Tire vibration and loose wheel detection

Abstract

The present disclosure provides "Tire Vibration and Loose Wheel Detection". A vehicle computer includes a memory and a processor, the processor being programmed to execute instructions stored in the memory. The instructions include: receiving a wheel speed from a wheel speed sensor; receiving a vehicle speed from a vehicle speed sensor; determining an average vibration amplitude based on the wheel speed and the vehicle speed; and detecting a vibrating wheel based on the average vibration amplitude.

Description

Technical Field

[0001] The present invention relates to in-situ vehicle tires, and more particularly to vehicle tire vibration and loose wheel detection. Background Art

[0002] The Society of Automotive Engineers (SAE) has defined several levels of autonomous vehicle operation. At Levels 0-2, the human driver monitors or controls most driving tasks, typically without assistance from the vehicle. For example, at Level 0 (“Autonomous”), the human driver is responsible for all vehicle operations. At Level 1 (“Driver Assisted”), the vehicle may sometimes assist with steering, acceleration, or braking, but the driver is still responsible for the vast majority of vehicle control. At Level 2 (“Partial Automation”), the vehicle may control steering, acceleration, and braking in certain situations without human interaction. At Levels 3-5, the vehicle takes on more driving-related tasks. At Level 3 (“Conditional Automation”), the vehicle may handle steering, acceleration, and braking in certain situations, as well as monitoring the driving environment. However, Level 3 requires the driver to intervene occasionally. At Level 4 (“High Automation”), the vehicle may handle the same tasks as Level 3, but does not rely on driver intervention for certain driving modes. At Level 5 (“Full Automation”), the vehicle may handle almost all tasks without any driver intervention. Summary of the invention

[0003] In a vehicle, excessive tire vibration may occur when one or more of the bolts that secure the tire to the vehicle chassis become loose. Tire vibration may also occur in other situations, such as when the wheel is unbalanced. Human drivers can usually feel when a tire is vibrating excessively. However, excessive tire vibration is less obvious to the virtual driver system of an autonomous vehicle.

[0004] A vehicle computer having a memory and a processor, the processor being programmed to execute instructions stored in the memory, the vehicle computer being capable of detecting tire vibration and loose wheels. The instructions stored in the memory include: receiving wheel speed from a wheel speed sensor; receiving vehicle speed from a vehicle speed sensor; determining an average vibration amplitude based on the wheel speed and the vehicle speed; and detecting a vibrating wheel based on the average vibration amplitude.

[0005] In the vehicle computer, the processor may be programmed to identify a speed range based on the vehicle speed. In this case, the processor may be programmed to estimate the wheel radius through the wheel speed sensor. In addition, the processor may be programmed to select a frequency segment of interest based on the speed range and the estimated wheel radius. In addition, the processor may be programmed to generate an intermediate signal of the wheel based on the wheel speed and the selected frequency segment of interest. The processor may be further programmed to determine the intermediate vibration amplitude based at least in part on the intermediate signal.

[0006] In the vehicle computer, the processor may be programmed to recursively determine the average vibration amplitude.

[0007] In the vehicle computer, the processor may be programmed to detect the vibrating wheel by comparing the average vibration amplitude to a threshold value. In this case, the processor may be programmed to detect the vibrating wheel as a result of determining that the average vibration amplitude exceeds the threshold value.

[0008] In the vehicle computer, the processor may be programmed to autonomously operate the host vehicle according to remedial measures as a result of detecting the vibrating wheel.

[0009] A method includes receiving a wheel speed from a wheel speed sensor; receiving a vehicle speed from a vehicle speed sensor; determining an average vibration amplitude based on the wheel speed and the vehicle speed; and detecting a vibrating wheel based on the average vibration amplitude.

[0010] The method may further include identifying a speed range based on the vehicle speed. In this case, the method may further include estimating a wheel radius by the wheel speed sensor. The method may further include selecting a frequency segment of interest based on the speed range and the estimated wheel radius. The method may further include generating an intermediate signal for the wheel based on the wheel speed and the selected frequency segment of interest. The method may further include determining the intermediate vibration amplitude based at least in part on the intermediate signal.

