A prediction system for detecting wear in an encoder used to sense the wheel speed in a vehicle

Abstract

The present invention relates to a prediction system for detecting wear in an encoder used to sense the wheel speed in a vehicle. A system for detecting wear in an encoder used to sense the wheel speed in a vehicle, the encoder being configured to sense the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a vehicle wheel. The noise detection module includes a plurality of noise detectors configured to detect noise in the wheel speed signal generated by the sensor. The estimation module is configured to estimate the health state of the encoder based on the noise detected in the wheel speed signal and generate an alert in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold. The filter is configured to filter the noise in the wheel speed signal and output the filtered wheel speed signal to a control system that controls the vehicle stability.

Description

Technical Field

[0001] Introduction

[0002] The information provided in this section is for the purpose of presenting in general the background of the present disclosure. The work of the currently named inventors, to the extent it is described in this section, and aspects of that description that are not otherwise prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.

[0003] The present invention generally relates to sensing wheel speed in a vehicle, and more particularly to a predictive system for detecting wear in an encoder used to sense wheel speed in a vehicle. Background Art

[0004] In many vehicles, including autonomous and semi-autonomous vehicles, wheel speed is measured to maintain vehicle stability. For example, a vehicle's anti-lock braking system (ABS), traction control system (TCS), and stability control system maintain vehicle stability based on the wheel speed sensed by wheel speed sensors. Summary of the Invention

[0005] A system for detecting wear in an encoder used to sense wheel speed in a vehicle, the system including a sensor, a noise detection module, an estimation module, and a filter. The sensor is configured to sense the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a vehicle wheel. The noise detection module includes a plurality of noise detectors configured to detect noise in a wheel speed signal generated by the sensor. The estimation module is configured to estimate the health state of the encoder based on the noise detected in the wheel speed signal and generate an alert in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold. The filter is configured to filter the noise in the wheel speed signal and output the filtered wheel speed signal to a control system that controls vehicle stability.

[0006] In other features, the plurality of noise detectors include first, second, and third noise detectors. The first noise detector is configured to detect noise in a bit stream received with the wheel speed signal. The bit stream includes bits generated based on sensing magnetic material on the encoder. The second noise detector is configured to detect noise in an envelope of the wheel speed signal. The third noise detector is configured to detect noise by detecting peaks in the wheel speed signal using a fast Fourier transform. The noise detected in the wheel speed signal is a combination of the noise detected by the first, second, and third noise detectors.

[0007] In another feature, the system further includes a weight adjusting module, which is configured to dynamically adjust the weights of the first, second, and third noise detectors to prevent noise from distorting the estimation of the encoder health state generated by the estimation module.

[0008] In another feature, the weight adjusting module is configured to dynamically adjust the weights of the first, second, and third noise detectors based on one or more of vehicle speed, whether the vehicle is turning, and road conditions.

[0009] In other features, when the vehicle speed is greater than or equal to a predetermined speed, the bit stream is truncated. The weight adjusting module is configured to reduce the weight of the first noise detector and increase the weights of the second and third noise detectors when the vehicle speed is greater than or equal to the predetermined speed.

[0010] In another feature, the weight adjusting module is configured to increase the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

[0011] In another feature, the weight adjusting module is configured to reduce the weights of the second and third noise detectors relative to the weight of the first noise detector under uneven road conditions.

[0012] In another feature, the weight adjusting module is configured to increase the weight of the first noise detector and reduce the weight of the second noise detector when the vehicle speed is less than or equal to the predetermined speed.

[0013] In another feature, the filter is configured to filter the wheel speed signal using a first filtering constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and to use a second filtering constant when the noise is greater than the first threshold, where the second filtering constant is greater than the first filtering constant.

[0014] In another feature, the control system for controlling vehicle stability includes a braking system, a traction control system, or a stability control system.

[0015] In still other features, a method for detecting wear in an encoder used to sense the wheel speed in a vehicle includes sensing the wheel speed of the vehicle by sensing magnetic material coupled to the encoder of the vehicle wheel. The method includes using a plurality of noise detectors to detect noise in the wheel speed signal generated by the sensing. The method includes estimating the health state of the encoder based on the noise detected in the wheel speed signal. The method includes generating an alarm in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold. The method includes filtering the noise in the wheel speed signal to output the filtered wheel speed signal to a control system for controlling vehicle stability.

[0016] Among other features, detecting noise using multiple noise detectors includes detecting noise in a bitstream received together with a wheel speed signal using a first noise detector. The bitstream includes bits generated based on magnetic material on a sensing encoder. Detecting noise using multiple noise detectors includes detecting noise in an envelope of the wheel speed signal using a second noise detector. Detecting noise using multiple noise detectors includes detecting noise in the wheel speed signal by detecting peaks in the wheel speed signal using a fast Fourier transform with a third noise detector. Detecting noise using multiple noise detectors includes combining the noise detected by the first, second, and third noise detectors.

[0017] In another feature, the method further includes dynamically adjusting the weights of the first, second, and third noise detectors to prevent noise from distorting the estimation of the encoder health state.

[0018] In another feature, the method further includes dynamically adjusting the weights of the first, second, and third noise detectors based on one or more of vehicle speed, whether the vehicle is turning, and road conditions.

[0019] Among other features, when the vehicle speed is greater than or equal to a predetermined speed, the bitstream is truncated. The method further includes reducing the weight of the first noise detector and increasing the weights of the second and third noise detectors when the vehicle speed is greater than or equal to a predetermined speed.

