Patent Description:
Sensors have been mounted on vehicle tires to monitor certain tire parameters, such as pressure and temperature. Systems that include sensors which monitor tire pressure are often known in the art as tire pressure monitoring systems (TPMS). For example, a tire may have a TPMS sensor that transmits a pressure signal to a processor, which generates a low pressure warning when the pressure of the tire falls below a predetermined threshold. It is desirable that systems including pressure sensors be capable of identifying the specific tire that is experiencing low air pressure, rather than merely alerting the vehicle operator or a fleet manager that one of the vehicle tires is low in pressure.

The process of identifying which sensor sent a particular signal and, therefore, which tire may have low pressure, is referred to as auto-location or localization. Effective and efficient auto-location or localization is a challenge in TPMS, as tires may be replaced, rotated, and/or changed between summer and winter tires, altering the position of each tire on the vehicle. Additionally, power constraints typically make frequent sensor communications and auto-location or localization of signal transmissions impractical.

Prior art techniques to achieve signal auto-location or localization have included various approaches. For example, low frequency (LF) transmitters have been installed in the vicinity of each tire, two-axis acceleration sensors have been employed to recognize a rotation direction of the tire for left or right tire location determination, and methods distinguishing front tires from rear tires using radio frequency (RF) signal strength have been used. The prior art techniques have deficiencies that make location of a sensor mounted in a tire on a vehicle either expensive or susceptible to inaccuracies. In addition, some prior art techniques may be undesirably complex and/or difficult to execute.

Prior art systems are known from <CIT>, <CIT> and <CIT>.

As a result, there is a need in the art for a system that provides economical and accurate identification of the location of a position of a tire on a vehicle.

The invention relates to system in accordance with claim <NUM> and to a method in accordance with claim <NUM>.

According to an aspect of an exemplary embodiment of the invention, an auto-location system for locating a position of a tire supporting a vehicle is provided. The system includes a tire sensor unit that is mounted on the tire. The tire sensor unit includes a footprint length measurement sensor to measure a length of a footprint of the tire, and electronic memory capacity to store identification information for the tire sensor unit. A vehicle sensor unit is mounted on the vehicle and measures a lateral acceleration of the vehicle and a longitudinal acceleration of the vehicle. 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 is executed on the processor, and employs the lateral acceleration and the longitudinal acceleration to estimate a virtual footprint length of the tire. A correlation module is executed on the processor, and receives the virtual footprint length and the measured footprint length to generate correlation values. A decision arbitrator is executed on the processor. The decision arbitrator applies a set of decision rules to the correlation values to generate a wheel position indication that correlates the tire sensor unit to a position of the tire on the vehicle.

"ANN" or "artificial neural network" is an adaptive tool for non-linear statistical data modeling that changes its structure based on external or internal information that flows through a network during a learning phase. ANN neural networks are non-linear statistical data modeling tools used to model complex relationships between inputs and outputs or to find patterns in data.

"CAN bus" is an abbreviation for controller area network.

"Equatorial centerplane" means the plane perpendicular to the tire's axis of rotation and passing through the center of the tread.

"Footprint" means the contact patch or area of contact created by the tire tread with a flat surface as the tire rotates or rolls.

"Tread element" or "traction element" means a rib or a block element defined by a shape having adjacent grooves.

With reference to <FIG>, an exemplary embodiment of an auto-location system <NUM> of the present invention is presented. With particular reference to <FIG>, the system <NUM> locates the position of each tire <NUM> supporting a vehicle <NUM>. The position of each tire <NUM> on the vehicle <NUM> shall be referred to herein by way of example as front left position 12a, front right position 12b, rear left position 12c, and rear right position 12d. While the vehicle <NUM> is depicted as a passenger car, the invention is not to be so restricted. The principles of the invention find application in other vehicle categories, such as commercial trucks, off-the-road vehicles, and the like, in which vehicles may be supported by more or fewer tires than those shown in <FIG>.