[0011] The method may further include determining the average vibration amplitude includes recursively determining the average vibration amplitude.

[0012] The method may further include: detecting the vibrating wheel includes comparing the average vibration amplitude to a threshold value. In this case, the method may further include: detecting the vibrating wheel because it is determined that the average vibration amplitude exceeds the threshold value.

[0013] The method may also include autonomously operating the host vehicle according to remedial action as a result of detecting the vibrating wheel. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 An exemplary autonomous vehicle with tire vibration and loose wheel detection is shown.

[0015] Figure 2 is a block diagram illustrating exemplary components of an autonomous vehicle for detecting tire vibrations and loose wheels.

[0016] Figure 3 is a block diagram illustrating tire vibration detection.

[0017] Figure 4is a block diagram illustrating loose wheel detection.

[0018] Figure 5 is a flow chart of an example process for tire vibration and loose wheel detection. DETAILED DESCRIPTION

[0019] The illustrated elements may take many different forms and include multiple and / or alternative components and facilities. The exemplary components illustrated are not intended to be limiting. In practice, additional or alternative components and / or implementations may be used. Furthermore, unless so explicitly stated, the illustrated elements are not necessarily drawn to scale.

[0020] like Figure 1 and Figure 2 As shown, the autonomous host vehicle 100 includes a virtual driver system 105, an automated vehicle platform 110, a wheel speed sensor 115, and a vehicle speed sensor 120. At least some portions of the virtual driver system 105 may be implemented by a vehicle computer. Although shown as a sedan, the host vehicle 100 may be any passenger or commercial vehicle, such as a car, a truck, a SUV hybrid, a van, a minivan, a taxi, a bus, etc. As described in more detail below, the host vehicle 100 is an autonomous vehicle that can operate in an autonomous (e.g., unmanned) mode, a partially autonomous mode, and / or a non-autonomous mode.

[0021] The virtual driver system 105 is a computing platform implemented via sensors, controllers, circuits, chips, and other electronic components that controls various autonomous operations of the host vehicle 100. The virtual driver system 105 includes an autonomous vehicle controller 125 implemented via circuits, chips, or other electronic components and programmed to process data captured by sensors 130, which may include lidar sensors, radar sensors, cameras, ultrasonic sensors, etc. The autonomous vehicle controller 125 is programmed to output control signals to components of the automated vehicle platform 110 to autonomously control the host vehicle 100 based on the data captured by the sensors.

[0022] The automated vehicle platform 110 refers to a component that performs autonomous vehicle operations according to instructions from the virtual driver system 105, specifically from the autonomous vehicle controller 125. As such, the automated vehicle platform 110 includes various actuators 135 incorporated into the host vehicle 100 to control the steering, propulsion, and braking of the host vehicle 100. Each actuator 135 is controlled by a control signal output by the autonomous vehicle controller 125. The actuator 135 can convert an electrical control signal into a mechanical motion that causes a steering wheel, an accelerator pedal, a brake pedal, etc. to move. Examples of the actuator 135 include linear actuators, servo motors, etc. The automated vehicle platform 110 also includes various platform controllers (sometimes referred to as "modules" in the art), such as a chassis controller, a powertrain controller, a body controller, an electric controller, etc.

[0023] The wheel speed sensors 115 are implemented via circuits, chips, or other electronic components that are programmed to measure the rotational speed of the wheels of the host vehicle 100. Each wheel speed sensor 115 may be associated with one of the wheels, and as such, each wheel speed sensor 115 may be programmed to measure the rotational speed of its corresponding wheel. The wheel speed sensors 115 may be programmed to calculate the wheel speed based on, for example, the number of times the wheel rotates within a particular time period. Thus, the units of wheel speed may be rotations per unit time. The wheel speed sensors 115 may be programmed to output their respective wheel speed measurements to the autonomous vehicle controller 125.

