US 12,220,946 B2
Tire replacement forecasting system and method
Kanwar Bharat Singh, Lorenztweiler (LU); and Mustafa Ali Arat, Ettelbruck (LU)
Assigned to The Goodyear Tire & Rubber Company, Akron, OH (US)
Filed by The Goodyear Tire & Rubber Company, Akron, OH (US)
Filed on Apr. 13, 2022, as Appl. No. 17/719,410.
Claims priority of provisional application 63/208,025, filed on Jun. 8, 2021.
Prior Publication US 2022/0388348 A1, Dec. 8, 2022
Int. Cl. B60C 11/24 (2006.01); B60C 23/04 (2006.01); B60W 40/105 (2012.01); G07C 5/08 (2006.01)
CPC B60C 11/246 (2013.01) [B60C 23/0486 (2013.01); B60W 40/105 (2013.01); G07C 5/0816 (2013.01); B60W 2520/105 (2013.01); B60W 2520/125 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A tire replacement forecasting system comprising:
a vehicle;
a tire supporting the vehicle;
a sensor unit being mounted on the tire, the sensor unit including:
a footprint centerline length measurement sensor to measure a centerline length of a footprint of the tire; and
a pressure sensor to measure a pressure of the tire;
a processor in electronic communication with the sensor unit, the processor receiving the measured centerline length and the measured pressure;
an electronic vehicle network transmitting selected vehicle parameters to the processor;
a wear state predictor being stored on the processor and receiving the measured centerline length, the measured pressure, and the selected vehicle parameters as inputs, the wear state predictor generating an estimated wear state of the tire from the inputs, wherein the wear state predictor includes:
a normalization module, the normalization module applying a pressure scaling factor to the centerline length measurement to generate a normalized footprint centerline length;
a median estimator, the median estimator receiving multiple normalized footprint centerline lengths and calculating a median of the normalized footprint centerline lengths;
a scaling module, the scaling module rescaling an initial value of the normalized footprint centerline lengths to a standard value and generating scaled footprint centerline lengths;
an exponential moving average calculator, the exponential moving average calculator generating exponentially weighted footprint centerline lengths from the scaled footprint centerline lengths; and
a wear state model receiving the exponentially weighted footprint centerline lengths and generating the estimated wear state of the tire;
a forecasting model being stored on the processor and receiving as inputs multiple estimated wear states of the tire from the wear state predictor, the forecasting model predicting future wear states of the tire; and
a forecast tire replacement date being generated by the forecasting model when the predicted future wear states of the tire are estimated to pass a predetermined wear threshold.