COST-OPTIMIZED MODEL-BASED EXTENSION OF SYSTEM LIFE

• US 20130073222A1
• Filed: 09/21/2011
• Published: 03/21/2013
• Est. Priority Date: 09/21/2011
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Shin, Kwang-Keun, Salman, Mutasim A.
• Granted Patent: US 9,251,309 B2
• Time in Patent Office: Days
• US Class Current: 702/34
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y02T 10/40 Engine management systems

Abstract

A method includes recording a current performance signature for first and second components in a system, recording a calibrated baseline performance signature for the components, and processing the performance signatures through an aging model to determine a future performance signature for each component. The future performance signatures are processed through a system function model to determine the state of function of the system for each possible repair case. A cost-optimal repair case is then determined from among the possible repair cases, and recorded in memory. An apparatus includes first and second components of a system, and a host machine configured for processing the current and baseline performance signatures through the aging and system function models as noted above. The cost-optimal repair case is determined from among all possible repair cases, and then recorded in memory. An example system may be a cranking system with a starter motor and battery.

Claims

1. A method comprising:

recording a current performance signature for a first and a second component in a system;

recording a calibrated baseline performance signature for the first and the second components;

processing the current and calibrated baseline performance signatures through an aging model to determine a future performance signature for each of the components;

processing the future performance signatures for the components through a system function model to determine the state of function (SOF) of the system for each possible repair case, wherein each possible repair case describes a possible repair combination of the first and second components;

calculating a cost-optimal repair case from among the possible repair cases; and

recording the cost-optimal repair case in memory.

2. The method of claim 1, further comprising recording a desired system life for the system, wherein calculating a cost-optimal repair case from among the possible repair cases includes calculating a repair which is cost-optimal over the desired system life.

3. The method of claim 1, further comprising:

recording the current and calibrated baseline performance signatures via a data recorder; and

processing the current and calibrated baseline performance signatures via a host machine in remote communication with the data recorder.

4. The method of claim 1, wherein processing the current and calibrated baseline performance signatures through an aging model includes comparing the current and calibrated baseline performance signatures to a recorded trace of past performance values for substantially similar components.

5. The method of claim 1, wherein the system is a vehicle, the first component is a starter motor, the second component is a battery, and the SOF is the cranking function of a starter system which includes the starter motor and the battery.

6. An apparatus comprising:

a first component;

a second component; and

a host machine in communication with the first and second components, and having an aging model and a system function model, wherein the host machine is configured for;

receiving current and calibrated baseline performance signatures for each of the first and second components;

processing the current and calibrated baseline performance signatures of the aging model to determine a future performance signature for each of the first and second components;

processing the future performance signatures through the system function model to determine a state of function (SOF) of the system for each possible repair case, wherein each possible repair case describes a possible repair combination of the first and second components;

calculating a cost-optimal repair case from among the possible repair cases; and

recording the cost-optimal repair case in memory.

7. The apparatus of claim 6, further comprising a data recorder in communication with the host machine, wherein the data recorder is configured for:

recording the current performance signature for each of the first and second components; and

recording the calibrated baseline performance signature for each of the first and the second components.

8. The apparatus of claim 7, wherein the system is a vehicle system, the data recorder is positioned aboard the vehicle, and the host machine is positioned remotely with respect to the vehicle.

9. The apparatus of claim 7, wherein the system is a vehicle cranking system, the first component is a starter motor, and the second component is a battery.

10. The apparatus of claim 6, wherein the host machine is configured for processing the current and calibrated baseline performance signatures through the aging model in part by comparing the current and calibrated baseline performance signatures to a recorded trace of past performance values for substantially similar components.

11. The apparatus of claim 6, wherein the host machine is configured for recording a desired system life for the system, and for calculating the cost-optimal repair case by calculating a repair which is cost-optimal over the desired system life.

12. A method comprising:

recording a current performance signature for a starter motor and a battery in a vehicle cranking system;

recording a calibrated baseline performance signature for the starter motor and the battery;

processing the current and calibrated baseline performance signatures through an aging model of a host machine to determine a future performance signature for each of the components;

processing the future performance signatures for the components through a system function model of the host machine to determine the state of function of the system for each possible repair case, wherein each possible repair case describes a possible repair combination of the first and second components;

calculating, via the host machine, a cost-optimal repair case from among the possible repair cases; and

recording the cost-optimal repair case in memory of the host machine.

13. The method of claim 12, further comprising:

extracting the cost-optimal repair case from memory of the host machine; and

performing the optimal repair case by replacing or repairing at least one of the starter motor and battery.

14. The method of claim 12, further comprising:

recording the current and calibrated baseline performance signatures via a data recorder positioned aboard the vehicle;

transmitting the current and calibrated baseline performance signatures to the host machine; and

processing the current and calibrated baseline performance signatures via a host machine in remote communication with the data recorder.

15. The method of claim 12, wherein processing the current and calibrated baseline performance signatures through an aging model includes comparing the current and calibrated baseline performance signatures to a recorded trace of past performance values for a substantially similar starter motor and battery.

16. The method of claim 12, further comprising:

recording a desired system life for the system; and

calculating, via the host machine, the cost-optimal repair case by calculating a repair which is cost-optimal over the desired system life.