Tire pressure monitoring system sensor level based vehicle auto-location

Abstract

Embodiments included herein are directed towards a method, computer program product, and computing system for tire pressure monitoring. Embodiments of the present disclosure may include receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors. Embodiments may further include comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location. Embodiments may also include distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model. Embodiments may further include determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer.

Description

Tire Pressure Monitoring System Sensor Level Based Vehicle Auto-LocationCross-Reference to Related Applications

[0001] The present application claims the benefit of U.S. Provisional Patent Application No. 63 / 625,328, entitled “Tire Pressure Monitoring System Sensor Level Based Vehicle Auto-Location”, filed on 26 January 2024. The entire disclosure of which is incorporated herein by reference.Technical Field

[0002] The present disclosure generally applies to monitoring systems, more specifically a system and method for a tire pressure monitoring system.Background

[0003] In tire pressure monitoring systems, performing auto-location of a wheel is needed for a number of reasons. Tire pressure monitoring systems generally include a sensor in or at each wheel of a vehicle and a central controller which receives tire pressure information from each sensor, to be reported to the driver of the vehicle. Autolocation is the identification of each sensor and determination of its position on the vehicle, automatically and without human intervention. Auto-location may be done initially upon installation and subsequently in the event of tire rotation or replacement. Performing auto-location involves determining the identity or serial number of a tire pressure monitoring system (TPMS) sensor in each of the wheels in the car. In premium vehicles, knowing the identity of the TPMS sensor in each wheel allows a pressure by position display to be implemented and shown to the driver. In base vehicles with different placard tire pressures for front and rear axles, it is desirable to know TPMS sensor identities and positions in order to check pressure against a correct threshold for an applicable axle.

[0004] In most countries, it is mandatory for passenger car vehicles to have the TPMS to alert the driver of under inflated tires. The purpose of this is to inform the driver of an unsafe operating mode relating to one, or all of the tires on the vehicle. Each sensor that is installed in the wheels has a unique identification code associated with it, which enables the pressure values for each wheel to be displayed on the dashboard. If the identification code for each sensor may be associated with a comer of the vehicle, then the vehicle original equipment manufacturer (“OEM”) may implement a ‘pressure by position’ display. The functionality of auto-location for all TPMS sensors requires some level of exterior data in addition to that available at a sensor level to create system level solution. Current auto-location solutions require partnership with OEMs to provide a system level solution for the auto-location of the TPMS. The most widely used technology requires correlation of the sensors to angle of wheels using antilock brake system (ABS) and ultimately involves an integration effort.Summary of the Disclosure

[0005] As will be discussed in greater detail below, embodiments of the present disclosure include a tire pressure monitoring system.

[0006] In one or more embodiments of the present disclosure, a method, computer program product, and computing system associated with a tire pressure monitoring system (“TPMS”) is included. The method may include receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors. The method may further include comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location. The method may also include distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model. The method may further include determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer.

[0007] One or more of the following features may be included. In some embodiments, the method may include determining a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model. In some embodiments, the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data. The method may further include using the direction of rotation of all the TPMS sensors on the vehicle to distinguish near-side information leading to a full system level solution being obtained from the sensor level. The method may further include using the direction of rotation of all the TPMS sensors on the vehicle to distinguish off-side information leading to a full system level solution being obtained from the sensor level. In some embodiments, the algorithm for autolocation at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors. In some embodiments, the algorithm for auto-location being independent of an antilock brake system (ABS) and any specific requirement on a placement of a receiver in the TPMS.

[0008] In another embodiment of the present disclosure, a non-transitory computer readable storage medium having stored thereon instructions, which when executed by a processor result in one or more operations is provided. Operations may include receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors. The operations may further include comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location. The operations may also include distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model. The operations may further include determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer.

[0009] One or more of the following features may be included. In some embodiments, the operation may further include determining a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model. In someembodiments, the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data. In some embodiments, the operation may further include using the direction of rotation of all the TPMS sensors on the vehicle to distinguish near-side information leading to a full system level solution being obtained from the sensor level. In some embodiments, the operation may further include using the direction of rotation of all the TPMS sensors on the vehicle to distinguish off-side information leading to a full system level solution being obtained from the sensor level. In some embodiments, the algorithm for auto-location at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors. In some embodiments, the algorithm for auto-location being independent of an antilock brake system (ABS) and any specific requirement on a placement of a receiver in the TPMS.