[0020] In another feature, the method further includes increasing the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

[0021] In another feature, the method further includes reducing the weights of the second and third noise detectors relative to the weight of the first noise detector in an uneven road condition.

[0022] In another feature, the method further includes increasing the weight of the first noise detector and reducing the weight of the second noise detector when the vehicle speed is less than or equal to a predetermined speed.

[0023] In another feature, the method further includes filtering the wheel speed signal using a first filter constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and using a second filter constant when the noise is greater than the first threshold, where the second filter constant is greater than the first filter constant.

[0024] In another feature, the method further includes controlling the stability of the vehicle by controlling at least one of a braking system, a traction control system, and a stability control system.

[0025] The present invention provides the following technical solutions:

[0026] 1. A system for detecting wear in an encoder, the encoder being used to sense the wheel speed in a vehicle, the system comprising:

[0027] A sensor configured to sense the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a wheel of the vehicle;

[0028] A noise detection module including a plurality of noise detectors configured to detect noise in a wheel speed signal generated by the sensor;

[0029] An estimation module configured to:

[0030] Estimate the health state of the encoder based on the noise detected in the wheel speed signal; and

[0031] Generate an alarm in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold; and

[0032] A filter configured to filter the noise in the wheel speed signal and output the filtered wheel speed signal to a control system for controlling vehicle stability.

[0033] 2. The system according to claim 1, wherein the plurality of noise detectors include:

[0034] A first noise detector configured to detect noise in a bit stream received together with the wheel speed signal, wherein the bit stream includes bits generated based on sensing the magnetic material on the encoder;

[0035] A second noise detector configured to detect noise in an envelope of the wheel speed signal; and

[0036] A third noise detector configured to detect noise by detecting peaks in the wheel speed signal using a fast Fourier transform,

[0037] wherein the noise detected in the wheel speed signal is a combination of the noise detected by the first, second, and third noise detectors.

[0038] 3. The system according to claim 2, further comprising a weight adjustment module configured to dynamically adjust the weights of the first, second, and third noise detectors to prevent the noise from distorting the estimation of the health state of the encoder generated by the estimation module.

[0039] 4. The system according to aspect 3, wherein the weight adjustment module is configured to dynamically adjust the weights of the first, second, and third noise detectors based on one or more of the speed of the vehicle, whether the vehicle is turning, and road conditions.

[0040] 5. The system according to aspect 3, wherein when the speed of the vehicle is greater than or equal to a predetermined speed, the bit stream is truncated, and wherein the weight adjustment module is configured to reduce the weight of the first noise detector and increase the weights of the second and third noise detectors when the speed of the vehicle is greater than or equal to the predetermined speed.

[0041] 6. The system according to aspect 3, wherein the weight adjustment module is configured to increase the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

[0042] 7. The system according to aspect 3, wherein the weight adjustment module is configured to reduce the weights of the second and third noise detectors relative to the weight of the first noise detector in an uneven road condition.

[0043] 8. The system according to aspect 3, wherein the weight adjustment module is configured to increase the weight of the first noise detector and reduce the weight of the second noise detector when the speed of the vehicle is less than or equal to a predetermined speed.

[0044] 9. The system according to aspect 1, wherein the filter is configured to filter the wheel speed signal using a first filter constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and using a second filter constant when the noise is greater than the first threshold, wherein the second filter constant is greater than the first filter constant.

[0045] 10. The system according to aspect 1, wherein the control system for controlling vehicle stability includes a braking system, a traction control system, or a stability control system.

[0046] 11. A method for detecting wear in an encoder used to sense the wheel speed in a vehicle, the method comprising:

[0047] sensing the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a wheel of the vehicle;

[0048] detecting noise in the wheel speed signal generated by the sensing using a plurality of noise detectors;

[0049] Estimate the health state of the encoder based on the noise detected in the wheel speed signal;

[0050] Generate an alarm in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold; and

[0051] Filter the noise in the wheel speed signal to output the filtered wheel speed signal to a control system for controlling vehicle stability.

[0052] 12. The method according to claim 11, wherein using a plurality of noise detectors to detect noise includes:

[0053] Use a first noise detector to detect noise in the bit stream received together with the wheel speed signal, wherein the bit stream includes bits generated based on sensing the magnetic material on the encoder;

[0054] Use a second noise detector to detect noise in the envelope of the wheel speed signal;

[0055] Use a third noise detector to detect noise by detecting peaks in the wheel speed signal using a fast Fourier transform; and

[0056] Combine the noise detected by the first, second, and third noise detectors.

[0057] 13. The method according to claim 12, further comprising dynamically adjusting the weights of the first, second, and third noise detectors to prevent the noise from distorting the estimation of the health state of the encoder.

[0058] 14. The method according to claim 13, further comprising dynamically adjusting the weights of the first, second, and third noise detectors based on one or more of the speed of the vehicle, whether the vehicle is turning, and road conditions.

[0059] 15. The method according to claim 13, wherein when the speed of the vehicle is greater than or equal to a predetermined speed, the bit stream is truncated, and the method further comprises reducing the weight of the first noise detector and increasing the weights of the second and third noise detectors when the speed of the vehicle is greater than or equal to the predetermined speed.

[0060] 16. The method according to claim 13, further comprising increasing the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

[0061] 17. The method according to claim 13, wherein it further comprises reducing the weights of the second and third noise detectors relative to the weight of the first noise detector under uneven road conditions.