[0024] The vehicle speed sensor 120 is implemented via a circuit, chip, or other electronic component programmed to measure the speed of the host vehicle 100. In some cases, the vehicle speed sensor 120 may be programmed to calculate or measure the speed of the host vehicle 100 relative to the speed of the drive shaft. Alternatively or in addition, the vehicle speed may be determined based on GPS data, for example, based on the distance traveled by the vehicle in a specific time period. The unit of the vehicle speed may be the distance traveled per unit time. The vehicle speed sensor 120 may be programmed to output the vehicle speed to the autonomous vehicle controller 125. In some cases, the vehicle speed sensor 120 is incorporated into the autonomous vehicle controller 125. That is, the autonomous vehicle controller 125 may be programmed to calculate the vehicle speed based on, for example, the number of drive shaft rotations, GPS data, etc.

[0025] The autonomous vehicle controller 125 is implemented via a circuit, chip, or other electronic component including a memory 140 and a processor 145. The memory 140 is implemented via a circuit, chip, or other electronic component, and may include one or more of the following: a read-only memory (ROM), a random access memory (RAM), a flash memory, an electrically programmable memory (EPROM), an electrically programmable and erasable memory (EEPROM), an embedded multimedia card (eMMC), a hard disk drive, or any volatile or non-volatile medium, etc. The memory 140 may store instructions executable by the processor 145 and data such as data output by the wheel speed sensor 115, the vehicle speed sensor 120, the threshold values ​​discussed below, etc. The instructions and data stored in the memory 140 may be accessed by the processor 145 and possibly other components of the host vehicle 100. The processor 145 is implemented via a circuit, chip, or other electronic component, and may include one or more microcontrollers, one or more field programmable gate arrays (FPGAs), one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more user-specific integrated circuits, etc. As a result of the programming of processor 145, autonomous vehicle controller 125 receives data from wheel speed sensors 115 and vehicle speed sensors 120, among others, and determines from the data whether one or more tires of host vehicle 100 are vibrating excessively, one or more wheels are loose, or both.

[0026] Autonomous vehicle controller 125 may be programmed to determine whether a tire is vibrating excessively and whether a wheel is loose based at least in part on certain entry conditions. An entry condition refers to a condition under which autonomous vehicle controller 125's decisions regarding tire vibration and loose wheels are more likely to be accurate. Examples of entry conditions may include low yaw (e.g., host vehicle 100 is generally traveling in a straight line), host vehicle 100 is accelerating or traveling at a relatively constant speed (e.g., brakes are not applied), vehicle speed exceeds a certain threshold, etc.

[0027] Figure 3 3 is a block diagram 300 showing how the processor 145 of the autonomous vehicle controller 125 may be programmed to determine if a tire is vibrating excessively. The autonomous vehicle controller 125 is programmed to determine if certain entry conditions exist. The entry conditions that the autonomous vehicle controller 125 considers for detecting excessive tire vibration may include determining if the vehicle yaw is approximately zero (which would indicate that the host vehicle 100 is traveling in a straight line) and determining that the host vehicle 100 is not decelerating (e.g., the brakes are not applied). If both entry conditions exist, the autonomous vehicle controller 125 may proceed to determine if one or more tires are vibrating excessively.

[0028] At block 305 , autonomous vehicle controller 125 may determine whether the speed of host vehicle 100 is within a particular range. Autonomous vehicle controller 125 may do this by receiving the output of vehicle speed sensor 120 and identifying a speed range associated with the output of vehicle speed sensor 120 .

[0029] At block 310, autonomous vehicle controller 125 may select a frequency segment of interest. The selected frequency segment of interest may be a function of vehicle speed. In addition, each frequency segment may be composed of a minimum frequency f min and the maximum frequency f max to define.

[0030] At block 315, autonomous vehicle controller 125 may calculate the vibration amplitude of each tire. That is, autonomous vehicle controller 125 may receive the wheel speed output by each wheel speed sensor 115, the vehicle speed output by vehicle speed sensor 120, the frequency bin of interest determined at block 310, and the entry condition. Calculating the vibration amplitude of each tire may be performed in stages. One stage may include recursively calculating the intermediate signal s(n), as shown in Equation 1,

[0031] s(n)=x(n)+2cos(ω0)s(n-1)-s(n-2) (1)

[0032] Where x(n) is the wheel speed sequence x(0), ... x(N-1). The second stage may include applying a filter to s(n) to produce an output sequence y(n), as shown in Equation 2.

