation system is provided. The system includes at least one tire that supports a vehicle. At least one sensor is affixed to the tire to generate a first predictor. A lookup table or a database stores data for a second predictor. One of the predictors includes at least one vehicle effect. A model receives the predictors and generates an estimated wear rate for the at least one tire.

Abstract: 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.

Abstract: A vehicle sideslip estimation system includes sensors mounted on a vehicle and a kinematic model receiving signals from the sensors to estimate a lateral velocity of the vehicle. A compensated acceleration calculator calculates a compensated lateral acceleration as a measure of conditions that result in a deviation of a measured lateral acceleration. A lateral acceleration calculator determines, based on the compensated lateral acceleration and the measured lateral acceleration, if a lateral acceleration error is larger than a predefined threshold. A filter corrects the estimated lateral velocity of the vehicle when the lateral acceleration error is larger than the predefined threshold.

Abstract: A tire wear state estimation system includes a tire that supports a vehicle. A sensor unit is mounted on the tire and includes a footprint centerline length measurement sensor, a pressure sensor, a temperature sensor, and electronic memory capacity for storing identification information for the tire. A processor is in electronic communication with the sensor unit and receives the measured centerline length, the measured pressure, the measured temperature and the identification information. A tire construction database stores tire construction data and is in electronic communication with the processor. The identification information is correlated to the tire construction data. An analysis module is stored on the processor and receives the measured centerline length, the measure pressure, the measured temperature, the identification information, and the tire construction data as inputs. The analysis module includes a prediction model that generates an estimated wear state for the tire from the inputs.

Abstract: A tire wear state estimation system includes a first sensor unit that is mounted on a tire and includes a footprint centerline length measurement sensor. A second sensor unit is mounted on the tire and includes a shoulder length measurement sensor. At least one of the first sensor unit and the second sensor unit includes a pressure sensor, a temperature sensor, and electronic memory capacity for storing tire identification information. A processor is in electronic communication with the sensor units and receives the measured centerline length, the measured pressure, the measured temperature, the identification information, and the measured shoulder length. The identification information is correlated to tire construction data. An analysis module stored on the processor receives the measured values, the identification information, and the tire construction data as inputs. The analysis module includes a prediction model that generates an estimated wear state for the tire from the inputs.

Abstract: A method for extracting changes in characteristics of a tire supporting a vehicle is provided. The method includes extracting selected tire characteristics from at least one sensor mounted on the tire. The selected tire characteristics are transmitted to a remote processor and are stored in a historical data log that is in communication with the remote processor. At least one tire characteristic of interest is selected, and a time series decomposition model is applied to data from the historical data log to delineate exogenous inputs from an underlying trend in the selected tire characteristic of interest. A learning model is applied to the underlying trend in the selected tire characteristic of interest to model a relationship between the selected tire characteristic of interest and a condition of the tire. A prediction value for a condition of the tire is output from the learning model.

Abstract: A tire data information system includes at least one tire that supports a vehicle and a processor. At least one sensor is mounted on the tire and is in electronic communication with the processor. The sensor measures a temperature and a pressure of the tire. A memory for storing tire identification information is in electronic communication with the processor. Tire wear state means generate a wear state of the tire and are in electronic communication with the processor. Tire wear rate means generate a wear rate of the tire and are in electronic communication with the processor. Transmission means transmit the temperature, pressure, identification information, wear state, and wear rate of the tire to a display device that is accessible to a user of the vehicle. The display device includes indicators for showing the temperature, pressure, identification information, wear state, and wear rate to the user.

Abstract: A tire wear state estimation system includes a CAN bus system disposed on a vehicle. A tire supporting the vehicle is mounted on a wheel. A wheel sensor unit is mounted on a structure adjacent the wheel, and the wheel sensor unit includes a longitudinal acceleration sensor to generate a longitudinal acceleration signal. The wheel sensor unit also includes a vertical acceleration sensor to generate a vertical acceleration signal, and transmission means to communicate the longitudinal acceleration signal and the vertical acceleration signal to the CAN bus system. A processor receives the longitudinal acceleration signal and the vertical acceleration signal. An extractor extracts a tire translational mode from the longitudinal acceleration signal and a tire vertical mode from the vertical acceleration signal. The tire translational mode and the tire vertical mode are input into a classifier to generate a wear state estimation for the tire. A method is also provided.