[0010] In one or more embodiments of the present disclosure, a TPMS is provided. The TPMS may include a receiver, an antilock brake system (ABS) with a plurality of ABS sensors, an Electronic Control Unit (ECU) including a processor and a storage, and a plurality of wheel units. The ECU is coupled to the plurality of ABS sensors. At least one wheel unit includes: a microcontroller, a battery, a transponder coil, a sensor interface, a pressure sensor, a wheel phase angle sensor, a transmitter, a sensor accelerometer, and an antenna. The microcontroller is coupled to the sensor interface and the sensor interface is coupled to the wheel phase angle sensor. The processor is configured to receive amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors. The processor is further configured to compare and monitor relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location. The processor is further configured to distinguish a front of a vehicle from a rear of the vehicle based on a statistical model. The processor is further configured to determine a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from the sensor accelerometer.

[0011] One or more of the following features may be included. In some embodiments, the processor is further configured to determine a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model. In some embodiments, the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data. In some embodiments, the processor is further configured to use the direction of rotation of all the TPMS sensors on the vehicle to distinguish near-side information leading to a full system level solution being obtained from the sensor level. In some embodiments, the processor is further configured to use the direction of rotation of all the TPMS sensors on the vehicle to distinguish off-side information leading to a full system level solution being obtained from the sensor level. In some embodiments, the algorithm for auto-location at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors. In some embodiments, the algorithm for auto-location being independent of the ABS and any specific requirement on a placement of the receiver in the TPMS.

[0012] The details of one or more example implementations are set forth in the accompanying drawings and the description below. Other possible example features and / or possible example advantages will become apparent from the description, the drawings, and the claims. Some implementations may not have those possible example features and / or possible example advantages, and such possible example features and / or possible example advantages may not necessarily be required of some implementations.

[0013] This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.Brief Description of the Drawings

[0014] The accompanying drawings, which are included to provide a further understanding of embodiments of the present disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the present disclosure and together with the description serve to explain the principles of embodiments of the present disclosure.

[0015] FIG. 1 illustrates one embodiment of a tire pressure monitoring system in accordance with embodiments of the present disclosure;

[0016] FIG. 2 illustrates one embodiment of a wheel unit for use with the tire pressure monitoring system in accordance with embodiments of the present disclosure;

[0017] FIG. 3A illustrates an example of a time difference between forward and reverse motion of a four wheeled vehicle in accordance with embodiments of the present disclosure;

[0018] FIG. 3B illustrates a table showing the time difference in accordance with embodiments of the present disclosure;

[0019] FIG. 4 illustrates a flowchart in accordance with embodiments of the present disclosure;

[0020] Like reference symbols in the various drawings may indicate like elements.Detailed Description

[0021] The discussion below is directed to certain implementations. It is to be understood that the discussion below is only for the purpose of enabling a person with ordinary skill in the art to make and use any subject matter defined now or later by the patent “claims” found in any issued patent herein.

[0022] It is specifically intended that the claimed combinations of features not be limited to the implementations and illustrations contained herein, but include modified forms of those implementations including portions of the implementations and combinations of elements of different implementations as come within the scope of the following claims. It should be appreciated that in the development of any such actualimplementation, as in any engineering or design project, numerous implementationspecific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. Nothing in this application is considered critical or essential to the claimed invention unless explicitly indicated as being "critical" or "essential."

[0023] It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first object or step could be termed a second object or step, and, similarly, a second object or step could be termed a first object or step, without departing from the scope of the invention. The first object or step, and the second object or step, are both objects or steps, respectively, but they are not to be considered a same object or step.

[0024] In commercial vehicles, there is a continual need in the TPMS market for increasing the life of the system to reduce down time and increase the effectiveness of this important safety system by remembering when to check tires and an additional comfort measure in safety. The purpose of this is to inform the driver of an unsafe operating mode relating to one, or all of the tires on the vehicle.

[0025] The present invention is directed to a method, computer program product, and computing system associated with a tire pressure monitoring system (“TPMS”). The functionality of auto-location for all TPMS sensors requires some level of exterior data in addition to that available at a sensor level to create system level solution. Current auto-location solutions require partnership with OEMs to provide a system level solution for the auto-location of the TPMS. The most widely used technologyrequires correlation of the sensors to angle of wheels using antilock brake system (ABS) and ultimately involves an integration effort.