[0062] 18. The method according to claim 13, wherein it further comprises increasing the weight of the first noise detector and reducing the weight of the second noise detector when the speed of the vehicle is less than or equal to a predetermined speed.

[0063] 19. The method according to claim 11, wherein it further comprises filtering the wheel speed signal using a first filtering constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and using a second filtering constant when the noise is greater than the first threshold, wherein the second filtering constant is greater than the first filtering constant.

[0064] 20. The method according to claim 11, wherein it further comprises controlling the stability of the vehicle by controlling at least one of a braking system, a traction control system, and a stability control system.

[0065] Other applicable fields of the present disclosure will become apparent from the detailed description, the claims, and the drawings. The detailed description and specific examples are only for illustrative purposes and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The present disclosure will be more fully understood from the detailed description and the drawings, wherein:

[0067] Figure 1A An example of an encoder used to sense the wheel speed in a vehicle is shown;

[0068] Figure 1B An example of a system using Figure 1A the encoder to measure the wheel speed is shown;

[0069] Figure 2A An example of a prediction system for estimating the health state of the encoder of FIG. 1 is shown;

[0070] Figure 2B An example of the noise detection module of Figure 2A the prediction system is shown in more detail;

[0071] Figure 3 An example of a method for estimating the health state of the encoder of FIG. 1 performed by Figure 2A the prediction system is shown;

[0072] Figures 4A to 4D An example of Figure 2AExamples of various methods performed by the weight adjustment module of a prediction system; and

[0073] Figures 5A to 5E illustrates examples of various signals received, processed, and generated by Figure 2A the prediction system of

[0074] In the drawings, reference numerals may be reused to identify similar and / or identical elements. Detailed Description

[0075] Figure 1A and 1B illustrates examples of an encoder, wheel speed sensors, and a wheel speed measurement system. The encoder 100 and one or more wheel speed sensors 102, 104 are used to sense the wheel speed of a vehicle. In Figure 1A , the encoder 100 includes magnetic material disposed around the edge of the encoder 100. The magnetic material is arranged such that a series of north and south poles (examples identified at 110, 112) are radially disposed around the edge of the encoder 100. The magnetic material is laminated to prevent dust, water, and other factors that can damage the magnetic material. The encoder 100 is mounted to the wheel bearing.

[0076] In Figure 1B , one or more wheel speed sensors 102, 104 are mounted near the edge of the encoder 100. When the wheel rotates, the encoder 100 rotates at the speed of the wheel. The wheel speed sensors 102, 104 detect the magnetic poles on the encoder 100 and generate an output. The wheel speed measurement system 118 includes one or more brake control modules (e.g., first and second brake control modules 120, 122). The first and second brake control modules 120, 122 respectively receive the outputs of the wheel speed sensors 102, 104. Each of the first and second brake control modules 120, 122 independently calculates the wheel speed based on the outputs of the wheel speed sensors 102, 104.

[0077] Each of the first and second brake control modules 120, 122 is connected to a Controller Area Network (CAN) bus 130 in the vehicle. Each of the first and second brake control modules 120, 122 provides the calculated wheel speed to other modules, such as the vehicle's Anti-lock Braking System (ABS) module 132, Traction Control System (TCS) module 134, and Stability Control module 136, via the CAN bus 130.

[0078] In many vehicles, by using two wheel speed sensors (e.g., Figure 1B the elements 102, 104 shown in Figure 1BComponents 120, 122 shown in are used to provide redundancy in wheel speed sensing, and the brake control module calculates the wheel speed based on data received from the respective wheel speed sensors. However, only one encoder is used. Although laminated, the encoder is prone to deterioration due to wear and tear. If the encoder fails, the wheel speed cannot be sensed. Losing wheel speed sensing will reduce the performance of the autonomous vehicle. The inability to actively detect faults in the wheel speed sensing system will affect the vehicle's safety and driving performance, and will reduce the customer experience. Due to defects in the sensor-encoder interface, a relatively high amount of noise in the wheel speed signal output by the wheel speed sensor will reduce the performance of the vehicle's ABS, TCS, and stability control.

[0079] The present disclosure provides a prediction system that monitors the health of the encoder, actively detects deterioration in the encoder health, and provides an alert for repairing the encoder before the encoder fails. The prediction system combines health indicators from the noisy wheel speed signal to detect the health status of the sensor / encoder interface. Based on the measured state of health (SOH) of the sensor / encoder interface, the prediction system uses an adaptive Kalman filter to generate a noise-resistant wheel speed signal to maximize the availability of vehicle stability control features (such as ABS and TCS).

[0080] Throughout the present disclosure, reference is made to the Verband der Automobilindustrie (VDA), which defines automotive industry standards. The prediction system of the present disclosure makes full use of the capabilities of the wheel speed sensor to classify dynamic changes in the sensor / encoder interface through VDA signals to estimate the state of health (SOH) of the encoder. The prediction system combines the noise determined from envelope-based and FFT-based detection processes with the magnetic field strength of the encoder obtained from the VDA signal to improve SOH estimation. The prediction system uses an adaptive Kalman filter to correct the high-noise wheel speed signal to allow the autonomous vehicle to perform its functions.