Abstract: A tire load estimation system includes at least one tire supporting a vehicle, in which the at least one tire includes a pair of sidewalls extending to a circumferential tread. A sensor is mounted to the at least one tire. A footprint is formed by the tread and includes a centerline with a footprint centerline length. The footprint centerline length is measured by the sensor. A tire load estimator receives a precalibrated sensitivity, the footprint centerline length during straight-line driving conditions, a reference footprint value, and a reference load value as inputs. The tire load estimator determines an estimation of tire load and outputs the estimation to at least one of a vehicle control system and a vehicle electronic control unit. A method for estimating the load of a tire is also provided.

Abstract: A tire wear state estimation system includes at least one sensor disposed on a vehicle and a CAN bus system. The sensor measures selected parameters associated with the vehicle and communicates data for the selected parameters through the CAN bus system, including a first set of data, a second set of data and a third set of data. A rolling radius estimator receives the first set of data and estimates a rolling radius for the tire. An acceleration slip estimator receives the second set of data and the estimated rolling radius to estimate the slip of the tire during acceleration. A braking slip estimator receives the third set of data and the estimated rolling radius to estimate the slip of the tire during braking. A tire slip analyzer correlates the acceleration slip estimation and the braking slip estimation and generates an estimated wear state of the tire.

Abstract: An assembly determines operating parameters of a tire. The assembly includes a tripod sensor mounted within an inner cavity of the tire underneath a crown portion and an innerliner on which the tripod sensor is mounted. The tripod sensor includes a tri-axial accelerometer for creating a circumferential signal for determining slip ratio, a lateral signal for determining a slip angle, and a radial signal for determining load on the tire.

Abstract: A system and method of estimating a load bearing on a vehicle tire includes an inflation pressure measuring sensor for measuring an inflation pressure level within a tire cavity; a contact patch length sensor measuring the rolling contact patch length of the tire; a tire rolling speed sensor measuring a rolling speed of the tire; and a tire wear state estimation calculator estimating a tire wear state of a tread of the tire. An artificial neural network estimates a tire load from the contact patch length, the inflation pressure level, and the tire rolling speed by utilizing as a compensation factor input the estimated tire wear state.

Abstract: A tire wear state estimation system includes at least one sensor disposed on a vehicle and a CAN bus system. The sensor measures selected parameters associated with the vehicle and communicates data for the selected parameters through the CAN bus system, including a first set of data, a second set of data and a third set of data. A rolling radius estimator receives the first set of data and estimates a rolling radius for the tire. An acceleration slip estimator receives the second set of data and the estimated rolling radius to estimate the slip of the tire during acceleration. A braking slip estimator receives the third set of data and the estimated rolling radius to estimate the slip of the tire during braking. A tire slip analyzer correlates the acceleration slip estimation and the braking slip estimation and generates an estimated wear state of the tire.

Abstract: A tire wear estimation system is provided. The system includes at least one tire that supports a vehicle. At least one sensor is affixed to the tire to generate a first predictor. A lookup table or a database stores data for a second predictor. One of the predictors includes at least one vehicle effect. A model receives the predictors and generates an estimated wear rate for the at least one tire.

Abstract: A system and method estimating a vehicle tire load identifies a change in vehicle loading condition by measuring vibration resonant frequency peaks (bounce mode and/or pitch mode) of the unsprung mass. Signals required include the chassis vertical acceleration and/or chassis pitch rate obtained from commercially available sensors mounted to the vehicle. An observer model receives the inertial signal(s) and generates a dynamic load estimation based upon observed frequency change in the sprung mass natural frequency.

Abstract: A vehicle state estimation system and method uses an observer model to make cornering stiffness estimates from tire-based sensor data and vehicle-based sensor data throughout transient and non-transient operational maneuvers of a vehicle. A cornering stiffness identifier extracts transient-state cornering stiffness estimates from the cornering stiffness estimates made by the observer model and extracts from the transient-state cornering stiffness estimates an optimal transient-state cornering stiffness estimate having a substantially highest confidence measure for use by a vehicle control system.

Abstract: 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.

Abstract: 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 wheel imbalance based upon measurements.