[0026] One or more embodiments of the present invention provide solution which negates the requirement to be used with that system. In accordance with various embodiments of the present invention, the auto-location solutions of the TPMS utilize the information available at a sensor and a communication between the sensors to create a standalone auto-location solution at a sensor level for the TPMS. In some embodiments, an algorithm is used to monitor and compare the relative amplitude and phase differences of radio-frequency (RF) signals between all TPMS sensors. A statistical model is built up by determining a positive or negative doppler shift and a vehicle speed to determine a front from a rear of the vehicle. In some embodiments, this information may be coupled with sensor accelerometer data which gives a direction of rotation of all the TPMS sensors on the vehicle which may be used to distinguish near-side or off-side information leading to a full system level solution being obtained at the sensor level of the TPMS.

[0027] In some embodiments, the algorithm being hosted at the sensor level negating a need for any system level processing of the data, minimizing any system level integration effort required. In accordance with various embodiments of the present invention, this solution for auto-location of the TPMS provides an independence from a requirement of partnership with OEMs to provide the system level solution, thus minimizing integration costs and also lending itself more readily to retro-fit solutions.

[0028] FIG. 1 illustrates a tire pressure monitoring system (“TPMS”) 100 according to a first embodiment of the present disclosure, which may be in communication, in whole or in part, with the network. TPMS 100 may be arranged in a standard vehicle 1 having four wheels. Four wheels include a front left wheel (FL), a front right wheel (FR), a rear left wheel (RL) and a rear right wheel (RR). In another embodiment, TPMS 100 may be arranged in any other vehicle having a different number of wheels. TPMS100 may include wheel units 101, 102, 103 and 104 that may be associated with each wheel of vehicle 1.

[0029] In some embodiments, TPMS 100 may further include an antilock brake system (ABS) (not shown in FIG. 1) with four ABS sensors 201, 202, 203 and 204. ABS sensors 201-204 may also be associated with each wheel of vehicle 1. Accordingly, each wheel may be assigned with one of wheel units 101, 102, 103 and 104 and one of ABS sensors 201, 202, 203 and 204.

[0030] In some embodiments, TPMS 100 may also include an Electronic Control Unit (ECU) 300 and a receiver 400. ECU 300 may be coupled to ABS sensors 201-204 via a communication bus such as a Controller Area Network (CAN) bus and may receive ABS data from ABS sensors 201-204. ECU 300 may include processor 302 and storage 304. ECU 300 operates to store received ABS data in storage 304 to provide a historic ABS trace. ECU 300 may be implemented by any suitable means, for example a microprocessor, microcontroller, an Application Specific Integrated Circuit (ASIC), or other suitable data processing device programmed to perform the functions described herein. Further, ECU 300 may communicate with other vehicle components using any other suitable device, either wire line or wireless. The CAN bus is an exemplary implementation of data communication among components of the vehicle.

[0031] In some implementations, as will be discussed below in greater detail, the TPMS 100 of FIG. 1, may include but is not limited to, receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors. Relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors may be compared and monitored based on an algorithm for autolocation. A front of a vehicle may be distinguished from a rear of the vehicle based on a statistical model. A direction of rotation of all the TPMS sensors on the vehicle may be determined based on information received from the statistical model coupled with data from a sensor accelerometer. The sensor level comparison may not require to beconfined to the vehicle, but may also be provided as a cloud, app based level or equivalent.

[0032] In some embodiments, ECU 300 may also receive data from wheel units 101, 102, 103 and 104 via receiver 400. For example, wheel units 101, 102, 103 and 104 transmit radio frequency or other wireless communications conveying data and other information to ECU 300. The respective wheel units may include a suitable radio transmission circuit and ECU 300 includes a suitable radio reception circuit for radio communication. Further, the radio circuits may use an agreed upon transmission and reception format and data encoding technique. ECU 300 operates to correlate the data received from wheel units 101, 102, 103 and 104 with the AB S data in order to perform auto-location, as will be discussed in detail below.

