Patent Publication Number: US-2022230481-A1

Title: System for auto-location of tires

Description:
FIELD OF THE INVENTION 
     The invention relates generally to tire monitoring systems. More particularly, the invention relates to systems that include sensors mounted on vehicle tires to measure tire parameters. Specifically, the invention is directed to a system for locating the position of a tire on a vehicle employing footprint length as measured by a sensor mounted on the tire. 
     BACKGROUND OF THE INVENTION 
     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 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 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 wheel of the tire, two-axis acceleration sensors have been employed which recognize a rotation direction of the tire for left or right tire location determination, as well as methods distinguishing front tires from rear tires using radio frequency (RF) signal strength. 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. 
     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. 
     SUMMARY OF THE INVENTION 
     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 sensor unit that is mounted on the tire, and which 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. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will be described by way of example and with reference to the accompanying drawings, in which: 
         FIG. 1  is a schematic perspective view of a vehicle that includes a tire employing an exemplary embodiment of the auto-location system of the present invention; 
         FIG. 2  is a plan view of a footprint of the tire shown in  FIG. 1 ; 
         FIG. 3A  is a schematic diagram of aspects of an exemplary embodiment of the auto-location system of the present invention; 
         FIG. 3B  is a schematic diagram of an aspect of the system shown in  FIG. 3A ; 
         FIG. 3C  is a schematic diagram of another aspect of the system shown in  FIG. 3A ; 
         FIG. 3D  is a schematic diagram of another aspect of the system shown in  FIG. 3A ; 
         FIG. 3E  is a schematic diagram of another aspect of the system shown in  FIG. 3A ; 
         FIG. 3F  is a schematic diagram of another aspect of the system shown in  FIG. 3A ; 
         FIG. 3G  is a schematic diagram of another aspect of the system shown in  FIG. 3A ; and 
         FIG. 3H  is a schematic diagram of another aspect of the system shown in  FIG. 3A . 
     
    
    
     Similar numerals refer to similar parts throughout the drawings. 
     Definitions 
     “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. 
     “Axial” and “axially” means lines or directions that are parallel to the axis of rotation of the tire. 
     “CAN bus” is an abbreviation for controller area network. 
     “Circumferential” means lines or directions extending along the perimeter of the surface of the annular tread perpendicular to the axial direction. 
     “Equatorial centerplane (CP)” means the plane perpendicular to the tire&#39;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. 
     “Inboard side” means the side of the tire nearest the vehicle when the tire is mounted on a wheel and the wheel is mounted on the vehicle. 
     “Lateral” means an axial direction. 
     “Outboard side” means the side of the tire farthest away from the vehicle when the tire is mounted on a wheel and the wheel is mounted on the vehicle. 
     “Radial” and “radially” means directions radially toward or away from the axis of rotation of the tire. 
     “Rib” means a circumferentially extending strip of rubber on the tread which is defined by at least one circumferential groove and either a second such groove or a lateral edge, the strip being laterally undivided by full-depth grooves. 
     “Tread element” or “traction element” means a rib or a block element defined by a shape having adjacent grooves. 
     DETAILED DESCRIPTION OF THE INVENTION 
     With reference to  FIGS. 1 through 3H , an exemplary embodiment of an auto-location system of the present invention is indicated at  10 . With particular reference to  FIG. 1 , the system  10  locates the position of each tire  12  supporting a vehicle  14 . The position of each tire  12  shall be referred to herein by way of example as left front  12   a , right front  12   b , left rear  12   c , and right rear  12   d . While the vehicle  14  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, in which vehicles may be supported by more or fewer tires than those shown in  FIG. 1 . 
     The tires  12  are of conventional construction, and each tire is mounted on a respective wheel  16  as known to those skilled in the art. Each tire  12  includes a pair of sidewalls  18  (only one shown) that extend to a circumferential tread  20 . An innerliner  22  is disposed on the inner surface of the tire  12 , and when the tire is mounted on the wheel  16 , an internal cavity  24  is formed, which is filled with a pressurized fluid, such as air. 
     A sensor unit  26  is attached to the innerliner  22  of each tire  12  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 sensor unit  26  may be attached in such a manner, or to other components of the tire  12 , such as on or in one of the sidewalls  18 , on or in the tread  20 , on the wheel  16 , and/or a combination thereof. For the purpose of convenience, reference herein shall be made to mounting of the sensor unit  26  on the tire  12 , with the understanding that such mounting includes all such types of attachment. 
