Method of enhanced component failure diagnosis for suggesting least probable fault

Patent metadata

Field	Value
Publication number	US-11288900-B2
Application number	US-201916561711-A
Country	US
Kind code	B2
Filing date	Sep 5, 2019
Priority date	Sep 5, 2019
Publication date	Mar 29, 2022
Grant date	Mar 29, 2022

Abstract

A method and system of diagnosing and suggesting least probable faults for an exhibited vehicle failure. The method includes initiating a vehicle health management (VHM) algorithm to monitor a state of health (SOH) for at least one vehicle component at each vehicle operating event over a predetermined time period. The VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation with a confidence level for the at least one vehicle component; calculating a number of Green SOH designations (Ncalculated) over the predetermined time period; and upon an exhibited vehicle failure, providing a least probable cause indication for the at least one component when a set of conditions are met. The set of conditions includes (i) Ncalculated is equal to or greater than a predetermined number of Green SOH designations and (ii) no Yellow SOH and Red SOH designations are present.

First claim

What is claimed is:

1. A method of diagnosing a least probable cause for a failure exhibited by a vehicle, comprising:
initiating a vehicle health management (VHM) algorithm, by a vehicle controller, to monitor a state of health (SOH) for at least one vehicle component at a predetermined vehicle operating event over a predetermined time period, wherein the VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation for the at least one vehicle component;
recording the Green SOH, the Yellow SOH, and the Red SOH designations over the predetermined time period;
retrieving the Green SOH, the Yellow SOH, and the Red SOH designations over the predetermined time period upon the failure exhibited by the vehicle; and
calculating a number of Green SOH designations (N calculated ) over the predetermined time period;
issuing a least probable cause suggestion for the at least one vehicle component when predetermined conditions are met, wherein the predetermined conditions include (i) the calculated number of Green SOH designations (N calculated ) is equal to or greater than a predetermined N value and (ii) no Yellow SOH and Red SOH designations are present; and
communicating, by the vehicle controller, the least probable cause suggestion to a human machine interface (HMI).

2. The method of claim 1 , further comprising:
partitioning the predetermined time period into partitioned time intervals; and
filtering out duplicates of the Green SOH, the Yellow SOH, and the Red SOH designations within a partitioned time interval.

3. The method of claim 2 , further comprising determining a confidence level for the determined at least one of the Green SOH, the Yellow SOH, and the Red SOH designation for the at least one vehicle component.

4. The method of claim 3 , further comprising:
determining a time gap, wherein the time gap is a predetermined number of consecutive partitioned time intervals without a SOH designation; and
wherein the predetermined conditions further include (iii) the time gap having less than a predetermined value.

5. The method of claim 4 , wherein N calculated is calculated using:
N Calculated =( N Total −N Before )
wherein:
N Before is a number of Green SOH designations before the time gap; and
N Total is a total number of Green SOH designations over the predetermined time period.

6. The method of claim 4 , wherein N calculated is calculated using:
N calculated =[ N Before ×f ( T )]+ N After
wherein:
N Before is the number of Green SOH designations before the time gap;
N After is the number of Green SOH designations after the time gap; and
f(T) is a monotonically decreasing function with 0<=f(T)<=1, wherein T is a predetermined amount of time in the time gap.

7. The method of claim 4 , wherein N calculated is calculated using:
N calculated =N Total when the time gap is less than a predetermined number of consecutive time intervals and a consolidated confidence level above a predetermined value, wherein the consolidated confidence level comprises one of a minimal confidence level, a maximum confidence level, and an average confidence level of a group of the Green SOH confidence levels after the time gap;
wherein:
N Total is a total number of Green SOH designations over the predetermined time period.

8. The method of claim 4 , further comprising:
determining when there are missing SOH designations over the predetermined time period;
wherein the predetermined conditions further include (iv) no missing SOH designation is present.

9. The method of claim 8 , further comprising:
determining when there are any alerts for the at least one vehicle component over the predetermined time period;
wherein the predetermined conditions further include (v) no alerts for the at least one vehicle component are present.

10. The method of claim 9 , further comprising:
manually inspecting the at least one vehicle component for visible faults;
wherein the predetermined conditions further include (vi) no visible faults are found.

11. A method of diagnosing and suggesting least probable cause for a failure exhibited by a vehicle, comprising:
initiating a vehicle health management (VHM) algorithm, by a vehicle controller, to monitor a state of health (SOH) for at least one vehicle component at a predetermined vehicle operating event over a predetermined time period, wherein the VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation together with a corresponding confidence level for the at least one vehicle component;
calculating a number of Green SOH designations (N calculated ) over the predetermined time period; and
upon the failure exhibited by the vehicle, displaying a least probable cause indication on a human machine interface (HMI) for the at least one vehicle component when a set of conditions are met,
wherein the set of conditions include (i) the calculated number of Green SOH designations (N calculated ) is equal to or greater than a predetermined number of Green SOH designations and (ii) no Yellow SOH and Red SOH designations are present.

12. The method of claim 11 , further comprising:
determining a maximum number of consecutive partitioned time intervals without a Green SOH designation;
wherein the set of conditions further includes (iii) the number of consecutive partitioned time intervals without a Green SOH designation is less than a predetermined number of partitioned time intervals.

13. The method of claim 12 , further comprising:
determining a number of missing SOH designations over the predetermined time period;
wherein the set of conditions further includes (iv) the number of missing SOH designations is less than a predetermined value.

14. The method of claim 13 , further comprising:
determining when there are any subsystem alerts over the predetermined time period;
wherein the set of conditions further includes (v) no subsystem alerts are present.

15. The method of claim 14 , further comprising:
visually inspecting the at least one vehicle component for faults;
wherein the set of conditions further includes (vi) no visible faults are found.

16. The method of claim 11 , wherein N calculated is calculated using at least one of equations:
N Calculated =( N Total −N Before );  (i)

N calculated =[ N Before ×f ( T )] N After , wherein T =a time gap; and   (ii)

N calculated =N Total   (iii)

when the time gap is less than a pre-defined value and a group of Green SOH designations after the time gap includes a consolidated confidence level above a predetermined value, wherein the consolidated confidence level comprises one of a minimal confidence level, a maximum confidence level, and an average confidence level of the group of Green SOH confidence levels after the time gap;
wherein
N Total is a total number of Green SOH designations over the predetermined time period;
N Before is a number of Green SOH designations before a time gap;
N After is a number of Green SOH designations after the time gap; and
f(T) is a monotonically decreasing function with 0<=f(T)<=1, wherein T is the size of the time gap.

17. An integrated vehicle health management system (IVHMs) for a vehicle, comprising:
a component sensor configured to collect information from a vehicle component; and
a controller in electronic communication with component sensor;
wherein the controller is configured to:
initiate a vehicle health management (VHM) algorithm to monitor a state of health

Assignees

• Gm Global Tech Operations Llc

Inventors

• Jiang Shengbing
• Du Xinyu
• Zhang Yilu
• Sadekar Varsha K
• Sanchez Joshua J
• Krajewski Paul E

Classifications

• G07C2205/02

  using a vehicle scan tool · CPC title

• G07C5/0825

  using optical means · CPC title

• G07C5/0808 Primary

  Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005) · CPC title

• G06F17/18

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G07C5/08 Primary

  Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time · CPC title