Load estimation system for a tire

1 . A load estimation system for a tire, the tire including a pair of sidewalls extending to a circumferential tread and supporting a vehicle, the system comprising:

a sensor being mounted to the tire, wherein the tire is a front tire;

an inflation pressure of the tire being measured by the sensor;

a footprint formed by the tread, the footprint including a footprint length, wherein the footprint length is measured by the sensor;

a processor in electronic communication with the sensor;

a vehicle loading state estimator in electronic communication with the processor and determining a loading state of the vehicle, wherein the vehicle loading state estimator employs the measured inflation pressure and a ratio of the measured footprint length of the front tire to a second footprint length, wherein the second footprint length is a footprint length of a rear tire, and the loading state of the vehicle distinguishes between an empty, half laden, and fully laden vehicle state;

an inflation correction factor for at least one of the front tire and the rear tire being determined from the loading state of the vehicle;

a pressure correction module in electronic communication with the processor, the pressure correction module receiving the measured footprint length, the measured inflation pressure, and the inflation correction factor, wherein the pressure correction module determines an adjusted footprint length;

a de-noising module in electronic communication with the processor, the de-noising module receiving the adjusted footprint length to generate a filtered footprint length;

a wear correction module in electronic communication with the processor, the wear correction module receiving the filtered footprint length and correcting for wear of at least one of the front tire and the rear tire to generate a wear-corrected footprint length;

a load determination model in electronic communication with the processor, the load determination model receiving the wear-corrected footprint length and determining an estimated load on at least one of front tire and the rear tire; and

a vehicle control system in electronic communication with the processor, the vehicle control system receiving the estimated load on at least one of the front tire and the rear tire.

2 . The load estimation system for a tire of claim 1 , wherein the sensor is a front sensor being mounted in the front tire, the inflation pressure is a front inflation pressure, and the measured footprint length is a front footprint length, the system further comprising:

a rear sensor being mounted to the rear tire;

a rear inflation pressure of the rear tire being measured by the rear sensor; and

wherein the rear footprint length is measured by the rear sensor, wherein the vehicle loading state estimator receives the front and rear measured footprint lengths and the front and rear inflation pressures.

3 . The load estimation system for a tire of claim 2 , wherein the vehicle loading state estimator includes a de-noising module receiving the front measured footprint length and the rear measured footprint length, the de-noising module removing signal noise to generate a filtered front footprint length and a filtered rear footprint length.

4 . The load estimation system for a tire of claim 3 , wherein the vehicle loading state estimator includes a ratio estimator that compares the filtered front footprint length to the filtered rear footprint length to determine the ratio.

5 . The load estimation system for a tire of claim 4 , wherein the vehicle loading state estimator includes a vehicle loading state estimation classification model, the vehicle loading state estimation classification model receiving the front inflation pressure, the rear inflation pressure, and the ratio to determine the loading state of the vehicle.

6 . The load estimation system for a tire of claim 5 , wherein the vehicle loading state estimation classification model employs a multinomial logistic regression classification methodology.

7 . The load estimation system for a tire of claim 1 , further comprising:

at least one of a lookup table and a database in electronic communication with the processor; and

an inflation sensitivity being stored in the at least one of the lookup table and the database, the inflation sensitivity being correlated to the vehicle loading state classification, wherein the inflation correction factor is determined from the inflation sensitivity.

8 . The load estimation system for a tire of claim 1 , wherein the de-noising module includes an event filter, the event filter receiving a steering wheel angle of the vehicle from a controlled area network bus of the vehicle to ensure that only footprint length measurements during straight-line travel of the vehicle are analyzed.

9 . The load estimation system for a tire of claim 8 , wherein the de-noising module includes a de-noising algorithm to filter the adjusted footprint length data.

10 . The load estimation system for a tire of claim 9 , wherein the de-noising algorithm includes a recursive least square algorithm with a forgetting factor.

11 . The load estimation system for a tire of claim 9 , wherein the de-noising module includes a smoothing module, the smoothing module receiving the adjusted footprint length from the de-noising algorithm to generate the filtered footprint length.

12 . The load estimation system for a tire of claim 11 , wherein the smoothing module employs an exponential weighted average filter.

13 . The load estimation system for a tire of claim 1 , wherein the wear correction module includes a direct current block filter, the direct current block filter separating a signal for the filtered footprint length into a direct current component that carries a load dependency and a drift component that carries a wear dependency.

14 . The load estimation system for a tire of claim 13 , wherein the wear correction module removes the drift component from the filtered footprint length to generate the wear-corrected footprint length.

15 . The load estimation system for a tire of claim 1 , wherein the wear determination model employs a regression model.

16 . The load estimation system for a tire of claim 15 , wherein the regression model includes a linear regression model.

17 . The load estimation system for a tire of claim 1 , wherein the processor includes at least one of a vehicle-mounted processor and a processor in a cloud-based computing system.

18 . A method for estimating the load of a tire, the tire including a pair of sidewalls extending to a circumferential tread and supporting a vehicle, the method comprising the steps of:

mounting a sensor to the tire, wherein the tire is a front tire;

measuring an inflation pressure of the tire with the sensor;

measuring with the sensor a length of a footprint formed by the tread;

providing a processor in electronic communication with the sensor;

determining a loading state of the vehicle with a vehicle loading state estimator that is in electronic communication with the processor, wherein the vehicle loading state estimator employs the measured inflation pressure and a ratio of the measured footprint length of the front tire to a second footprint length, wherein the second footprint length is a footprint length of a rear tire, and the loading state of the vehicle distinguishes between an empty, half laden, and fully laden vehicle state;

determining an inflation correction factor for at least one of the front tire and the rear tire from the loading state of the vehicle;

determining an adjusted footprint length with a pressure correction module that is in electronic communication with the processor, the pressure correction module receiving the measured footprint length, the measured inflation pressure, and the inflation correction factor;

generating a filtered footprint length with a de-noising module that is in electronic communication with the processor, the de-noising module receiving the adjusted footprint length;

generating a wear-corrected footprint length with a wear correction module that is in electronic communication with the processor, the wear correction module receiving the filtered footprint length;

determining an estimated load on at least one of the front tire and the rear tire with a load determination model that is in electronic communication with the processor, the load determination model receiving the wear-corrected footprint length; and

communicating the estimated load on at least one of the front tire and the rear tire to a vehicle control system in electronic communication with the processor.