     The sensor unit  26  is mounted on each tire  12  for the purpose of detecting certain real-time tire parameters, such as tire pressure  34  and tire temperature  36 . For this reason, the sensor unit  26  preferably includes a pressure sensor and a temperature sensor, and may be of any known configuration. The sensor unit  26  may be referred to as a tire pressure monitoring system (TPMS) sensor. The sensor unit  26  preferably also includes electronic memory capacity for storing identification (ID) information for the sensor unit mounted in each tire  12 , known as sensor ID information, which includes a unique identifying number or code for each sensor unit. 
     The electronic memory capacity in the sensor unit may also store ID information for each tire  12 , known as tire ID information. Alternatively, tire ID information may be included in another sensor unit, or in a separate tire ID storage medium, such as a tire ID tag, which preferably is in electronic communication with the sensor unit  26 . The tire ID information may be correlated to specific construction data for each tire  12 , including: the tire type; tire model; size information, such as rim size, width, and outer diameter; manufacturing location; manufacturing date; a treadcap code that includes or correlates to a compound identification; and a mold code that includes or correlates to a tread structure identification. 
     As described above, the phrases sensor ID and sensor ID information refer to identification of the tire-mounted sensor unit  26 . The system  10  employs sensor ID and sensor ID information to identify each sensor unit  26 , and analyses data from each sensor unit to determine the location of each respective tire  12  on the vehicle  14 , as will be described in detail below. In the art, the phrase tire ID is sometimes used in connection with identification of the location of each tire  12  on the vehicle  14 . However, as described above, the phrases tire ID and tire ID information as used herein refer to specific construction data for each tire  12 , rather than locating the position of each tire on the vehicle  14 . 
     Turning to  FIG. 2 , the sensor unit  26  ( FIG. 1 ) preferably also measures a length  28  of a centerline  30  of a footprint  32  of the tire  12 . More particularly, as the tire  12  contacts the ground, the area of contact created by the tread  20  with the ground is known as the footprint  32 . The centerline  30  of the footprint  32  corresponds to the equatorial centerplane of the tire  12 , which is the plane that is perpendicular to the axis of rotation of the tire and which passes through the center of the tread  20 . The sensor unit  26  thus measures the length  28  of the centerline  30  of the tire footprint  32 , which is referred to herein as the footprint length  28 . Any suitable technique for measuring the footprint length  28  may be employed by the sensor unit  26 . For example, the sensor unit  26  may include a strain sensor or piezoelectric sensor that measures deformation of the tread  20  and thus indicates the footprint length  28 . 
     The sensor unit  26  may also include an accelerometer for measuring wheel acceleration  38 , and a revolution counter to measure wheel revolution time  40 . It is to be understood that the pressure sensor, the temperature sensor, the sensor ID capacity, the tire ID capacity, the footprint length sensor, the accelerometer, and/or the revolution counter may be incorporated into the single sensor unit  26 , or may be incorporated into multiple units. For the purpose of convenience, reference herein shall be made to a single sensor unit  26 . 
     With reference to  FIG. 3A , the parameters of tire pressure  34 , tire temperature  36 , footprint length  28 , the wheel acceleration  38 , and the wheel revolution time  40  are collectively referred to as sensed parameters  42 . The sensor unit  26  includes wireless transmission means  44 , such as an antenna, for wirelessly sending the sensed parameters  42  to a processor  46 . The processor  46  may be integrated into the sensor unit  26 , or may be a remote processor, which may be mounted on the vehicle  14  or be cloud-based. For the purpose of convenience, the processor  46  will be described as a cloud-based processor, with the understanding that the processor may alternatively be integrated into the sensor unit  26  or mounted on the vehicle  14 . 
     Aspects of the auto-location system  10  preferably are executed on the processor  46 , which enables input of the sensed parameters  42  and execution of specific analysis techniques, to be described below, which are stored in a suitable storage medium and are also in electronic communication with the processor. For preliminary treatment, the sensed parameters  26  are input into a data converter  48 , which processes and normalizes the data from the sensed parameters for analysis. 
     Turning to  FIG. 3B , after the data converter  48 , output data  52  from the sensed parameters  26  are analyzed by an initial assessment module  50  to determine if the incoming data is for an ongoing trip, or if a new trip by the vehicle  14  is in progress  54 . The output data  52  may include, by way of example, tire footprint length  28 , lateral acceleration of the vehicle  14 , longitudinal acceleration of the vehicle, yaw rate of the vehicle, a time stamp, a revolution time of the tire  12 , a vehicle speed from a global positioning system (GPS), a received signal strength indication (RSSI) from each sensor unit  26 , and/or sensor ID information. 