The tires <NUM> are of conventional construction, and each tire is mounted on a respective wheel <NUM> as known to those skilled in the art. Each tire <NUM> includes a pair of sidewalls <NUM> that extend to a circumferential tread <NUM>. An innerliner <NUM> is disposed on the inner surface of the tire <NUM>, and when the tire is mounted on the wheel <NUM>, an internal cavity <NUM> is formed, which is filled with a pressurized fluid, such as air.

A tire sensor unit <NUM> is attached to the innerliner <NUM> of each tire <NUM> by means such as an adhesive, and measures certain parameters or conditions of the tire as will be described in greater detail below. It is to be understood that the tire sensor unit <NUM> may be attached in such a manner, or to other components of the tire <NUM>, such as on or in one of the sidewalls <NUM>, on or in the tread <NUM>, on the wheel <NUM>, and/or a combination thereof. For the purpose of convenience, reference herein shall be made to mounting of the tire sensor unit <NUM> on the tire <NUM>, with the understanding that such mounting includes all such types of attachment.

A respective tire sensor unit <NUM> is mounted on each tire <NUM> for the purpose of detecting certain real-time tire parameters, such as tire pressure and tire temperature. For this reason, the tire sensor unit <NUM> preferably includes a pressure sensor and a temperature sensor, and may be of any known configuration. The tire sensor unit <NUM> may be referred to as a tire pressure monitoring system (TPMS) sensor. The tire sensor unit <NUM> preferably also includes electronic memory capacity for storing identification (ID) information for the tire sensor unit, known as sensor ID information <NUM>, which includes a unique identifying number or code for each tire sensor unit. In the art, the phrase tire ID is sometimes used interchangeably with sensor ID information <NUM>, and reference herein shall be made to sensor ID information for the purpose of convenience.

Turning to <FIG>, the tire sensor unit <NUM> (<FIG>) preferably also measures a length <NUM> of a centerline <NUM> of a footprint <NUM> of the tire <NUM>. More particularly, as the tire <NUM> contacts the ground, the area of contact created by the tread <NUM> with the ground is known as the footprint <NUM>. The centerline <NUM> of the footprint <NUM> corresponds to the equatorial centerplane of the tire <NUM>, which is the plane that is perpendicular to the axis of rotation of the tire and which passes through the center of the tread <NUM>. The tire sensor unit <NUM> thus measures the length <NUM> of the centerline <NUM> of the tire footprint <NUM>, which is referred to herein as the measured footprint length <NUM>. Any suitable technique for measuring the measured footprint length <NUM> may be employed by the tire sensor unit <NUM>. For example, the tire sensor unit <NUM> may include a strain sensor or piezoelectric sensor that measures deformation of the tread <NUM> and thus indicates the measured footprint length <NUM>. Preferably, each measured footprint length <NUM> is associated with the sensor ID information <NUM> of the particular tire sensor unit <NUM> that obtained the measured footprint length.

As shown in <FIG>, a vehicle sensor unit <NUM> preferably is mounted on the vehicle <NUM> to measure a lateral acceleration <NUM> of the vehicle and a longitudinal acceleration <NUM> of the vehicle. The vehicle sensor unit <NUM> may include a telematics unit that is equipped with an inertial measurement unit (IMU), which is attached to the vehicle <NUM> to measure the lateral acceleration <NUM> and longitudinal acceleration <NUM>.

With reference to <FIG>, aspects of the auto-location system <NUM> preferably are executed on a processor <NUM>. The processor <NUM> enables input of parameters and execution of specific techniques, to be described below, which are stored in a suitable storage medium and are in electronic communication with the processor. The processor <NUM> may be mounted on the vehicle <NUM>, or may be a remote processor in a cloud-based server <NUM>.

The tire sensor unit <NUM> (<FIG>) preferably includes wireless transmission means <NUM>, such as an antenna, for wirelessly sending the measured footprint length <NUM> and the sensor ID information <NUM> to the processor <NUM>. The vehicle sensor unit <NUM> (<FIG>) preferably also includes wireless transmission means <NUM>, such as an antenna, for wirelessly sending the lateral acceleration <NUM> and the longitudinal acceleration <NUM> to the processor <NUM>.