[0033]

[0034] The transfer function can be defined as:

[0035]

[0036] The output y(n) in the time domain can be defined as:

[0037]

[0038] The power spectrum can be defined as follows. First, define

[0039]

[0040] Where k is the frequency bin of interest, leading to Equation 6.

[0041]

[0042] The power spectrum of the wheel speed signal x(n) at the frequency of interest is given by:

[0043] |X(k)| 2=|Y(N-1)| 2 =y(N-1)y′(N-1) (7)

[0044] because

[0045]

[0046] Therefore, the vibration amplitude can be calculated using Equation 8.

[0047]

[0048] Autonomous vehicle controller 125 can be programmed to calculate the magnitude of the vibration approximately, for example, every 2 seconds when the vehicle speed is within a range of, for example, 5 mph, since those vehicle speeds will have the same frequency bin of interest. Furthermore, with this approach, the range is determined based on the instantaneous vehicle speed, and autonomous vehicle controller 125 can be programmed to detect excessive tire vibration based on a recursive average. The wheel vibration signal from Equation 8 is output to block 320.

[0049] At box 320, autonomous vehicle controller 125 compares the wheel vibration signal to a threshold. If the vibration of one or more wheels exceeds the threshold, autonomous vehicle controller 125 is programmed to set a flag indicating excessive (or abnormal) tire vibration. Setting the flag may include setting a diagnostic trouble code. Autonomous vehicle controller 125 may be further programmed to take another action, such as presenting an alert in host vehicle 100, selecting a minimum risk condition event, etc. Minimum risk condition events may include autonomously operating host vehicle 100 to pull over, stop in a lane, or go to a service station.

[0050] Figure 4 is a block diagram 400 illustrating how to program the processor 145 of the automatic vehicle controller 125 to detect a loose wheel.

[0051] At block 405, autonomous vehicle controller 125 identifies a speed range. That is, autonomous vehicle controller 125 is programmed to receive the vehicle speed from vehicle speed sensor 120 and determine the minimum vehicle speed V and the minimum vehicle speed V respectively based on the instantaneous vehicle speed. smin and maximum vehicle speed V smax .

[0052] At block 410 , autonomous vehicle controller 125 performs an online estimation of wheel radius. Autonomous vehicle controller 125 may perform an online estimation of wheel radius r for each wheel of host vehicle 100. w Online estimation of the wheel radius can be calculated according to the following equation 9:

[0053]

[0054] Where V s is the instantaneous vehicle speed in miles per hour, Ws is the wheel speed in radians per second, and r w is the wheel radius in meters.

[0055] At block 415, autonomous vehicle controller 125 selects a frequency segment of interest. The frequency segment of interest may be selected based on the speed range determined at block 405 and the wheel radius determined at block 410. The frequency segment of interest may be selected by a minimum frequency range f min and the maximum frequency range f max Equations 10 and 11 define the frequency f in the selected frequency bin.

[0056] A min ≤f≤f max (10)

[0057]

[0058] At box 420, autonomous vehicle controller 125 calculates the vibration amplitude of each wheel. The vibration amplitude may be a function of the selected frequency, the vehicle speed measured by wheel speed sensor 115, and entry conditions, including whether the brakes are being applied and the vehicle yaws. For example, autonomous vehicle controller 125 may generate an intermediate signal s(n) for each vehicle speed and selected frequency bin according to equations 1 and 5 above, and wherein the selected frequency bin k is defined as follows:

[0059]

[0060] As shown in Equation 8 above, autonomous vehicle controller 125 may determine the magnitude of vibration for each tire given the result of Equation 1 for each tire. Using the magnitude of vibration for each tire, autonomous vehicle controller 125 may calculate a recursive average of the vibration magnitudes using data corresponding to entry conditions (e.g., the vehicle is traveling in a straight line and the brakes are not applied). When a new vibration magnitude Mag is added i+1 When , the recursive mean can be calculated as follows:

[0061]

[0062] Autonomous vehicle controller 125 may output the average vibration value for each wheel as a result of block 420 .