     If the data  52  from the sensed parameters  26  indicates that a new trip by the vehicle  14  is in progress, the system  10  proceeds to an initial system diagnosis module  56 . If the data  52  from the sensed parameters  26  indicates that a new trip by the vehicle  14  is not in progress, an ongoing trip is in progress, and the data is reviewed to determine if new sensor ID detection has been completed  64 . If the new sensor ID detection has not been completed, the system  10  again proceeds to the initial system diagnosis module  56 . If the new sensor ID detection has been completed, the assessment module determines if auto-location for the current trip of the vehicle  14  has already been performed  66 . If auto-location for the current vehicle trip has already been performed, the system  10  proceeds to an auto-location assessment module  68 . If auto-location for the current vehicle trip has not been performed, the system proceeds to a location determination pre-assessment module  70 . 
     Referring to  FIG. 3C , in the initial system diagnosis module  56 , a self-diagnosis of the system  10  is executed. As described in greater detail below, the system  10  is in communication with a cloud-based server  160 , which saves data from the system. The initial system diagnosis module  56  checks for sensor ID information  60  in the saved data. If no sensor ID information is present in the saved data, the module generates a message that sensor ID information is not available  62 . If sensor ID information is detected in the saved data, the system  10  proceeds to an identification review module  72 . 
     As shown in  FIG. 3D , the identification review module  72  detects a new tire  12 . For the detection, the sensor ID information is reviewed for a predetermined period of time  74 . Within the predetermined period of time, the review module  72  receives additional data  76  to continue to review the sensor ID information. When the predetermined period of time has elapsed, the system  10  proceeds to the location determination pre-assessment module  70 . Also when the predetermined period of time has elapsed, the review module  72  determines if the sensor ID information matches previously received and stored sensor identification information  78  associated with the vehicle  14 . 
     If the current sensor ID information matches sensor ID information identified for the vehicle  14  by the identification review module  72  when a previous iteration of the system  10  was running, the review module  72  generates a message that no new sensor ID information was found  80 , as consistent sensor ID information corresponds to each tire  12  remaining in the same location on the vehicle from prior determinations. If the current sensor ID information does not match previously received and stored identification information, the review module  72  generates a message that auto location is being executed  82 , as replacement or repositioning of one or more tires  12  may have occurred. It is to be understood that the system  10  may execute auto-location when the current sensor ID information matches sensor ID information identified for the vehicle  14  by the identification review module  72  when a previous iteration of the system  10  was running, as tire repositioning or rotation on the vehicle may have occurred. 
     Turning to  FIG. 3E , the location determination pre-assessment module  70  verifies if all sensed parameter signals  42  are available  84 . If the sensed parameter signals  42  are not available, the pre-assessment module  70  generates an error message that not all signals are available, so location cannot be performed  86 . If the sensed parameter signals  42  are available, the system  10  proceeds to a sensor ID monitoring module  200 . 
     As shown in  FIG. 3H , the system  10  includes the sensor ID monitoring module  200 . The sensor ID monitoring module  200  compares  202  the most recently received sensor ID information with the sensor ID information from the identification review module  72  ( FIG. 3D ). If the most recently received sensor ID information and the sensor ID information from the identification review module  72  match, the sensor ID information is maintained  204 . If the most recently received sensor ID information and the sensor ID information from the identification review module  72  do not match, the most recently received sensor ID information is added to the stored data as described above, and the sensor ID information from the identification review module  72  that does not match the most recently received sensor ID information is removed or dropped  206 . After the sensor ID information is compared in the sensor ID monitoring module, the system  10  proceeds to a location determination module  88 . 
     Referring to  FIG. 3F , the location determination module  88  executes a driving event classifier  90 . The driving event classifier  90  determines from the sensed parameters  42  and the output data  52 , such as the lateral acceleration of the vehicle  14 , the longitudinal acceleration of the vehicle, and the yaw rate of the vehicle, whether the vehicle is traveling straight and at a steady speed, referred to as cruising  92 . If the vehicle is traveling straight and at a steady speed, the data is labeled as cruising  94 , which enables the determination of a mean footprint length  28 . When the vehicle is cruising, the driving event classifier  90  checks whether a predetermined number of cruising events has been met  96 . If so, a mean footprint length  28  for each tire  12  is determined  98 . If the predetermined number of cruising events has not been met, the driving event classifier  90  waits for additional sensed parameters  42  to be received  100 . 
