Predictive diagnostic method

• US 9,177,428 B2
• Filed: 08/20/2012
• Issued: 11/03/2015
• Est. Priority Date: 08/20/2012
• Status: Active Grant

• Current Assignee: Innova Electronics Corporation (Innova Telematics Solutions)
• Original Assignee: Innova Electronics Corporation (Innova Telematics Solutions)
• Inventors: Nguyen, Michael, Madison, Robert, Andreasen, Keith
• Primary Examiner(s): Mawari, Redhwan k
• Assistant Examiner(s): King, Rodney P
• Application Number:
  US13/589,532
• Publication Number:
  US 20140052328A1
• Time in Patent Office: 1,170 Days
• Field of Search: 701/29
• US Class Current: 1/1
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G07C 2205/02 using a vehicle scan tool
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005

Abstract

There is provided a method of predicting defects likely to occur in a vehicle over a predetermined period. The method includes receiving vehicle characteristic data regarding a vehicle under consideration, and comparing the received vehicle characteristic data with a defect database. The defect database includes information related to defects that have occurred in different vehicles and the mileage at which such defects occurred. The method additionally includes identifying defects that occurred in vehicles corresponding to use vehicle under consideration, and the mileage at which such defects occurred. Detects which fail to satisfy minimum count requirements are then filtered out, and the defects are then sorted in order of the highest defect count.

Claims

1. A method of predicting defects likely to occur in a vehicle over a predetermined period, the method comprising:

a) receiving, at a server, vehicle characteristic data regarding a vehicle under consideration;

b) establishing a defect database at the server, the defect database having information related to defects that have occurred in different vehicles and the reference mileage at which such defects occurred;

c) identifying, at the server, defects that occurred in vehicles corresponding to the vehicle under consideration, and the reference mileage at which such defects occurred;

d) comparing, at the server, vehicle characteristic data associated with the vehicle under test with vehicle characteristic data associated with the identified defects stored in the defect database to identify defects that have occurred in vehicles that substantially correspond to the vehicle under consideration; and

e) restricting, at the server, the identified defects to defects that have occurred in substantially corresponding vehicles that are associated with a reference mileage that is within a mileage bracket that extends from a mileage approximately 15,000 miles less than the current mileage to a mileage approximately 30,000 miles greater than the current mileage.

2. The method as recited in claim 1, wherein the received vehicle characteristic data includes the year, make, model, engine, and current mileage of the vehicle under consideration.

3. The method as recited in claim 2, wherein the defect database information includes the year, make, model, engine, defect(s), and the reference mileage associated with each identified associated defect.

4. The method as recited in claim 1, further including the step of adjusting the current mileage to the nearest 5,000 mile gradient.

5. The method as recited in claim 1, wherein the mileage bracket extends from 15,000 miles less than the adjusted mileage to 30,000 miles greater than adjusted mileage.

6. The method as recited in claim 1, further including the step of receiving live data from the vehicle under consideration, the live data including diagnostic information regarding operating characteristics of an automotive device associated with at least one defect within the mileage bracket.

7. The method as recited in claim 1, further including the step of adjusting the current mileage based on diagnostic information indicating the operating condition of the automotive device associated with the defect.

8. The method as recited in claim 7, wherein the step of adjusting the current mileage includes the step of increasing the current mileage where the diagnostic information associated with the automotive device associated with the defect indicates that the associated device is not in optimum operating condition.

9. The method as recited in claim 7, wherein the step of adjusting the current mileage includes the step of increasing the current mileage where the diagnostic information indicates that the device associated with the defect is in optimum operating condition.

10. The method as recited in claim 1, further comprising the steps of receiving information regarding the climatic region in which the vehicle under consideration has been used, and adjusting the current mileage based on the information regarding the climate region.

11. The method as recited in claim 10, wherein the step of adjusting the current mileage based on the information regarding the climatic region comprises the step of increasing the current mileage where the information regarding the climate region indicates that the vehicle has operated in a region characterized by harsh climate conditions.

12. The method as recited in claim 11, wherein at least one defect is associated with a climatically sensitive vehicle device.

13. The method as recited in claim 12, wherein the climatically sensitive device includes at least one in the group consisting of:

a muffler, a body panel, a radiator, a battery, a door lock, and a starter.

14. The method as recited in claim 1, further comprising the step of limiting the identified defects to those defects which occurred in a mileage bracket that includes the mileage of the vehicle under consideration.

15. The method as recited in claim 1, wherein the defects in the defect database are derived from actual repair records.

16. The method as recited in claim 1, wherein the defects in the defect database are derived from a probabilistic determination of a most likely defect based on vehicle diagnostic data.