[0063] At box 425, the autonomous vehicle controller 125 compares the vibration average output at box 420 to a threshold value indicating a loose wheel. The threshold value may be stored in the memory 140. If the vibration average value exceeds the threshold value, the autonomous vehicle controller 125 is programmed to set a flag indicating excessive (or abnormal) tire vibration indicating a loose wheel. Setting the flag may include setting a diagnostic trouble code. The autonomous vehicle controller 125 may be further programmed to take another action, such as presenting an alarm in the host vehicle 100, selecting a minimum risk condition event, etc. The minimum risk condition event may include autonomously operating the host vehicle 100 to pull over, stop in a lane, or go to a service station.

[0064] Figure 5 A flow chart is shown of an exemplary process 500 that may be performed by the host vehicle 100 to detect excessive tire vibration and a loose wheel.

[0065] At block 505, autonomous vehicle controller 125 receives vehicle speed. Vehicle speed may be received by processor 145 of autonomous vehicle controller 125 from, for example, vehicle speed sensor 120.

[0066] At block 510 , autonomous vehicle controller 125 receives the wheel speed of each wheel of host vehicle 100 . The wheel speed may be output by, for example, wheel speed sensor 115 and received by processor 145 of autonomous vehicle controller 125 .

[0067] At block 515 , autonomous vehicle controller 125 identifies a speed range. The speed range may be identified via processor 145 of autonomous vehicle controller 125 , as explained above with respect to block 405 .

[0068] At block 520 , autonomous vehicle controller 125 estimates the wheel radius. Processor 145 of autonomous vehicle controller 125 estimates the wheel radius as explained above with respect to block 410 .

[0069] At block 525 , autonomous vehicle controller 125 selects the frequency segment of interest. Processor 145 of autonomous vehicle controller 125 may select the frequency segment of interest as explained above with respect to block 415 .

[0070] At block 530, autonomous vehicle controller 125 determines the magnitude of the tire vibrations. Processor 145 of autonomous vehicle controller 125 may determine the magnitude of the tire vibrations using a Goertzel-based calculation, as described above with respect to Figure 3 and as discussed in block 420.

[0071] At block 535, autonomous vehicle controller 125 compares the magnitude of the tire vibration obtained from block 530 with a predetermined threshold. That is, processor 145 of autonomous vehicle controller 125 may make such a comparison as explained above with respect to block 425.

[0072] At decision block 540, autonomous vehicle controller 125 determines whether the magnitude of any of the tire vibrations exceeds a threshold. Processor 145 may achieve this by comparing the magnitude of each tire vibration to a threshold. If the tire vibrations exceed the threshold, process 500 may proceed to block 545, as vibrations exceeding the threshold may indicate a loose wheel. Otherwise, process 500 may return to block 505.

[0073] At box 545, the autonomous vehicle controller 125 sets a flag and takes remedial action. For example, the processor 145 of the autonomous vehicle controller 125 may set a diagnostic trouble code flag and may also initiate a minimal risk condition event. The minimal risk condition event may include autonomously operating the host vehicle 100 to pull over, stop in a lane, or navigate to a service station.

[0074] In general, the computing systems and / or devices described may employ any of a number of computer operating systems, including but not limited to Ford Version and / or variant of the application, AppLink / Smart Device Link middleware, Microsoft Operating system, Microsoft Operating systems, Unix operating systems (for example, those released by Oracle Corporation of Redwood Shores, California) operating system), the AIX UNIX operating system released by International Business Machines Corporation of Armonk, New York, the Linux operating system, Mac OSX and iOS operating systems released by Apple Inc. of Cupertino, California, BlackBerry OS released by BlackBerry Ltd. of Waterloo, Canada, and the Android operating system developed by Google Inc. and the Open Handset Alliance, or the QNX software company for infotainment CAR Platform. Examples of computing devices include, but are not limited to, an in-vehicle computer, a computer workstation, a server, a desktop computer, a notebook, a laptop or a handheld computer, or some other computing system and / or device.