[0081] Specifically, any defect in the wheel speed sensor-encoder interface will increase the noise in the wheel speed signal. The prediction system identifies the noise in the wheel speed signal by combining three different health indicators, which are: the VDA signal, the envelope-based process, and the fast Fourier transform (FFT)-based process, to obtain a robust SOH estimate. An adaptive Kalman filter is used to generate a noise-resistant wheel speed signal, which allows the autonomous vehicle to perform its operations in the case of a slight deterioration in wheel speed sensing. These and other features of the prediction system of the present invention will be described in more detail below.

[0082] This disclosure is organized as follows. Reference is made to Figure 2A and Figure 2B which illustrate and describe a prediction system. Reference is made to Figure 3 which illustrate and describe a method performed by the prediction system. Reference is made to Figures 4A to 4D which illustrate and describe examples of various methods performed by the weight adjustment module of the prediction system. Various signals received, processed, and generated by the prediction system are shown in Figures 5A to 5E and are described in the discussion of Figure 2A , Figure 2B and Figure 3 during.

[0083] Figure 2A and Figure 2B illustrate a prediction system 200 for determining the state of health (SOH) of an encoder 100, which is used to sense wheel speed. Figure 2A A block diagram of the prediction system 200 is shown in its entirety. Figure 2B The noise detection module of the prediction system 200 is shown in detail. The prediction system 200 can be implemented in each of the first and second brake control modules 120, 122.

[0084] In Figure 2A , the prediction system 200 includes an encoder 100, a wheel speed sensor 102 (or 104), and a signal processing module 202. The prediction system 200 also includes a noise detection module 204, an SOH estimation module 206, an adaptive Kalman filter 208, and a weight adjustment module 210. The prediction system 200 communicates with the vehicle's infotainment subsystem 212, an ABS module 132, a TCS module 134, and a stability control module 136. The signal processing module 202 also communicates with the vehicle's rough road sensor 220 and other sensors 222.

[0085] The signal processing module 202 processes the data received from the wheel speed sensor 102 and generates a wheel speed signal 230. The signal processing module 202 also outputs serial data (explained below with reference to Figure 2B ) known as the VDA bitstream, as well as the wheel speed signal 230. The sensor 102 generates the VDA bitstream. The signal processing module 202 decodes and parses the VDA bitstream. In addition, the signal processing module 202 processes the data received from the vehicle's rough road sensor 220 and other sensors 222 and outputs corresponding signals 232 to the weight adjustment module 210, which is described in more detail below with reference to Figure 2B .

[0086] The noise detection module 204 uses the method described below with reference to Figure 2BA variety of techniques described in detail are used to estimate the amount of noise in the wheel speed signal 230. The SOH estimation module 206 estimates the SOH of the encoder 100 based on the amount of noise in the wheel speed signal 230 estimated by the noise detection module 204, as described in detail below with reference to Figure 3 When the SOH of the encoder 100 deteriorates severely, the SOH estimation module 206 provides an alert (e.g., an audiovisual alert) via the vehicle's infotainment subsystem 212.

[0087] The adaptive Kalman filter 208 filters the noise in the wheel speed signal 230 according to whether the amount of noise in the wheel speed signal 230 is relatively low or relatively high. When the amount of noise in the wheel speed signal 230 is relatively low (e.g., below a first threshold), the adaptive Kalman filter 208 filters the noise slightly (i.e., using a relatively low filtering constant). When the amount of noise in the wheel speed signal 230 is relatively high (e.g., above a second threshold), the adaptive Kalman filter 208 uses a relatively high filtering constant to filter the noise. Thus, the adaptive Kalman filter 208 adapts its filtering constant to the amount of noise in the wheel speed signal 230 and thus to the SOH of the encoder 100. The adaptive Kalman filter 208 provides a noise-resistant wheel speed signal 240 to the vehicle's ABS module 132, TCS module 134, and stability control module 136.

[0088] Figure 2B The noise detection module 204 is shown in more detail. The noise detection module 204 employs three independent noise detection techniques to detect the amount of noise in the wheel speed signal 230, which includes the VDA bitstream 230-1 and the wheel speed signal 230-2. Figure 5A An example of the wheel speed signal 230-2 is shown, which is shown as a graph of the wheel speed 500 versus time 502. Figure 5B An example of the VDA bitstream 230-1 is shown, which is shown as a graph of the normalized amplitude 504 of the pulses of the VDA bitstream 230-1 versus time 506.

[0089] The noise detection module 204 includes a VDA noise detector 250, an envelope filter 252, and an FFT module 254. The VDA noise detector 250 detects the noise in the VDA bitstream 230-1. The envelope filter 252 determines the amount of noise in the wheel speed signal 230-2. The FFT module 254 detects the peaks in the wheel speed signal 230-2 (e.g., due to defects in the encoder 100). The VDA noise detector 250, the envelope filter 252, and the FFT module 254 are described in turn below.

[0090] The VDA bit stream 230-1 includes a set of nine bits serially output by the wheel speed sensor 102 when magnetic pole pairs 110, 112 on the encoder 100 are sensed. As Figure 5B shown, in the VDA bit stream 230-1, the first bit 510-1 indicates whether the air gap limit has been reached, where the air gap refers to the gap between the encoder 100 and the wheel speed sensor 102. The second bit 510-2 indicates the operating mode (calibrated or uncalibrated) of the encoder 100 and the wheel speed sensor 102. The third bit 510-3 provides an indication of the protocol (standard or advanced) used by the encoder 100 and the wheel speed sensor 102 to provide the VDA bit stream 230-1. The fourth bit 510-4 indicates whether the wheel movement direction indicated by the encoder 100 is valid. The fifth bit 510-5 indicates the wheel movement direction (clockwise or counterclockwise) indicated by the encoder 100. The sixth, seventh, and eighth bits 510-6, 510-7, and 510-8 (collectively 510-6,7,8) indicate the magnetic strength (air gap) of the magnetic poles on the encoder 100 sensed by the wheel speed sensor 102. The ninth bit 510-9 is a parity bit. The nine bits 510-1 to 510-9 are collectively referred to as the VDA bits 510.