     If the vehicle is not traveling straight and at a steady speed, the driving event classifier  90  determines, based on the sensed parameters  42 , whether the vehicle  14  is accelerating  102 . If the vehicle  14  is accelerating, the sensed parameters  42  are designated as acceleration data  104 . The driving event classifier  90  then checks whether a predetermined number of acceleration events has been met  106 . If the predetermined number of acceleration events has not been met, the driving event classifier  90  waits for additional sensed parameters  42  to be received  108 . If the predetermined number of acceleration events has been met, the determined mean footprint length  98  is input into an acceleration-based auto-locator  110 . 
     In the acceleration-based auto-locator  110 , the front tire positions  12 A and  12 B are distinguished from the rear tire positions  12 C and  12 D. More particularly, when the vehicle  14  accelerates, there is typically a load transfer from the front tires  12 A and  12 B to the rear tires  12 C and  12 D. This load transfer results in a positive change or gain in the footprint length  28  for the rear tires  12 C and  12 D relative to the mean footprint length, and a negative change or reduction in the footprint length for the front tires  12 A and  12 B relative to the mean footprint length. This positive change in the footprint length  28  for the rear tires  12 C and  12 D and negative change in the footprint length for the front tires  12 A and  12 B enables the front tires to be distinguished from the rear tires. Once the front tires  12 A and  12 B are distinguished from the rear tires  12 C and  12 D, the relative front and rear positions are sent to an acceleration output block  112 . 
     If the vehicle  14  is not accelerating, the driving event classifier  90  determines, based on the sensed parameters  42 , whether the vehicle  14  is braking  114 . If the vehicle  14  is braking, the sensed parameters  42  are designated as braking data  116 . The driving event classifier  90  checks whether a predetermined number of braking events has been met  118 . If the predetermined number of braking events has not been met, the driving event classifier  90  waits for additional sensed parameters  42  to be received  120 . If the predetermined number of braking events has been met, the determined mean footprint length  98  is input into a braking-based auto-locator  122 . 
     In the braking-based auto-locator  122 , the front tire positions  12 A and  12 B are distinguished from the rear tire positions  12 C and  12 D. When the vehicle  14  brakes, there is typically a load transfer from the rear tires  12 C and  12 D to the front tires  12 A and  12 B. This load transfer results in a positive change or gain in the footprint length  28  for the front tires  12 A and  12 B relative to the mean footprint length, and a negative change or reduction in the footprint length for the rear tires  12 C and  12 D relative to the mean footprint length. This positive change in the footprint length  28  for the front tires  12 A and  12 B and negative change in the footprint length for the rear tires  12 C and  12 C enables the front tires to be distinguished from the rear tires. Once the front tires  12 A and  12 B are distinguished from the rear tires  12 C and  12 D, the relative front and rear positions are sent to a braking output block  124 . 
     If the vehicle  14  is not braking, the driving event classifier  90  determines, based on the sensed parameters  42 , whether the vehicle is executing a right turn  126 . If the vehicle  14  is executing a right turn, the sensed parameters  42  are designated as right turn data  128 . The driving event classifier  90  then checks whether a predetermined number of right turn events has been met  130 . If the predetermined number of right turn events has not been met, the driving event classifier  90  waits for additional sensed parameters  42  to be received  132 . If the predetermined number of right turn events has been met, the determined mean footprint length  98  is input into a right turn based auto-locator  134 . 
     In the right turn based auto-locator  134 , the left tire positions  12 A and  12 C are distinguished from the right tire positions  12 B and  12 D. More particularly, when the vehicle  14  executes a right turn, there is lateral load transfer from the inside or right side tires  12 B and  12 D to the outside or left side tires  12 A and  12 C. This load transfer results in a positive change or gain in the footprint length  28  for the left side tires  12 A and  12 C relative to the mean footprint length, and a negative change or reduction in the footprint length for right side tires  12 B and  12 D relative to the mean footprint length, which enables the left side tires to be distinguished from the right side tires. 
     In addition, during turning of the vehicle  14 , each outer wheel turns  16  slower than the inner wheel. The speed difference between the wheel revolution time  40  (TREV) for each tire  12  and the speed of the vehicle  14  is expected to be positive for the tires on the outer wheels  16  and negative for the tires on the inner wheels, further enabling the left side tires  12 A and  12 C to be distinguished from the right side tires  12 B and  12 D. Once the left side tires  12 A and  12 C are distinguished from the right side tires  12 B and  12 D, the relative left and right positions are sent to a right turn output block  136 . 