[0075] A computing device typically includes computer executable instructions, where the instructions can be executed by one or more computing devices (such as those listed above). Computer executable instructions can be compiled or interpreted from a computer program created using a variety of programming languages ​​and / or techniques, including but not limited to, individually or in combination, JavaTM, C, C++, Visual Basic, Java Script, Perl, etc. Some of these applications can be compiled and executed on virtual machines such as Java virtual machines, Dalvik virtual machines, etc. In general, a processor (e.g., a microprocessor) receives instructions, such as from a memory, a computer readable medium, etc., and executes these instructions, thereby performing one or more processes, including one or more of the processes described herein. Various computer readable media can be used to store and transmit such instructions and other data.

[0076] Computer-readable media (also referred to as processor-readable media) include any non-temporary (e.g., tangible) media that participate in providing data (e.g., instructions) that can be read by a computer (e.g., by a processor of a computer). Such media can take many forms, including but not limited to non-volatile media and volatile media. Non-volatile media can include, for example, optical or magnetic disks and other persistent memories. Volatile media can include, for example, dynamic random access memory (DRAM), which typically constitutes main memory. Such instructions can be transmitted by one or more transmission media, including coaxial cables, copper wires, and optical fibers, including wires that constitute a system bus connected to a processor of a computer. Common forms of computer-readable media include, for example, floppy disks, floppy disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs, any other optical media, punch cards, paper tapes, any other physical media with a pattern of holes, RAMs, PROMs, EPROMs, FLASH-EEPROMs, any other memory chips or cassettes, or any other media from which a computer can read.

[0077] The database, data repository described herein may include various mechanisms for storing, accessing and retrieving various data, including hierarchical databases, a set of files in a file system, an application database in a proprietary format, a relational database management system (RDBMS), etc. Each such data storage device is typically included in a computing device that uses a computer operating system such as mentioned above, and is accessed via a network in any one or more of a variety of ways. The file system can be accessed by a computer operating system and may include files stored in various formats. In addition to the language (such as the PL / SQL language mentioned above) for creating, storing, editing, and executing stored procedures, RDBMS typically also uses structured query language (SQL).

[0078] In some examples, system elements may be implemented as computer-readable instructions (e.g., software) on one or more computing devices (e.g., servers, personal computers, etc.) stored on computer-readable media associated therewith (e.g., disks, memories, etc.). A computer program product may include instructions stored on a computer-readable medium for performing the functions described herein.

[0079] With respect to the processes, systems, methods, heuristics, etc. described herein, it should be understood that although the steps of such processes, etc. have been described as occurring in a sequence in a particular order, such processes may be practiced with the steps being performed in an order different from the order described herein. It should also be understood that certain steps may be performed simultaneously, other steps may be added, or certain steps described herein may be omitted. In other words, the description of the processes herein is provided for the purpose of illustrating certain embodiments and should in no way be considered to limit the claims.

[0080] Therefore, it should be understood that the above description is intended to be illustrative rather than restrictive. By reading the above description, many embodiments and applications other than the provided examples will become apparent. The scope should not be determined with reference to the above description, but with reference to the appended claims together with the full range of equivalents to which the claims are assigned to determine the scope. It is expected and hoped that the technology discussed herein will develop in the future, and the disclosed system and method will be incorporated into such future embodiments. In short, it should be understood that the application can be modified and varied.

[0081] Unless explicitly stated to the contrary herein, all terms used in the claims are intended to be given their ordinary meaning as understood by those skilled in the art. Specifically, unless a claim states an explicit limitation to the contrary, the use of singular articles such as "a / kind", "the", "said", etc. should be understood to refer to one or more of the indicated elements.

[0082] The abstract is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It should be understood that the abstract is not intended to interpret or limit the scope or meaning of the claims. In addition, in the foregoing detailed description, it can be seen that various features are combined together in various embodiments for the purpose of streamlining the disclosure. This approach to the disclosure should not be interpreted as reflecting the intention that the claimed embodiments require more features than those expressly set forth in each claim. On the contrary, as reflected in the following claims, the subject matter of the present invention lies in less than all the features of a single disclosed embodiment. Therefore, the following claims are hereby incorporated into the detailed description, with each claim itself as a separately claimed subject matter.

[0083] According to the present invention, a vehicle computer is provided, which has: a memory; and a processor, the processor being programmed to execute instructions stored in the memory, the instructions including: receiving a wheel speed from a wheel speed sensor; receiving a vehicle speed from a vehicle speed sensor; determining an average vibration amplitude based on the wheel speed and the vehicle speed; and detecting a vibrating wheel based on the average vibration amplitude.

