Abstract: An auto-location system locates a position of a tire. A tire sensor unit is mounted on the tire and measures a length of a footprint of the tire, and electronic memory capacity stores identification information for the tire sensor unit. A vehicle sensor unit is mounted on the vehicle and measures a lateral acceleration and a longitudinal acceleration. A processor is in electronic communication with the tire sensor unit and the vehicle sensor unit, and receives the measured footprint length, the identification information, the lateral acceleration, and the longitudinal acceleration. A virtual footprint length estimator employs the lateral acceleration and the longitudinal acceleration to estimate a virtual footprint length of the tire. A correlation module receives the virtual footprint length and the measured footprint length to generate correlation values. A decision arbitrator applies a set of decision rules to the correlation values to generate a wheel position indication.

Abstract: A method, comprising: measuring a rotational speed of a wheel of a vehicle, determining a longitudinal acceleration of the vehicle relative to a plurality of ambient terrestrial objects using a measurement system onboard the vehicle, determining a longitudinal speed of the vehicle relative to the plurality of ambient terrestrial objects using the measurement system, judging a slippage state of the vehicle using the longitudinal acceleration, and if a result of the judging indicates the vehicle is in a low-slippage state, estimating a coefficient of traction using the rotational speed and the longitudinal speed, wherein the measurement system is structured to radiate electromagnetic energy and to receive reflections of the electromagnetic energy reflected from the plurality of ambient terrestrial objects.

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 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 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 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 longitudinal stiffness estimation system includes an electronic communication system disposed on a vehicle. A sensor is disposed on the vehicle in communication with the electronic communication system, and a processor is accessible through the electronic communication system. The sensor measures parameters associated with the vehicle and communicates data for the parameters to the processor. A mu slip curve generator receives the parameters to generate a mu slip curve in real time from the data. An extraction module extracts raw data from a linear portion of the mu slip curve. A denoising module de-noises the raw data from the mu slip curve by determining a vector for the raw data, an orientation of the vector, and a heading of the vector. The denoising module generates de-noised data, and a stiffness calculator receives the de-noised data and generates a longitudinal stiffness estimate for the tire.

Abstract: An irregular wear detection system for a tire supporting a vehicle includes a sensor unit mounted on the tire. The sensor unit includes a footprint centerline length measurement sensor to measure a centerline length of a footprint of the tire. A processor is in electronic communication with the sensor unit and receives a plurality of measured centerline lengths over time. An analysis module is stored on the processor and receives the measured centerline lengths as inputs. The analysis module detects irregular wear of the tire from the measured footprint centerline lengths. An irregular wear determination is generated by the analysis module when the measured footprint centerline lengths remain the same or increase.

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 load estimation system for a tire is provided. The tire includes a pair of sidewalls extending to a circumferential tread and supports a vehicle. A sensor is mounted to the tire and measures an inflation pressure of the tire and a footprint length of the tread. A vehicle loading state estimator determines a loading state of the vehicle. An inflation correction factor is determined from the vehicle loading state. A pressure correction module receives the measured footprint length, the measured inflation pressure, and the inflation correction factor, and determines an adjusted footprint length. A de-noising module processor receives the adjusted footprint length to generate a filtered footprint length, and a wear correction module receives the filtered footprint length and corrects for wear of the tire to generate a wear-corrected footprint length. A load determination model receives the wear-corrected footprint length and determines an estimated load on the tire.

Abstract: A road condition monitoring system for a vehicle is provided. The vehicle is supported by at least one tire and includes a central communication system. The system includes a processor in electronic communication with the central communication system. An identifier is in electronic communication with the processor, receives vehicle condition data from the central communication system, and identifies a free rolling instance of the at least one tire. A slip estimator is in electronic communication with the processor, receives speed data from the central communication system, and determines slip characteristics of the at least one tire during the free rolling instance. A classifier is in electronic communication with the processor, receives the slip characteristics of the at least one tire, and identifies a road surface condition from the slip characteristics.

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 pressure monitoring system includes a first tire mounted on a first end of an axle and a second tire mounted on a second end of the axle. A first sensor is mounted on the first tire for measuring a pressure, and a second sensor is mounted on the second tire for measuring a pressure. The system includes means for transmitting measured pressure data from the first sensor and the second sensor to a processor. A tire pressure model is executed on the processor, and includes an aggregator that accumulates the measured pressure data from the first sensor and the second sensor. A noise filter filters sensor noise and generates filtered pressure data from the measured tire pressure data. A detection module receives the filtered pressure data and determines when a leak occurs in one of the tires. A leak notification is generated when the leak occurs.

Abstract: A tire replacement forecasting system includes a tire supporting a vehicle. A sensor unit is mounted on the tire and includes a footprint centerline length measurement sensor and a pressure sensor. A processor is in electronic communication with the sensor unit and receives the measured centerline length and the measured pressure. An electronic vehicle network transmits selected vehicle parameters to the processor. A wear state predictor is stored on the processor and receives the measured centerline length, the measured pressure, and the selected vehicle parameters to generate an estimated wear state of the tire. A forecasting model is stored on the processor and receives multiple estimated wear states of the tire, and predicts future wear states of the tire. A forecast tire replacement date is generated by the forecasting model when the predicted future wear states of the tire are estimated to pass a predetermined wear threshold.

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. A tire wear state estimator generates a wear state of the tire and is in electronic communication with the processor. A tire wear rate estimator generates a wear rate of the tire and is in electronic communication with the processor. An antenna transmits 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: An auto-location system locates a position of a tire that supports a vehicle. The system includes a sensor unit that is mounted on the tire and includes a footprint length measurement sensor to measure a length of a footprint of the tire. A processor is in electronic communication with the sensor unit and receives the measured footprint length. A driving event classifier is executed on the processor and employs the measured footprint length to determine the position of the tire on the vehicle. An auto-location output block is executed on the processor and receives the determined position of the tire on the vehicle and generates a message correlating the sensor unit to the position of the tire on the vehicle.

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 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.