     If the vehicle  14  is not executing a right turn, the driving event classifier  90  determines, based on the sensed parameters  42 , whether the vehicle is executing a left turn  138 . If the vehicle  14  is executing a left turn, the sensed parameters  42  are designated as left turn data  140 . The driving event classifier  90  then checks whether a predetermined number of left turn events has been met  142 . If the predetermined number of left turn events has not been met, the driving event classifier  90  waits for additional sensed parameters  42  to be received  144 . If the predetermined number of left turn events has been met, the determined mean footprint length  98  is input into a left turn based auto-locator  146 . 
     In the left turn based auto-locator  146 , the left tire positions  12 A and  12 C are distinguished from the right tire positions  12 B and  12 D. When the vehicle  14  executes a left turn, there is lateral load transfer from the inside or left side tires  12 A and  12 C to the outside or right side tires  12 B and  12 D. This load transfer results in a positive change or gain in the footprint length  28  for the right side tires  12 B and  12 D relative to the mean footprint length, and a negative change or reduction in the footprint length for left side tires  12 A and  12 C relative to the mean footprint length, which enables the left side tires to be distinguished from the right side tires. 
     In addition, during turning, the speed difference between the wheel revolution time  40  (TREV) for each tire  12  and the speed of the vehicle  14  is expected to be positive for the tires on the outer wheels  16  and negative for the tires on the inner wheels, further enabling the left side tires  12 A and  12 C to be distinguished from the right side tires  12 B and  12 D. Once the left side tires  12 A and  12 C are distinguished from the right side tires  12 B and  12 D, the relative left and right positions are sent to a left turn output block  148 . 
     If the vehicle  14  is not executing a left turn, the driving event classifier  90  labels the sensed parameters  42  as a non-event  150 , and the data are not used as inputs for auto-location based on footprint length  28  and TREV  40  methodology. 
     Optionally, the driving event classifier  90  may include a received signal strength indicator (RSSI) auto-locator  152 . For example, when a vehicle-based processor or receiver is employed, it may be placed closer to the rear tires  12 C and  12 D than the front tires  12 A and  12 B. In such a case, the signal received from the sensor unit  26  in each of the rear tires  12 C and  12 D will be stronger than the strength of the signal received from the sensor unit in each of the front tires  12 A and  12 B, enabling the front tires to be distinguished from the rear tires. Once the front tires  12 A and  12 B are distinguished from the rear tires  12 C and  12 D, the relative front and rear positions are sent to an RSSI output block  154 . 
     The front tire position data  12 A and  12 B and the rear tire position data  12 C and  12 D from the acceleration output block  112 , the front tire position data and the rear tire position data from the braking output block  124 , the left side tire position data and the right side tire position data from the right turn output block  136 , the left side tire position data and the right side tire position data from the left turn output block  148 , and optionally, the front tire position data and the rear tire position data from the RSSI output block  154 , are sent to a combined auto-location mapping function  156 . The combined auto-location mapping function  156  executes a comparison between the data from all of the output blocks, isolating the front tires  12 A and  12 B from the rear tires  12 C and  12 D, and the left tires from the right tires. In this manner, the position of each respective front left tire  12 A, front right tire  12 B, rear left tire  12 C and rear right tire  12 D is identified. 
     The identification of the position of respective front left tire  12 A, front right tire  12 B, rear left tire  12 C and rear right tire  12 D locations is output from the combined auto-location mapping function  156  to an auto-location output block  158 . The output block  158  generates a message correlating each sensor unit  26 , and thus its sensed parameters, to a respective front left tire  12 A, front right tire  12 B, rear left tire  12 C and rear right tire  12 D location. 
     Returning to  FIG. 3A , the identified location or positions of each sensor unit  26  and its respective tire  12 A,  12 B,  12 C and  12 D is transmitted from the output block  158  to a cloud-based server  160 . The cloud-based server  160  may be in electronic communication with control systems of the vehicle  14 , a fleet management device, or a vehicle operator device. In this manner, the parameters sensed by each sensor unit  26  may be correlated to each respective tire  12 A,  12 B,  12 C and  12 D for use in vehicle control systems, a fleet manager, and/or an operator of the vehicle  14 . 
     With reference to  FIG. 3G , the auto-location assessment module  68  provides an analysis of historical data to ensure a satisfactory level of statistical confidence is achieved by the system  10 . Location data as determined above, along with sensed parameter data  42 , is input from the cloud-based server  160  into the assessment module  68 . The assessment module  68  employs statistical tests to determine the level of statistical confidence reached by the system  10 . An example of a statistical test that may be employed is an inferential statistical analysis, which is referred to as a T-test. 