[0091] The VDA noise detector 250 detects the amount of noise in the VDA bits 510, which can be used to estimate the health of the encoder 100. The VDA bits 510 include noise depending on vehicle operation and road conditions. For example, the fourth and fifth bits 510-4, 510-5 may include jitter, which may indicate wear in the encoder 100. For example, if the sixth, seventh, and eighth bits 510-6, 510-7, and 510-8 indicate that the magnetic strength (air gap) increases and decreases frequently, this inconsistent pattern may indicate wear in the encoder 100. Generally, the content and pattern of the VDA bits 510 detected by the VDA noise detector 250 can indicate the health of the encoder 100.

[0092] The envelope filter 252 determines the amount of normalized noise in the wheel speed signal 230-2. Figure 5C A graph of the wheel speed 500 versus time 502 is shown, and the envelope 520 of the wheel speed signal 230-2 is shown. The envelope filter 252 determines the normalized noise 522 in the envelope 520.

[0093] The FFT module 254 transforms the wheel speed signal 230-2 into the frequency domain and detects the peaks in the wheel speed signal 230-2. Figure 5DA graph showing the power spectral density 530 of the wheel speed signal 230-2 relative to the frequency 532 is presented. The FFT module 254 detects a peak 534 in the wheel speed signal 230-2, the amplitude of which is greater than a predetermined threshold. For example, the peak 534 may occur due to a fault in the encoder 100, which may occur due to contaminant deposition and / or other losses in the encoder 100.

[0094] The weight adjustment module 210 adjusts the weights of the VDA noise detector 250, the envelope filter 252, and the FFT module 254. The noise in the wheel speed signal 230 varies according to various factors. For example, the noise varies based on the operation of the vehicle (e.g., vehicle speed, whether the vehicle is turning, etc.), which can be sensed by other sensors 222 of the vehicle. In addition, the noise varies according to road conditions. For example, uneven road conditions may include potholes, rumble strips, etc. encountered by the wheels, which can be sensed by the uneven road sensor 220.

[0095] Various other factors related to vehicle operation and road conditions are sensed by other sensors 222 of the vehicle. The weight adjustment module 210 adjusts the weights of the VDA noise detector 250, the envelope filter 252, and the FFT module 254 according to these factors.

[0096] For example, at a relatively low vehicle speed, the wheel speed signal 230 may include a relatively high amount of noise. Therefore, at a relatively low vehicle speed, the envelope filter 252 may detect a relatively high amount of noise, which may not reliably indicate the health of the encoder 100. For example, at a relatively low vehicle speed, the SOH estimation module 206 may misinterpret the relatively high amount of noise detected by the envelope filter 252 in the wheel speed signal 230-2 as an indication of wear in the encoder 100. To avoid such inaccurate determination or false alarm detection by the SOH estimation module 206, the weight adjustment module 210 is capable of reducing the weight of the envelope filter 252 at a relatively low vehicle speed.

[0097] On the other hand, at a lower vehicle speed, the VDA bits may include a relatively low amount of noise compared to at a higher vehicle speed. Therefore, the weight adjustment module 210 may increase the weight of the VDA noise detector 250 at a relatively low vehicle speed. In addition, when the vehicle is turning, the vehicle speed is usually relatively low, and the VDA bits 510 may include a relatively low amount of noise. Therefore, when the vehicle is turning (which can be detected by other sensors 222), the weight adjustment module 210 may increase the weight of the VDA noise detector 250.

[0098] Conversely, at relatively high vehicle speeds, the VDA bitstream is typically truncated (i.e., not all VDA bits 510 are output together with the wheel speed signal 230). As a result, false alarms may be generated if wear on the encoder 100 is erroneously inferred based on the truncated VDA bitstream. Therefore, at relatively high vehicle speeds, the weight adjustment module 210 can reduce the weight of the VDA noise detector 250 and increase the weights of the envelope filter 252 and the FFT module 254.

[0099] As another example, in uneven road conditions, the FFT module 254 and the envelope filter 252 can detect noise in the wheel speed signal 230-2. As a result, false alarms may also be generated if wear on the encoder 100 is erroneously inferred based on the noise detected by the FFT module 254 and the envelope filter 252 in the wheel speed signal 230-2. Therefore, when uneven road conditions are detected, the weight adjustment module 210 can reduce the weights of the FFT module 254 and the envelope filter 252.

[0100] In general, the weight adjustment module 210 can dynamically adjust the weights of the VDA noise detector 250, the envelope filter 252, and the FFT module 254 based on factors such as vehicle speed, whether the vehicle is turning, and road conditions, to prevent the SOH estimation module 206 from detecting false alarms and distorting the estimation of the health state of the encoder 100. The SOH estimation module 206 determines the health of the encoder 100 based on the amount of noise estimated by the noise detection module 204 as follows.

[0101] Figure 3 Method 300 performed by the prediction system 200 is shown. For example, one or more components of the prediction system 200 may perform the steps of method 300. Therefore, the term "controller" used in the following description refers to one or more components of the prediction system 200.