Output from the auto-location system <NUM> may be wirelessly transmitted by an antenna <NUM> from the processor <NUM> to a display device <NUM>. By way of example, the display device <NUM> may include a device that is accessible to a user of the vehicle <NUM> or a technician for the vehicle, such as a smartphone, and/or a device that is accessible to a fleet manager, such as a computer. Output from the auto-location system <NUM> may also be wirelessly transmitted from the processor <NUM> to an electronic control system <NUM> of the vehicle <NUM>.

Turning to <FIG>, in the auto-location system <NUM>, the measured footprint length <NUM> is transmitted from the tire sensor unit <NUM> to the processor <NUM>, and the lateral acceleration <NUM> and the longitudinal acceleration <NUM> are transmitted from the vehicle sensor unit <NUM> to the processor. The auto-location system <NUM> includes a virtual footprint length estimator <NUM>, a correlation module <NUM>, and a decision arbitrator <NUM> to generate a wheel position indication <NUM>, as will be described in greater detail below.

The footprint length estimator <NUM> is in electronic communication with and is executed on the processor <NUM>. The vehicle acceleration data, including the lateral acceleration <NUM> and the longitudinal acceleration <NUM>, as measured over a predetermined window of time, are electronically communicated or transmitted to the footprint length estimator <NUM>. The footprint length estimator <NUM> employs the lateral acceleration <NUM> and the longitudinal acceleration <NUM> to estimate a virtual footprint length <NUM> of the tire <NUM>.

To estimate the virtual footprint length <NUM>, the footprint length estimator <NUM> executes a vehicle dynamics model <NUM>. The vehicle dynamics model <NUM> receives the lateral acceleration <NUM> and the longitudinal acceleration <NUM> as inputs and generates an estimate of the corresponding lateral and longitudinal load transfer of the vehicle <NUM>, as well as an estimate of a total load <NUM> (<FIG>) at each tire <NUM> of the vehicle <NUM>. Exemplary vehicle dynamics models <NUM> are described in <CIT>; <CIT>; and <CIT>.

With additional reference to <FIG>, once the estimate of the tire load <NUM> is generated, the virtual footprint length <NUM> of each tire <NUM> is generated. Preferably, the virtual footprint length <NUM> is estimated with a regression model <NUM>. In the regression model <NUM>, a predetermined plot <NUM> of footprint length data <NUM> versus tire load data <NUM>, which may be determined from earlier testing, is employed. The estimated tire load <NUM> from the vehicle dynamics model <NUM> is correlated in the plot <NUM> to determine the estimate of the virtual footprint length <NUM>.

Returning to <FIG>, the correlation module <NUM>, which is in electronic communication with and is executed on the processor <NUM>, receives the virtual footprint length <NUM> from the footprint length estimator <NUM> and the measured footprint length <NUM> as measured by the tire sensor unit <NUM>. The correlation module <NUM> correlates a set of virtual footprint lengths <NUM> with a corresponding set of measured footprint lengths <NUM> for each tire <NUM> on the vehicle <NUM>. More particularly, the correlation module <NUM> executes a statistical correlation of the virtual footprint length <NUM> for each of the front left 12a, front right 12b, rear left 12c, and rear right 12d tire positions with the measured footprint lengths <NUM> for each of the front left, front right, rear left, and rear right tire positions.

With additional reference to <FIG>, an exemplary correlation between a plot line <NUM> for the virtual footprint length <NUM> of a tire <NUM> with a plot line <NUM> for the measured footprint length <NUM> of the tire is shown in a correlation plot <NUM>. For a vehicle <NUM> with four (<NUM>) tires <NUM>, sixteen (<NUM>) total correlations preferably are performed, as the virtual footprint length <NUM> for each of the four (<NUM>) positions of front left 12a, front right 12b, rear left 12c, and rear right 12d is correlated with the measured footprint length <NUM> for each of the four (<NUM>) positions. The resulting correlation values <NUM> preferably are stored in a correlation matrix <NUM>, which is stored on and/or is in electronic communication with the processor <NUM>.