[0033] Referring to FIG. 2, the structure of wheel unit 101 is illustrated in more detail. Wheel units 102-104 may incorporate the same structure as that of wheel unit 101. As shown in FIG. 2, wheel unit 101 includes a microcontroller 220, a battery 210, a transponder coil 206, a sensor interface 207, a pressure sensor 208, a wheel phase angle sensor 212, a transmitter 214 and an antenna 216. Microcontroller 220 is coupled to sensor interface 207. Sensor interface 207 is coupled to wheel phase angle sensor 212. Wheel phase angle sensor 212 measures a wheel phase angle at multiple different times. Wheel phase angle sensor 212 provides measurements to sensor interface 207. Sensor interface 207 may receive the measurements of wheel phase angle sensor 212 in the form of an electrical output signal. Sensor interface 207 may receive the electrical output signal and amplifies and filters the signal. Sensors mounted in each wheel of the vehicle constantly measure a tire’s pressure and, if mounted inside the tire, its temperature. This information is transmitted wirelessly to sensor interface 207 and displayed by either an in-cab display or a technician’s hand-held device during maintenance checks. Sensor interface 207 may send the processed signal to an analog to digital converter (not shown) in order to convert the signal into a digital signal.Microcontroller 220 may receive the digital form of the output signal from wheel phase angle sensor 212 for processing.

[0034] In the illustrated embodiment, pressure sensor 208 may detect the pneumatic air pressure of the tire with which wheel unit 101 is associated. In alternative embodiments, pressure sensor 208 may be supplemented with or replaced by a temperature sensor or other devices for detecting tire data. An indication of the tire pressure data is sent to microcontroller 220 via the analog-to-digital converter (not shown).

[0035] In some embodiments, battery 210 may be a power source of wheel unit 101. Transponder coil 206 may detect external activation of the transponder by a signal applied by a remote exciter and may modulate a signal to communicate data to a remote detector from wheel unit 101. Wheel unit 101 may provide data including tire pressure from the pressure sensor 208 and the wheel phase angle information from wheel phase angle sensor 212 through transmitter 214 and antenna 216 to ECU 300 (as shown in FIG. 1).

[0036] In operation, upon rotation of a wheel, wheel phase angle sensor 212 may operate to measure a wheel phase angle. The wheel phase angle measurements may not have to be against an absolute reference. In other words, the phase measurements do not have to be measured from a top of wheel, or road striking point. The key piece of information may be a phase difference, or a phase delta of the wheel, and therefore, the requirement is that two different phase angles are measured relative to the same angle. The reference may be arbitrarily selected based on accuracy capability and ease of implementation. Wheel phase angle sensor 212 may be mounted on a rim of the wheel, or a tire mounted sensor. Alternatively, or additionally, wheel phase angle sensor 212 may be arranged on any suitable location associated with a wheel. In one embodiment, wheel phase angle 212 includes a rotation sensor. For example, the rotation sensor may be a piezoelectric rotation sensor which measures a wheel phase angle based on the gravitational force. Specifically, as the wheel rotates, the gravitational force causes asensing element of the rotation sensor to experience different forces which results in a different output signal representing a wheel phase angle or wheel angular position. In that way, the rotation sensor produces an output signal indicating a wheel phase angle at a predetermined time. The output signal of the rotation sensor may have different amplitude and / or different polarity depending on the wheel phase angle. For instance, the rotation sensor produces the output signal having amplitude M at 0 degree and having the amplitude -M at 180 degree. Alternatively, or additionally, any conventional rotation sensor may be used as wheel phase angle sensor 212.

[0037] In another embodiment, wheel phase angle sensor 212 comprises a shock sensor of the type that produces an electrical signal in response to acceleration. The electrical signal is indicative of, or typically proportional to, the experienced change in acceleration. Alternatively, wheel phase angle sensor 212 may each comprise an accelerometer or a micro-electromechanical systems (MEMS) sensor. The main difference between an accelerometer and a shock sensor is that the output signal from a shock sensor is related to a change of force applied to the shock sensor, whereas the output signal from an accelerometer is proportional to the absolute force applied.

[0038] Referring also to FIGs. 1 and 2, in most countries, it is mandatory for passenger car vehicles to have a tire pressure monitoring system to alert the driver of under inflated tires. The purpose of this is to inform the driver of an unsafe operating mode relating to one, or all of the tires on the vehicle. Each sensor that is installed in the wheels may include a unique identification code associated with it, which enables the pressure values for each wheel to be displayed on the dashboard. If the identification code for each sensor can be associated with a comer of the vehicle, then the vehicle OEM can implement a ‘pressure by position’ display as described above.