[0102] At 302, the controller (e.g., the signal processing module 202) generates a wheel speed signal 230 based on data received from the wheel speed sensor 102 coupled to the encoder 100. At 304, the controller (e.g., the noise detection module 204) detects and analyzes the noise in the wheel speed signal 230. At 306, the controller (e.g., the SOH estimation module 206) estimates the health of the encoder 100 based on the noise analysis.

[0103] At 308, the controller (e.g., SOH estimation module 206) determines whether the noise in the wheel speed signal 230 is less than a first threshold (Th1). If the noise is less than the first threshold (Th1), then at 310, the controller (e.g., SOH estimation module 206) determines that the encoder 100 is healthy (i.e., without defects or wear and operating normally). At 312, the controller (e.g., adaptive Kalman filter 208) slightly filters the wheel speed signal 230 (i.e., using a relatively low filter constant) and provides the slightly filtered wheel speed signal 230 to one or more control systems of the vehicle (e.g., ABS module 132, TCS module 134, and stability control module 136). Control returns to 302.

[0104] If the noise in the wheel speed signal 230 is greater than the first threshold (Th1), at 314, the controller (e.g., SOH estimation module 206) determines whether the noise in the wheel speed signal 230 is less than a second threshold (Th2), where Th2 > Th1. If the noise in the wheel speed signal 230 is greater than the first threshold (Th1) but less than the second threshold (Th2), at 316, the controller (e.g., SOH estimation module 206) determines that the encoder 100 is deteriorating (i.e., the encoder 100 has a certain amount of wear or defects), but the error due to the deterioration is recoverable (i.e., the amount of wear is less than a predetermined threshold).

[0105] At 318, the controller (e.g., adaptive Kalman filter 208) increases the filter constant and filters the wheel speed signal 230 with a relatively high amount of filtering (i.e., using a relatively high filter constant). The controller (e.g., adaptive Kalman filter 208) provides the relatively highly filtered wheel speed signal 230 to one or more control systems of the vehicle (e.g., ABS module 132, TCS module 134, and stability control module 136). Control returns to 302.

[0106] If the noise in the wheel speed signal 230 is greater than the second threshold (Th2), at 320, the controller (e.g., SOH estimation module 206) determines that the encoder is severely or significantly deteriorated (i.e., the amount of wear is greater than a predetermined threshold). The controller (e.g., SOH estimation module 206) generates an alert (e.g., displays a message to schedule a repair on the infotainment subsystem 212). Control returns to 302.

[0107] Figure 5E An example of the encoder health state determined by the SOH estimation module 206 is shown. Figure 5E The health state is shown according to a graph of the amount of noise 540 in the wheel speed signal 230 detected by the noise detection module 204 relative to the wheel speed 542. AtFigure 5E In the graph shown in, region 544 indicates a severely degraded health state of encoder 100, where errors due to degradation are not recoverable. Region 546 indicates a moderately degraded health state of encoder 100, where errors caused by degradation are recoverable. Region 548 indicates the health state of encoder 100, where the error rate is relatively low (e.g., less than a predetermined threshold).

[0108] Figures 4A to 4D Various examples of the method performed by weight adjustment module 210 are shown. Weight adjustment module 210 performs these methods simultaneously to dynamically adjust the weights of VDA noise detector 250, envelope filter 252, and FFT module 254 according to factors such as vehicle speed, whether the vehicle is turning, road conditions, etc., to prevent SOH estimation module 206 from detecting false alarms and distorting the estimation of the health state of encoder 100.

[0109] In Figure 4A , weight adjustment module 210 performs method 400 as follows. At 402, weight adjustment module 210 determines whether the wheel speed is relatively low (e.g., less than a first speed). If the wheel speed is relatively low, at 404, weight adjustment module 210 reduces the weight of envelope filter 252. At 406, weight adjustment module 210 increases the weight of VDA noise detector 250. Method 400 ends.

[0110] In Figure 4B , weight adjustment module 210 performs method 420 as follows. At 422, weight adjustment module 210 determines whether the wheel speed is relatively high (e.g., greater than a second speed, which is greater than the first speed). If the wheel speed is relatively high, at 424, weight adjustment module 210 reduces the weight of VDA noise detector 250. At 426, weight adjustment module 210 increases the weights of envelope filter 252 and FFT module 254. Method 420 ends.

[0111] In Figure 4C , weight adjustment module 210 performs method 450 as follows. At 452, weight adjustment module 210 determines whether the vehicle is turning (e.g., based on one of the signals 232 received from signal processing module 202). If the vehicle is turning, at 454, weight adjustment module 210 increases the weight of VDA noise detector 250, and method 450 ends.

[0112] In Figure 4DIn [the above], the weight adjustment module 210 executes method 480 as follows. At 482, the weight adjustment module 210 determines whether an uneven road condition is detected (e.g., based on one of the signals 232 received from the signal processing module 202). If an uneven road condition is detected, at 484, the weight adjustment module 210 reduces the weights of the envelope filter 252 and the FFT module 254, and method 450 ends.