Referring to <FIG> and <FIG>, the correlation matrix <NUM> is input into the decision arbitrator <NUM>, which is in electronic communication with and is executed on the processor <NUM>. The decision arbitrator <NUM> includes a set of decision rules <NUM> that are preferably applied in sequence to the correlation values <NUM> of the correlation matrix <NUM> to assign each respective tire sensor unit <NUM> to a tire mounting position of front left 12a, front right 12b, rear left 12c, and rear right 12d on the vehicle <NUM>. As described above, each measured footprint length <NUM> is associated with the sensor ID information <NUM> of the particular tire sensor unit <NUM> that obtained the measured footprint length.

The decision rules <NUM> preferably include a first rule <NUM> that identifies the left side positions 12a, 12c and the right side positions 12b, 12d. The decision arbitrator <NUM> compares the virtual footprint length <NUM> for the front left position 12a and the virtual footprint length for the rear left position 12c to the measured footprint lengths <NUM> in the correlation matrix <NUM>. The measured footprint lengths <NUM> that yield a positive correlation with the virtual footprint length <NUM> for the front left position 12a and the virtual footprint length for the rear left position 12c enables the tire sensor units <NUM> for those measured footprint lengths, through the sensor ID information <NUM>, to be designated as left side positions <NUM>.

The decision arbitrator <NUM> compares the virtual footprint length <NUM> for the front right position 12b and the virtual footprint length for the rear right position 12d to the measured footprint lengths <NUM> in the correlation matrix <NUM>. The measured footprint lengths <NUM> that yield a positive correlation with the virtual footprint length <NUM> for the front right position 12b and the virtual footprint length for the rear right position 12d enables the tire sensor units <NUM> for those measured footprint lengths, through the sensor ID information <NUM>, to be designated as right side positions <NUM>.

The decision rules <NUM> preferably include a second rule <NUM> that differentiates between the front left position 12a and the rear left position 12c. The decision arbitrator <NUM> compares the virtual footprint length <NUM> for the front left position 12a and the virtual footprint length for the rear left position 12c to the measured footprint lengths <NUM> of the designated left side positions <NUM>. The tire sensor unit <NUM>, through the sensor ID information <NUM>, having the maximum correlation value in the Virtual FL row in the correlation matrix <NUM> is designated as the front left position 12a ID1, which is a first estimate for the identification of the tire <NUM> mounted in the front left position. The remaining tire sensor unit <NUM>, through the sensor ID information <NUM>, is designated as the rear left position 12c ID1, which is a first estimate for the identification of the tire <NUM> mounted in the rear left position. In a second estimate, the tire sensor unit <NUM>, through the sensor ID information <NUM>, having the maximum correlation value in the Virtual RL row in the correlation matrix <NUM> is designated as the rear left position 12c ID2. The remaining tire sensor unit <NUM>, through the sensor ID information <NUM>, is designated as the front left position 12a ID2.

If the sensor ID information <NUM> for the tire sensor unit <NUM> designated in the front left position 12a is the same in the first estimate and the second estimate, that tire sensor unit is finally designated as the front left position, and the remaining tire sensor unit is finally designated as the rear left position 12c. If the sensor ID information <NUM> for the tire sensor unit <NUM> designated in the front left position 12a is not the same in the first estimate and the second estimate, a determination is made as to whether a difference between the maximum correlation value and the second highest correlation value in the Virtual FL row in the correlation matrix <NUM> is greater than a difference between the maximum correlation value and the second highest correlation value in the Virtual RL row. If it is greater, the designation of front left position 12a and rear left position 12c from the first estimate is used as the final designation. If it is less or equal, the designation of front left position 12a and rear left position 12c from the second estimate is used as the final designation.

The decision rules <NUM> preferably include a third rule <NUM>, which differentiates between the front right position 12b and the rear right position 12d. The decision arbitrator <NUM> compares the virtual footprint length <NUM> for the front right position 12b and the virtual footprint length for the rear right position 12d to the measured footprint lengths <NUM> of the designated right side positions <NUM>. The tire sensor unit <NUM>, through the sensor ID information <NUM>, having the maximum correlation value in the Virtual FR row in the correlation matrix <NUM> is designated as the front right position 12b ID1, which is a first estimate for the identification of the tire <NUM> mounted in the front right position. The remaining tire sensor unit <NUM>, through the sensor ID information <NUM>, is designated as the rear right position 12d ID1, which is a first estimate for the identification of the tire <NUM> mounted in the rear right position. In a second estimate, the tire sensor unit <NUM>, through the sensor ID information <NUM>, having the maximum correlation value in the Virtual RR row in the correlation matrix <NUM> is designated as the rear right position 12d ID2. The remaining tire sensor unit <NUM>, through the sensor ID information <NUM>, is designated as the front right position 12b ID2.