[0039] However, a problem may arise if the wheels on the vehicle are swapped. If the vehicle ECU has no way of knowing that this has happened, then the warning given to the driver may be indicating issues with the wrong wheel position. The issues related to this particular problem may be addressed using auto-location system solutions suchas wheel unit auto-location (“WAL”) and phase auto-location (“PAL”). In some embodiments, TPMS 100 may have traditionally used ultra-high frequency (“UHF”) RF systems transmitting in 315 and 433 MHz ISM bands to transfer the auto-location data from the sensor to the vehicle ECU. In some other embodiments, OEMs are now beginning to move to Bluetooth based systems to achieve further integration of the TPMS, remote keyless entry (“RKE”) systems, Passive Entry Passive Start (“PEPS”), and entertainment systems.

[0040] Bluetooth Low Energy (BLE) is one of the most common short range wireless standards in use today and is available across many products and industries, including computing, mobile, health and fitness and automotive. As the automotive industry moves towards wireless vehicle architectures that use BLE, new methods are required for manufacturing and service processes. While aspects of the present disclosure may discuss certain communication protocols, such as BLE, it should be noted that any suitable communication protocol may be used with out departing from the scope of the present disclosure.

[0041] Auto-location systems, such as PAL, may correlate the wheel unit angular information with the vehicle ABS data and the system must have knowledge of the elapsed time from the wheel unit being located at a pre-determined angular position and the vehicle ECU receiving the auto-location data from the wheel unit. Typically, this auto-location data may be included as a time value encoded into the RF frame and may include all system delays up to the point of the RF frame being received at the vehicle ECU.

[0042] Referring now to FIG. 3 A, an example 350 of a time difference between forward and reverse motion of a four wheeled vehicle in accordance with embodiments of the present disclosure is shown. For example, as shown in FIG. 1, TPMS 100 may be arranged in the four wheels of the vehicle (e.g., vehicle 1) which may include the front left wheel (FL) with sensor 2, the front right wheel (FR) with sensor 4, the rear left wheel (RL) with sensor 1 and the rear right wheel (RR) with sensor 3. In anotherembodiment, TPMS 100 may be arranged in any other vehicle having a different number of wheels. In some embodiments, the auto-location solutions of the TPMS utilize the information available at the sensor (e.g. sensor 1, sensor 2, sensor 3 and sensor 4 shown in FIG. 3A and ABS sensors 201-204, pressure sensor 208 and wheel phase angle sensor 212 shown in FIG. 1) and a communication between the TPMS sensors (e.g., sensor 1, sensor 2, sensor 3 and sensor 4 shown in FIG. 3 A and ABS sensors 201-204, pressure sensor 208 and wheel phase angle sensor 212 shown in FIG. 1) to create a standalone auto-location solution at a sensor level for TPMS 100. For example, the information may include the time difference between forward and reverse motions (t = AT) (bidirectional) of the vehicle with respect to the vehicle when at stationary (t = 0) for all the TPMS sensors (e.g. sensor 1, sensor 2, sensor 3 and sensor 4 shown in FIG. 3A and ABS sensors 201-204, pressure sensor 208 and wheel phase angle sensor 212 shown in FIG. 1).

[0043] In some embodiments, when vehicle 1 is stationary at t=0, a distance between sensor 1 and sensor 2 (similarly between sensor 3 and sensor 4) is D and a distance between sensor 2 and sensor 4 (similarly between sensor 2 and sensor 4) is W. In some embodiments, an algorithm is used to monitor and compare the relative amplitude and phase differences of radio-frequency (RF) signals between all TPMS sensors. For example, a rear of vehicle 1 may be determined by determining the reverse motions of sensor 1, sensor 2, sensor 3 and sensor 4 of vehicle 1 moving at a speed v m / s at time t = AT for a distance D+ v* AT. Similarly, a front of vehicle 1 may be determined by determining the forward motions of sensor 1, sensor 2, sensor 3 and sensor 4 of vehicle 1 moving at a speed v m / s at time t = AT for a distance D+ v* AT. In some embodiments, a statistical model is built up by determining a positive or negative doppler shift and a vehicle speed to determine the front from the rear of vehicle 1.