[0113] Accordingly, the prediction system 200 provides two - level control to detect wear in the encoder 100 and mitigate the effects of wear in the encoder 100. The first - level control is provided by the weight adjustment module 210, which dynamically adjusts the weights of the VDA noise detector 250, the envelope filter 252, and the FFT module 254 to correctly detect the SOH and thus correctly detect wear in the encoder 100, as described above. The second - level control is provided by the adaptive Kalman filter 208, which selectively filters the wheel speed signal 230 based on the amount of noise detected by the noise detection module 204 to mitigate the effects of wear in the encoder 100. Further, when the wear of the encoder 100 becomes greater than a predetermined threshold, the prediction system 200 proactively provides an alert, which allows the encoder 100 to be repaired before it fails, which in turn prevents vehicle stability features (e.g., ABS, TCS, etc.) from being disabled.

[0114] The foregoing description is merely illustrative in nature and is not intended to limit the present disclosure, its application, or uses. The broad teachings of the present disclosure may be implemented in a variety of forms. Thus, although the present disclosure includes specific examples, the true scope of the present disclosure should not be so limited because other modifications will become apparent upon study of the drawings, the specification, and the following claims. It should be understood that one or more steps within a method may be executed in a different order (or simultaneously) without altering the principles of the present disclosure. Further, although each of the embodiments above is described as having certain features, any one or more of those features described with respect to any embodiment of the present disclosure can be implemented in and / or combined with the features of any one of the other embodiments, even if the combination is not explicitly described. In other words, the described embodiments are not mutually exclusive, and permutations of one or more of the embodiments with each other are still within the scope of the present disclosure.

[0115] The spatial and functional relationships between elements (e.g., between modules, circuit elements, semiconductor layers, etc.) are described using various terms, including "connected", "engaged", "coupled", "adjacent", "immediate", "on top of", "above", "below", and "disposed". Unless explicitly described as "direct", when the relationship between a first element and a second element is described in the foregoing disclosure, the relationship can be a direct relationship with no other intervening elements between the first and second elements, but can also be an indirect relationship with one or more intervening elements (spatially or functionally) between the first and second elements. As used herein, the phrase "at least one of A, B, and C" should be construed to mean logic (A or B or C) using non-exclusive logical OR and should not be construed to mean "at least one of A, at least one of B, and at least one of C".

[0116] In the figures, the arrow direction indicated by the arrow generally shows the flow of information (e.g., data or instructions) of interest in the illustration. For example, when elements A and B exchange various information and the information sent from element A to element B is relevant to the illustration, the arrow can point from element A to element B. Such a unidirectional arrow does not mean that no other information is sent from element B to element A. In addition, for the information sent from element A to element B, element B can send a request for the information or receive an acknowledgement to element A.

[0117] In this application, including the following definitions, the term "module" or the term "controller" can be replaced with the term "circuit". The term "module" can refer to, be part of, or include the following: application specific integrated circuit (ASIC); digital, analog, or mixed analog / digital discrete circuit; digital, analog, or mixed analog / digital integrated circuit; combinational logic circuit; field programmable gate array (FPGA); processor circuit (shared, dedicated, or group) that executes code; memory circuit (shared, dedicated, or group) that stores code executed by the processor circuit; other suitable hardware components that provide the function; or a combination of some or all of the foregoing, such as in a system on a chip.

[0118] A module can include one or more interface circuits. In some examples, the interface circuit can include a wired or wireless interface connected to a local area network (LAN), the Internet, a wide area network (WAN), or a combination thereof. The functions of any given module of the present disclosure can be distributed among multiple modules connected through the interface circuit. For example, multiple modules can allow load balancing. In another example, a server (also referred to as remote or cloud) module can perform some functions on behalf of a client module.

[0119] The term code as used above can include software, firmware, and / or microcode, and can refer to programs, routines, functions, classes, data structures, and / or objects. The term shared processor circuit includes a single processor circuit that executes portions or all of the code from multiple modules. The term group processor circuit includes a processor circuit that, in conjunction with additional processor circuits, executes some or all of the code from one or more modules. References to a multi-processor circuit include multiple processor circuits on discrete die, multiple processor circuits on a single die, multiple cores of a single processor circuit, multiple threads of a single processor circuit, or combinations of the above. The term shared memory circuit includes a single memory circuit that stores some or all of the code from multiple modules. The term group memory circuit includes a memory circuit that, in combination with additional memory, stores some or all of the code from one or more modules.

[0120] The term memory circuit is a subset of the term computer-readable medium. As used herein, the term computer-readable medium does not include transitory electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); thus, the term computer-readable medium can be considered tangible and non-transitory. Non-limiting examples of non-transitory tangible computer-readable media are non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only memory circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital magnetic tape or hard disk drives), and optical storage media (such as CDs, DVDs, or Blu-ray discs).

[0121] The devices and methods described in this application can be implemented, in part or in whole, by a special-purpose computer created by configuring a general-purpose computer to execute one or more specific functions embodied in a computer program. The above functional blocks, flowchart components, and other elements serve as software specifications that can be translated into a computer program by the routine work of a skilled technician or programmer.

[0122] A computer program includes processor-executable instructions stored on at least one non-transitory tangible computer-readable medium. The computer program can also include or rely on stored data. The computer program can include a basic input / output system (BIOS) that interacts with the hardware of the special-purpose computer, device drivers that interact with specific devices of the special-purpose computer, one or more operating systems, user applications, background services, background applications, and the like.