If the sensor ID information <NUM> for the tire sensor unit <NUM> designated in the front right position 12b is the same in the first estimate and the second estimate, that tire sensor unit is finally designated as the front right position, and the remaining tire sensor unit is finally designated as the rear right position 12d. If the sensor ID information <NUM> for the tire sensor unit <NUM> designated in the front right position 12b is not the same in the first estimate and the second estimate, a determination is made as to whether a difference between the maximum correlation value and the second highest correlation value in the Virtual FR row in the correlation matrix <NUM> is greater than a difference between the maximum correlation value and the second highest correlation value in the Virtual RR row. If it is greater, the designation of front right position 12b and rear right position 12d from the first estimate is used as the final designation. If it is less or equal, the designation of front right position 12b and rear right position 12d from the second estimate is used as the final designation.

The decision rules <NUM> thus identify which tire sensor unit <NUM> is mounted in each respective position of front left 12a, front right 12b, rear left 12c, and rear right 12d on the vehicle <NUM>, which is expressed as the wheel position indication <NUM>. The wheel position indication <NUM> may be transmitted to a display device <NUM> and/or may be transmitted to an electronic control system <NUM> of the vehicle <NUM>, as described above.

In this manner, the auto-location system <NUM> of the present invention employs correlation of a measured footprint length <NUM> as measured by a tire sensor unit <NUM> mounted on each tire <NUM> with an estimated footprint length <NUM> of the tire to identify the position of each tire sensor unit and thus each tire on the vehicle <NUM>. The system <NUM> provides economical and accurate identification of the location of each tire <NUM> on the vehicle <NUM> with an approach that is agnostic as to the vehicle platform and/or tire identification numbers, such as stock keeping unit (SKU) numbers.

The present invention also includes a method for locating the position of a tire <NUM> on a vehicle <NUM>. The method includes steps in accordance with the description that is presented above and shown in <FIG>.

Claim 1:
An auto-location system for locating a position of a tire supporting a vehicle, the system (<NUM>) comprising:
a tire sensor unit (<NUM>) being mounted on the tire (<NUM>), the tire sensor unit (<NUM>) including a footprint length measurement sensor to measure a length of a footprint of the tire, and electronic memory capacity to store identification information for the tire sensor unit (<NUM>);
a vehicle sensor unit (<NUM>) being mounted on the vehicle (<NUM>), the vehicle sensor unit (<NUM>) being configured to measure a lateral acceleration (<NUM>) of the vehicle and a longitudinal acceleration (<NUM>) of the vehicle;
a processor (<NUM>) in electronic communication with the tire sensor unit (<NUM>) and the vehicle sensor unit (<NUM>), the processor (<NUM>) being configured to receive the measured footprint length, the identification information, the lateral acceleration, and the longitudinal acceleration; characterized by
a virtual footprint length estimator (<NUM>) being configured for execution on the processor (<NUM>), the footprint length estimator being configured to employ the lateral acceleration and the longitudinal acceleration to estimate a virtual footprint length (<NUM>) of the tire;
a correlation module (<NUM>) being configured for execution on the processor (<NUM>), the correlation module being configured to receive the virtual footprint length (<NUM>) and the measured footprint length to generate correlation values; and
a decision arbitrator (<NUM>) being configured for execution on the processor (<NUM>), the decision arbitrator being configured to apply a set of decision rules (<NUM>) to the correlation values to generate a wheel position indication (<NUM>) that correlates the tire sensor unit (<NUM>) to a position of the tire (12a, 12b, 12c, 12d) on the vehicle (<NUM>).