[0084] According to one embodiment, the processor is programmed to identify a speed range based on the vehicle speed.

[0085] According to one embodiment, the processor is programmed to estimate the wheel radius via the wheel speed sensor.

[0086] According to one embodiment, the processor is programmed to select the frequency bin of interest based on the speed range and the estimated wheel radius.

[0087] According to one embodiment, the processor is programmed to generate an intermediate signal of the wheel based on the wheel speed and the selected frequency bin of interest.

[0088] According to one embodiment, the processor is programmed to determine the average vibration amplitude based at least in part on the intermediate signal.

[0089] According to one embodiment, the processor is programmed to recursively determine the average vibration amplitude.

[0090] According to one embodiment, the processor is programmed to detect the vibrating wheel by comparing the average vibration amplitude to a threshold value.

[0091] According to one embodiment, the processor is programmed to detect the vibrating wheel due to a determination that the average vibration amplitude exceeds the threshold value.

[0092] According to one embodiment, the processor is programmed to autonomously operate the host vehicle according to remedial measures as a result of detecting the vibrating wheel.

[0093] According to the present invention, a method includes: receiving a wheel speed from a wheel speed sensor; receiving a vehicle speed from a vehicle speed sensor; determining an average vibration amplitude based on the wheel speed and the vehicle speed; and detecting a vibrating wheel based on the average vibration amplitude.

[0094] According to one embodiment, the present invention is further characterized by identifying a speed range based on the vehicle speed.

[0095] According to one embodiment, the present invention is further characterized in that the wheel radius is estimated by means of the wheel speed sensor.

[0096] According to one embodiment, the invention is further characterized by selecting the frequency segment of interest based on said speed range and said estimated wheel radius.

[0097] According to one embodiment, the invention is further characterized by generating an intermediate signal of the wheel based on the wheel speed and the selected frequency bin of interest.

[0098] According to one embodiment, the invention is further characterized by determining the average vibration amplitude based at least in part on the intermediate signal.

[0099] According to one embodiment, determining the average vibration amplitude comprises recursively determining the average vibration amplitude.

[0100] According to one embodiment, detecting said vibrating wheel comprises comparing said average vibration amplitude with a threshold value.

[0101] According to one embodiment, detecting the vibrating wheel includes detecting the vibrating wheel because it is determined that the average vibration amplitude exceeds the threshold value.

[0102] According to one embodiment, the invention is further characterized by autonomously operating the host vehicle according to remedial measures as a result of detecting the vibrating wheel.

Claims

1. A method for a vehicle, comprising: receiving wheel speed from a wheel speed sensor; receiving a vehicle speed from a vehicle speed sensor; identifying a speed range according to the vehicle speed; estimating a wheel radius according to the wheel speed sensor; selecting a frequency segment of interest according to the speed range and the estimated wheel radius; determining an average vibration amplitude associated with a selected frequency bin of interest; as well as A vibrating wheel is detected based on the average vibration amplitude. 2 . The method of claim 1 , further comprising generating an intermediate signal for the wheel based on the wheel speed and the selected frequency bin of interest. 3 . The method of claim 2 , further comprising determining the intermediate vibration amplitude based at least in part on the intermediate signal. The method of claim 1 , wherein determining the average vibration amplitude comprises recursively determining the average vibration amplitude.

5. The method of claim 1, wherein detecting the vibrating wheel comprises comparing the average vibration amplitude to a threshold value.

6. The method of claim 5, wherein detecting the vibrating wheel comprises: The vibrating wheel is detected because it is determined that the average vibration amplitude exceeds the threshold value.

7. The method of claim 1, further comprising: Because the vibrating wheel is detected, the host vehicle is autonomously operated according to remedial measures.

8. The method of any one of claims 1-7, executed by a vehicle computer.

9. The method of any one of claims 1-7, performed by an autonomous vehicle controller.

10. The method of any one of claims 1-7, stored as computer executable instructions in a memory and executed by a vehicle computer.

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