Systems and methods for fault detection in lateral velocity estimation

US10202125B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10202125-B2
Application numberUS-201715486107-A
CountryUS
Kind codeB2
Filing dateApr 12, 2017
Priority dateApr 12, 2017
Publication dateFeb 12, 2019
Grant dateFeb 12, 2019

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

Methods and systems are provided for an improved system and method for validating vehicle lateral velocity estimation. The provided system and method employ an efficient validation algorithm to detect lateral velocity estimation faults. The method and system are robust to road uncertainties and do not require redundant estimations or measurements. The provided system and method offer a technological solution for real time validation of lateral velocity estimation using already existing vehicle sensors, and are independent of (i) road condition information, (ii) wheel torque information, (iii) tire model information, and (iv) tire wear information.

First claim

Opening claim text (preview).

What is claimed is: 1. A control system for detecting faults in lateral velocity estimation of a vehicle, the control system comprising: a memory device; and a processor coupled to the memory device and configured to: initialize parameters in the memory device; receive sensor data from sensors in the vehicle, the sensor data comprising acceleration data and longitudinal speed data; process the sensor data and the parameters to generate a plurality of thresholds comprising (i) a lateral acceleration residual threshold, (ii) a pneumatic trail threshold, and (iii) a slip angle threshold; process the sensor data with a drift type fault detection engine, to thereby generate a drift-type fault flag (DTFF) based on the lateral acceleration residual threshold; process the sensor data with a bias type fault detection engine, to thereby generate a bias-type fault flag (BTFF) based on the pneumatic trail threshold and slip angle threshold; process the DTFF and the BTFF with a persistence checking engine, to thereby (i) monitor the BTFF for a first time frame to confirm that the BTFF is stable; and (ii) monitor the DTFF for a second time frame to confirm that the DTFF is stable; and generate a combined fault flag on the concurrence of conditions (a) the stable BTFF and (b) the stable DTFF. 2. The system of claim 1 , wherein the lateral acceleration residual threshold is a variable defined as the difference between a measured lateral acceleration, a y , and an estimated lateral acceleration. 3. The system of claim 2 , wherein the processor is further configured to compare the variable lateral acceleration residual threshold to an acceleration estimation error. 4. The system of claim 1 , wherein sensor data comprises longitudinal acceleration (a x ), yaw rate r, steering wheel angle (δ sw ), and electric power steering (EPS) steering torques (T drv , and T EPS ). 5. The system of claim 4 , wherein the processor is configured to estimate the pneumatic trail threshold based on an excitation measure that reflects a variance of a center of gravity (CG) of the vehicle. 6. The system of claim 5 , wherein the processor is further configured to employ a recursive least square (RLS) method with a forgetting factor to generate a pneumatic trail for a front wheel of the vehicle. 7. The system of claim 6 , wherein the processor is further configured to generate the pneumatic trail for the front wheel of the vehicle based on a self-aligning torque (SAT) and lateral forces on the vehicle. 8. The system of claim 7 , wherein slip angle saturation thresholds are variable, and wherein the processor is further configured to check an estimated slip angle to assure it is within a range of an expected slip angle saturation threshold at low pneumatic trail (PT). 9. The system of claim 8 , wherein the processor is further configured to check an estimated slip angle to see if it has exceeded a slip angle saturation threshold at high PT. 10. The system of claim 9 , wherein the processor is further configured to assert the BTFF based on a combination of the estimated slip angle and the PT. 11. A method for detecting faults in lateral velocity estimation of a vehicle, the method comprising: at a control module: initializing parameters; receiving sensor data from a sensor system in the vehicle, the sensor data comprising acceleration data and longitudinal speed data; processing the sensor data and the parameters to generate a plurality of thresholds comprising (i) a lateral acceleration residual threshold, (ii) a pneumatic trail threshold, and (iii) a slip angle threshold; processing the sensor data with a drift type fault detection engine, thereby generating a drift-type fault flag (DTFF) based on the lateral acceleration residual threshold; processing the sensor data with a bias type fault detection engine, thereby generating a bias-type fault flag (BTFF) based on the pneumatic trail threshold and slip angle threshold; processing the DTFF and the BTFF with a persistence checking engine, thereby (i) monitoring the BTFF for a first time frame to confirm a stable BTFF; and (ii) monitoring the DTFF for a second time frame to confirm a stable DTFF; and generating a combined fault flag on the concurrence of (a) the stable BTFF and (b) the stable DTFF. 12. The method of claim 11 , wherein the lateral acceleration residual threshold is a variable defined as the difference between a measured lateral acceleration, a y , and an estimated lateral acceleration. 13. The method of claim 12 , wherein the estimated lateral acceleration is based on an estimated lateral velocity. 14. The method of claim 13 , wherein sensor data comprises longitudinal acceleration (a x ), yaw rate r, steering wheel angle (δ sw ), and electric power steering (EPS) steering torques (T drv , and T EPS ). 15. The method of claim 14 , further comprising estimating the pneumatic trail threshold based on an excitation measure that reflects a variance of a center of gravity (CG) of the vehicle. 16. The method of claim 15 , further comprising generating a pneumatic trail for a front wheel of the vehicle based on a self-aligning torque (SAT) and lateral forces on the vehicle. 17. The method of claim 16 , further comprising: checking an estimated slip angle to assure it is within a range of expected slip angle saturation thresholds at low pneumatic trail (PT); and checking an estimated slip angle to see if it has exceeded the slip angle threshold at high PT. 18. A vehicle, comprising: a sensor system; a control module coupled to the sensor system, and comprising a memory device and a processor, the control module configured to: initialize parameters in the memory device; receive sensor data from the sensor system, the sensor data comprising acceleration data and longitudinal speed data; process the sensor data and the parameters to generate a plurality of thresholds comprising (i) a lateral acceleration residual threshold, (ii) a pneumatic trail threshold, and (iii) a slip angle threshold; process the sensor data with a drift type fault detection engine, to thereby generate a drift-type fault flag (DTFF)based on the lateral acceleration residual threshold; process the sensor data with a bias type fault detection engine, to thereby generate a bias-type fault flag (BTFF) based on the pneumatic trail threshold and slip angle threshold; process the DTFF and the BTFF with a persistence checking engine, to thereby (i) confirm that the BTFF is stable; and (ii) confirm that the DTFF is stable; and generate a combined fault flag on the concurrence of (a) the stable BTFF and (b) the stable DTFF.

Assignees

Inventors

Classifications

  • Yaw · CPC title

  • Signal treatments, identification of variables or parameters, parameter estimation or state estimation · CPC title

  • Sideslip angle · CPC title

  • B60W40/00Primary

    Estimation or calculation of {non-directly measurable} driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, {e.g. by using mathematical models} · CPC title

  • Steering torque · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US10202125B2 cover?
Methods and systems are provided for an improved system and method for validating vehicle lateral velocity estimation. The provided system and method employ an efficient validation algorithm to detect lateral velocity estimation faults. The method and system are robust to road uncertainties and do not require redundant estimations or measurements. The provided system and method offer a technolo…
Who is the assignee on this patent?
Gm Global Tech Operations Llc
What technology area does this patent fall under?
Primary CPC classification B60W40/00. Mapped technology areas include Operations & Transport.
When was this patent published?
Publication date Tue Feb 12 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).