[0044] Referring now to FIG. 3B, a table 360 gives an overview of the physical differences expected between the forward and reverse motions (bidirectional) of thevehicle illustrated as the time difference in accordance with embodiments of the present disclosure. Table 360 illustrates the information available at sensor 1, sensor 2, sensor 3 and sensor 4, shown in FIG. 3 A, and the communication among sensor 1, sensor 2, sensor 3 and sensor 4 for vehicle 1 when stationary at t=0, for vehicle 1 in forward motion at t = AT and for vehicle 1 in reverse motion at t = AT. For example, while observing communication between the TPMS sensors with respect to sensor 2 in the transmitter and sensor 1 in the receiver of vehicle 1 during the forward motion, a negative Doppler shift may be determined, as shown in table 360. Similarly, for example, while observing communication between the TPMS sensors with respect to sensor 4 in the transmitter and sensor 3 in the receiver of vehicle 1 during the reverse motion, a positive Doppler shift may be determined, as shown in table 360. In some embodiments, these information may be coupled with sensor accelerometer data which gives a direction of rotation of all the TPMS sensors on the vehicle which may be used to distinguish near-side or off-side information leading to a full system level solution being obtained at the sensor level of TPMS 100. In some embodiments, this solution may not require any system level integration work. The solution may be independent of the ABS and may not impose any specific requirement on the placement of the RF receiver (e.g., receiver 400) in TPMS 100.

[0045] Referring now to FIG. 4, a flowchart illustrating a method, computer program product, and computing system associated with TPMS 100 in accordance with embodiments of the present disclosure is shown. In some embodiments, an autolocation functionality of TPMS 100 may require some level of exterior data in addition to that available at a sensor level of TPMS 100 and utilizes the information available at the one or more TPMS sensors and a communication between the TPMS sensors to create a standalone auto-location solution at the sensor level. A method 400 may include receiving (402) amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors (e.g., ABS sensors 201-204, pressure sensor 208 and wheel phase angle sensor 212).

[0046] In some embodiments, the method 400 may further include comparing and monitoring (404) relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors (e.g., ABS sensors 201-204, pressure sensor 208 and wheel phase angle sensor 212) based on an algorithm for auto-location. In some embodiments, the algorithm for auto-location being hosted at a sensor level (406) negating a need for any system level processing of data and thus may not require any system level integration work. For example, the algorithm may require logging the repeated phases and amplitudes over a (or multiple) drive(s) and building confidence against the anticipated results of FIG. 3B. As more data is received, it builds a higher statistical confidence for the algorithm that the wheels may be allocated the correct position. In some other embodiments, the algorithm for auto-location being independent of the ABS (e.g., ABS with ABS sensors 201-204) (408) and any specific requirement on a placement of a receiver (e.g., receiver 400) in the TPMS (e.g., TPMS 100).

[0047] In some embodiments, the method 400 may also include distinguishing (410) a front of a vehicle (e.g., vehicle 1 ) from a rear of the vehicle based on a statistical model. In some embodiments, the method 400 may further include determining (412) a positive or a negative doppler shift and a vehicle speed may be determined in order to build up the statistical model. For example, the algorithm for auto-location may be designed to monitor and compare the relative amplitude and phase differences of the RF signals between all TPMS sensors, determining the positive or negative doppler shift and vehicle speed in order to build up a statistical model to determine the front from the rear of the vehicle, as shown in FIG. 3A. In some other embodiments, the statistical model may be updated using artificial intelligence (Al) or machine learning (ML) as these technologies mature.

[0048] In some embodiments, the method 400 may further include determining (414) a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer. In some embodiments, the method 400 may include using (416) thedirection of rotation of all the TPMS sensors on the vehicle to distinguish near-side or off-side information leading to a full system level solution being obtained from the sensor level.

[0049] For example, the information obtained from the statistical model may be coupled with the data from the sensor accelerometer which provides the direction of rotation of all the TPMS sensors on the vehicle which may be used to distinguish the near-side or off-side information leading to the full system level solution being obtained from the sensor level. For example, the amplitude / phase difference obtained from the data from the sensor accelerometer may tell the relative position of the sensors with respect to each other, but the algorithm needs some method of identifying the near-side or off-side information when the vehicle is moving forward from reverse. In accordance with various embodiments of the present invention, this solution for auto-location of the TPMS provides an independence from a requirement of partnership with OEMs to provide the system level solution, thus minimizing integration costs and also lending itself more readily to retro-fit solutions.

[0050] The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting of the disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, ft will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0051] The corresponding structures, materials, acts, and equivalents of means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present disclosure has been presented for purposes of illustration and description, but is not intended to be exhaustive orlimited to the disclosure in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the disclosure. The embodiments were chosen and described in order to best explain the principles of the disclosure and the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.