     For example, an acceleration T-test  162  employs the change in footprint length  28  as described above from the acceleration data  104  to compare footprint-length based position determinations  112  for the front left tire  12 A versus the rear left tire  12 C, the front left tire versus the rear right tire  12 D, the front right tire  12 B versus the rear left tire, and the front right tire versus the rear right tire. The T-test  162  outputs a confidence value or level  164 . The output confidence value  164  is compared to a predetermined threshold value  166 . If the confidence value  164  is less than the threshold, the assessment module  68  generates a message that the auto-location confidence threshold of the system  10  has been achieved  168 . If the confidence value  164  is not less than the threshold, the assessment module  68  generates a message that the auto-location confidence threshold of the system  10  has not been achieved  170 . 
     A braking-based T-test  172  employs the change in footprint length  28  as described above from the braking data  116  to compare footprint-length based position determinations  124  for the front left tire  12 A versus the rear left tire  12 C, the front left tire versus the rear right tire  12 D, the front right tire  12 B versus the rear left tire, and the front right tire versus the rear right tire. The T-test  172  outputs a confidence value or level  174 . The output confidence value  174  is compared to a predetermined threshold value  176 . If the confidence value  174  is less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has been achieved  168 . If the confidence value  174  is not less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has not been achieved  170 . 
     A right-turn based T-test  178  employs labeled data points from the right turn data  128  to compare right turn determinations  136 , including the change in footprint length  28  and the speed difference based determinations described above for the front left tire  12 A versus the front right tire  12 B and the rear left tire  12 C versus the rear right tire  12 D. The T-test  178  outputs a confidence value or level  180 . The output confidence value  180  is compared to a predetermined threshold value  182 . If the confidence value  180  is less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has been achieved  168 . If the confidence value  180  is not less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has not been achieved  170 . 
     A left-turn based T-test  184  employs labeled data points from the left turn data  140  to compare left turn determinations  148 , including the change in footprint length  28  and the speed difference based determinations described above for the front left tire  12 A versus the front right tire  12 B and the rear left tire  12 C versus the rear right tire  12 D. The T-test  184  outputs a confidence value or level  186 . The output confidence value  188  is compared to a predetermined threshold value  190 . If the confidence value  188  is less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has been achieved  168 . If the confidence value  188  is not less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has not been achieved  170 . 
     An RSSI-based T-test  190  employs the RSSI determinations  154  to compare position determinations for the front left tire  12 A versus the rear left tire  12 C, the front left tire versus the rear right tire  12 D, the front right tire  12 B versus the rear left tire, and the front right tire versus the rear right tire. The T-test  190  outputs a confidence value or level  192 . The output confidence value  192  is compared to a predetermined threshold value  194 . If the confidence value  192  is less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has been achieved  168 . If the confidence value  192  is not less than the threshold, the assessment module  68  generates the message that the auto-location confidence threshold of the system  10  has not been achieved  170 . 
     In this manner, the auto-location system  10  of the present invention employs sensed parameters  42 , including the tire footprint length  28 , to identify and locate the position of each tire  12  on a vehicle  14 . As described above, the auto-location system  10  generates notifications when a newly mounted tire  12  on the vehicle  14  is detected, accompanied by the tire location or mounting position. The system  10  also generates notifications when a mounting position or location of a tire  12  has been changed, such as in a tire rotation procedure, accompanied by the new tire position or location. The system  10  provides economical and accurate identification of the location of each tire  12  on the vehicle  14  with self-diagnosis, and optionally includes an assessment module  68  that analyzes historical data to ensure a satisfactory level of statistical confidence is achieved by the system. 
     The present invention also includes a method for locating the position of a tire  12  on a vehicle  14 . The method includes steps in accordance with the description that is presented above and shown in  FIGS. 1 through 3H . 
     It is to be understood that the structure and method of the above-described auto-location system may be altered or rearranged, or components or steps known to those skilled in the art omitted or added, without affecting the overall concept or operation of the invention. For example, electronic communication may be through a wired connection or wireless communication without affecting the overall concept or operation of the invention. Such wireless communications include radio frequency (RF) and Bluetooth® communications. 
     The invention has been described with reference to a preferred embodiment. Potential modifications and alterations will occur to others upon a reading and understanding of this description. It is to be understood that all such modifications and alterations are included in the scope of the invention as set forth in the appended claims, or the equivalents thereof.