[0123] A computer program may include: (i) descriptive text to be parsed, such as HTML (HyperText Markup Language), XML (eXtensible Markup Language), or JSON (JavaScript Object Notation); (ii) assembly code; (iii) object code generated from source code by a compiler; (iv) source code executed by an interpreter; (v) source code compiled and executed by a just-in-time compiler, etc. By way of example only, source code may be written using the syntax of languages such as: C, C++, C#, Objective C, Swift, Haskell, Go, SQL, R, Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, Javascript®, HTML5 (HyperText Markup Language version 5), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Flash®, Visual Basic®, Lua, MATLAB, SIMULINK, and Python®.

Claims

1. A system for detecting wear in an encoder, the encoder being used to sense the wheel speed in a vehicle, the system comprising: A sensor configured to sense the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a wheel of the vehicle; A noise detection module including a plurality of noise detectors configured to detect noise in a wheel speed signal generated by the sensor; An estimation module configured to: Estimate the health state of the encoder based on the noise detected in the wheel speed signal; And Generate an alarm in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold; And A filter configured to filter the noise in the wheel speed signal and output the filtered wheel speed signal to a control system for controlling vehicle stability, wherein The plurality of noise detectors include: A first noise detector configured to detect noise in a bit stream received together with the wheel speed signal, wherein the bit stream includes bits generated based on sensing the magnetic material on the encoder; A second noise detector configured to detect noise in an envelope of the wheel speed signal; and A third noise detector configured to detect noise by detecting peaks in the wheel speed signal using a fast Fourier transform, Wherein the noise detected in the wheel speed signal is a combination of the noise detected by the first, second, and third noise detectors.

2. The system according to claim 1, characterized in that It further includes a weight adjustment module configured to dynamically adjust the weights of the first, second, and third noise detectors to prevent the noise from distorting the estimation of the health state of the encoder generated by the estimation module.

3. The system according to claim 2, wherein The weight adjustment module is configured to dynamically adjust the weights of the first, second, and third noise detectors based on one or more of the speed of the vehicle, whether the vehicle is turning, and road conditions.

4. The system according to claim 2, wherein When the speed of the vehicle is greater than or equal to a predetermined speed, the bit stream is truncated, and wherein the weight adjustment module is configured to reduce the weight of the first noise detector and increase the weights of the second and third noise detectors when the speed of the vehicle is greater than or equal to a predetermined speed.

5. The system according to claim 2, characterized in that, The weight adjustment module is configured to increase the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

6. The system according to claim 2, wherein The weight adjustment module is configured to reduce the weights of the second and third noise detectors relative to the weight of the first noise detector in an uneven road condition.

7. The system according to claim 2, characterized in that, The weight adjustment module is configured to increase the weight of the first noise detector and reduce the weight of the second noise detector when the speed of the vehicle is less than or equal to a predetermined speed.

8. The system according to claim 1, characterized in that, The filter is configured to filter the wheel speed signal with a first filtering constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and use a second filtering constant when the noise is greater than the first threshold, where the second filtering constant is greater than the first filtering constant.

9. The system according to claim 1, wherein The control system for controlling vehicle stability includes a braking system, a traction control system, or a stability control system.

10. A method for detecting wear in an encoder that is used to sense the wheel speed in a vehicle, the method comprising: sensing the wheel speed of the vehicle by sensing magnetic material on an encoder coupled to a wheel of the vehicle; detecting noise in the wheel speed signal generated by the sensing using a plurality of noise detectors; estimating the health state of the encoder based on the noise detected in the wheel speed signal; generating an alert in response to a health state indicating that the amount of wear on the encoder is greater than a predetermined threshold; and filtering the noise in the wheel speed signal to output the filtered wheel speed signal to a control system for controlling vehicle stability, wherein detecting noise using a plurality of noise detectors includes: detecting noise in a bit stream received together with the wheel speed signal using a first noise detector, where the bit stream includes bits generated based on sensing the magnetic material on the encoder; detecting noise in an envelope of the wheel speed signal using a second noise detector; detecting noise using a third noise detector by detecting peaks in the wheel speed signal using a fast Fourier transform; and combining the noise detected by the first, second, and third noise detectors.

11. The method according to claim 10, wherein It further includes dynamically adjusting the weights of the first, second, and third noise detectors to prevent the noise from distorting the estimation of the health state of the encoder.

12. The method according to claim 11, characterized in that, It further includes dynamically adjusting the weights of the first, second, and third noise detectors based on one or more of the speed of the vehicle, whether the vehicle is turning, and road conditions.

13. The method according to claim 11, wherein When the speed of the vehicle is greater than or equal to a predetermined speed, the bit stream is truncated, and the method further includes reducing the weight of the first noise detector and increasing the weights of the second and third noise detectors when the speed of the vehicle is greater than or equal to the predetermined speed.

14. The method according to claim 11, wherein It further includes increasing the weight of the first noise detector relative to the weights of the second and third noise detectors when the vehicle is turning.

15. The method according to claim 11, wherein It further includes reducing the weights of the second and third noise detectors relative to the weight of the first noise detector under uneven road conditions.

16. The method according to claim 11, wherein It further includes increasing the weight of the first noise detector and reducing the weight of the second noise detector when the speed of the vehicle is less than or equal to a predetermined speed.

17. The method according to claim 10, wherein It further includes filtering the wheel speed signal with a first filtering constant when the noise detected in the wheel speed signal is less than or equal to a first threshold, and using a second filtering constant when the noise is greater than the first threshold, where the second filtering constant is greater than the first filtering constant.

18. The method according to claim 10, characterized in that, It also includes controlling the stability of the vehicle by controlling at least one of the braking system, the traction control system, and the stability control system.

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