[0052] Although a few example embodiments have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the example embodiments without materially departing from the scope of the present disclosure, described herein. Accordingly, such modifications are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Thus, although a nail and a screw may not be structural equivalents in that a nail employs a cylindrical surface to secure wooden parts together, whereas a screw employs a helical surface, in the environment of fastening wooden parts, a nail and a screw may be equivalent structures. It is the express intention of the applicant not to invoke 35 U.S.C. § 112, paragraph (f) for any limitations of any of the claims herein, except for those in which the claim expressly uses the words ‘means for’ or 'step for' together with an associated function.

[0053] Having thus described the disclosure of the present application in detail and by reference to embodiments thereof, it will be apparent that modifications and variations are possible without departing from the scope of the disclosure defined in the appended claims.

Claims

What Is Claimed Is:

1. A computer- implemented method in a tire pressure monitoring system (“TPMS”), comprising: receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors; comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location; distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model; and determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer.

2. The method of claim 1, further comprising: determining a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model.

3. The method of claim 1, wherein the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data.

4. The method of claim 3, further comprising: using the direction of rotation of all the TPMS sensors on the vehicle to distinguish near-side information leading to a full system level solution being obtained from the sensor level.

5. The method of claim 3, further comprising:using the direction of rotation of all the TPMS sensors on the vehicle to distinguish off-side information leading to a full system level solution being obtained from the sensor level.

6. The method of claim 3, wherein the algorithm for auto-location at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors.

7. The method of claim 1, wherein the algorithm for auto-location being independent of an antilock brake system (ABS) and any specific requirement on a placement of a receiver in the TPMS.

8. A non-transitory computer readable storage medium having stored thereon instructions, which when executed by a processor result in one or more operations, the operations comprising: receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors; comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location; distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model; and determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from a sensor accelerometer.

9. The non-transitory computer readable storage medium of claim 8, further comprising determining a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model.

10. The non-transitory computer readable storage medium of claim 8, wherein the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data.

11. The non-transitory computer readable storage medium of claim 10, further comprising using the direction of rotation of all the TPMS sensors on the vehicle to distinguish near-side information leading to a full system level solution being obtained from the sensor level.

12. The non-transitory computer readable storage medium of claim 10, further comprising using the direction of rotation of all the TPMS sensors on the vehicle to distinguish off-side information leading to a full system level solution being obtained from the sensor level.

13. The non-transitory computer readable storage medium of claim 10, wherein the algorithm for auto-location at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors.

14. . The non-transitory computer readable storage medium of claim 8, wherein the algorithm for auto-location being independent of an antilock brake system (ABS) and any specific requirement on a placement of a receiver in the TPMS.

15. A tire pressure monitoring system (“TPMS”) comprising:a receiver; an antilock brake system (ABS) with a plurality of ABS sensors; an Electronic Control Unit (ECU) including a processor and a storage, wherein the ECU is coupled to the plurality of ABS sensors; and a plurality of wheel units, wherein at least one wheel unit includes: a microcontroller; a battery; a transponder coil; a sensor interface; a pressure sensor; a wheel phase angle sensor; a transmitter; a sensor accelerometer; and an antenna, wherein the microcontroller is coupled to the sensor interface and the sensor interface is coupled to the wheel phase angle sensor, and wherein the processor is configured to: receiving amplitude and phase differences of a plurality of radiofrequency (RF) signals between one or more TPMS sensors; comparing and monitoring relative amplitude and phase differences of the plurality of RF signals among all TPMS sensors based on an algorithm for auto-location; distinguishing a front of a vehicle from a rear of the vehicle based on a statistical model; and determining a direction of rotation of all the TPMS sensors on the vehicle based on information received from the statistical model coupled with data from the sensor accelerometer.

16. The system of claim 15, wherein the processor is further configured to determine a positive or a negative doppler shift and a vehicle speed in order to build up the statistical model.

17. The system of claim 15, wherein the algorithm for auto-location being hosted at a sensor level negating a need for any system level processing of data.

18. The system of claim 17, wherein the processor is further configured to use the direction of rotation of all the TPMS sensors on the vehicle to distinguish nearside and off-side information leading to a full system level solution being obtained from the sensor level.

19. The system of claim 17, wherein the algorithm for auto-location at the sensor level utilizes information available from at least one TPMS sensor and communication between the one or more TPMS sensors20. The system of claim 15, wherein the algorithm for auto-location being independent of the ABS and any specific requirement on a placement of the receiver in theTPMS.

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