17. The method as recited in claim 1, wherein the received vehicle characteristic data includes geographic information associated with the vehicle under consideration.

18. The method as recited in claim 1, further including the step of adjusting the mileage associated with the identified defects based on vehicle characteristic data.

19. The method as recited in claim 18, wherein the mileage associated with the identified defects is lowered based on the vehicle characteristic data.

20. The method as recited in claim 18, wherein the mileage associated with the identified defects is raised based on the vehicle characteristic data.

21. A predictive diagnostic system for generating a predictive diagnostic report for a vehicle under consideration, the predictive diagnostic system comprising:

a defect database located in a server, the defect database having information related to defects that have occurred in different reference vehicles and the reference mileage at which such defects occurred, each reference vehicle being associated with characteristic data; and

a comparison module located in the server and in operative communication with the defect database, the comparison module configured to compare vehicle characteristic data associated with the vehicle under consideration and to identify defects that have occurred in certain ones of the different reference vehicles having associated vehicle characteristic data that is substantially similar to the vehicle characteristic data associated with the vehicle under consideration over a mileage range that extends at least 10,000 miles beyond the current mileage of the vehicle under consideration.

22. The predictive diagnostic system recited in claim 21, further comprising a report generating module in operative communication with the comparison module and configured to generate a predictive diagnostic report including the identified defects and the reference mileage at which such defects occurred.

23. The predictive diagnostic system recited in claim 21, wherein the vehicle characteristic data includes year, make, and model of the vehicle under consideration.

24. The predictive diagnostic system recited in claim 23, wherein the vehicle characteristic data further includes data selected from the group comprising:

geographic information related to the operating environment of the vehicle under consideration and climatic information relating to the operating environment.

25. The predictive diagnostic system recited in claim 21, wherein the vehicle characteristic data associated with the vehicle under consideration includes live data from the vehicle under consideration.

26. A method of predicting defects likely to occur in a vehicle over a predetermined period, the method comprising:

a) receiving, at a server, vehicle characteristic data regarding a vehicle under consideration;

b) establishing a defect database in the server, the defect database having information related to defects that have occurred in different vehicles and the reference mileage at which such defects occurred;

c) identifying, at the server, defects that occurred in vehicles corresponding to the vehicle under consideration, and the reference mileage at which such defects occurred;

d) comparing, at the server, vehicle characteristic data associated with the vehicle under test with vehicle characteristic data associated with the identified defects stored in the defect database to identify defects that have occurred in vehicles that substantially correspond to the vehicle under consideration; and

e) restricting, at the server, the identified defects to defects that have occurred in substantially corresponding vehicles that are associated with a reference mileage that is within a mileage bracket that extends at least 10,000 miles beyond the current mileage of the vehicle.

27. A method of predicting defects likely to occur in a vehicle over a predetermined period, the method comprising:

a) receiving, at a server, vehicle characteristic data regarding a vehicle under consideration;

b) establishing a defect database in the server, the defect database having information related to defects that have occurred in different vehicles and the reference mileage at which such defects occurred;

c) identifying, at the server, defects that occurred in vehicles corresponding to the vehicle under consideration, and the reference mileage at which such defects occurred;

d) comparing, at the server, vehicle characteristic data associated with the vehicle under test with vehicle characteristic data associated with the identified defects stored in the defect database to identify defects that have occurred in vehicles that substantially correspond to the vehicle under consideration; and

e) restricting, at the server, the identified defects to defects that have occurred in substantially corresponding vehicles that are associated with a reference mileage that is within a mileage bracket that extends 10,000 miles about the current mileage of the vehicle.

28. A method of predicting defects likely to occur in a vehicle over a predetermined period, the method comprising:

a) receiving, at a server, vehicle characteristic data regarding a vehicle under consideration;

b) establishing a defect database in the server, the defect database having information related to defects that have occurred in different vehicles and the reference mileage at which such defects occurred;

c) identifying, at the server, defects that occurred in vehicles corresponding to the vehicle under consideration, and the reference mileage at which such defects occurred;

d) comparing, at the server, vehicle characteristic data associated with the vehicle under test with vehicle characteristic data associated with the identified defects stored in the defect database to identify defects that have occurred in vehicles that substantially correspond to the vehicle under consideration; and

e) restricting, at the server, the identified defects to defects that have occurred in substantially corresponding vehicles that are associated with a reference mileage that is within a mileage bracket that is sufficiently extensive as to encompass vehicle defects that are unrelated to any current vehicle defects.