COLLABORATIVE VEHICLE HEALTH MODEL

• US 20130262067A1
• Filed: 03/29/2012
• Published: 10/03/2013
• Est. Priority Date: 03/29/2012
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: ZHANG, Yilu, Howell, Mark N., Tang, Xidong, Bai, Fan, Du, Xinyu, Singh, Satnam
• Granted Patent: US 9,058,038 B2
• Time in Patent Office: Days
• US Class Current: 703/8
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G05B 23/024 Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C

Abstract

A method includes collecting vehicle health data from a plurality of vehicles. A peer group is identified among the plurality of vehicles. The collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.

Claims

1. A method comprising:

collecting vehicle health data from a plurality of vehicles;

identifying a peer group among the plurality of vehicles; and

incorporating the collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.

2. The method of claim 1, wherein the vehicle health data is collected via a network.

3. The method of claim 2, wherein the network is a wireless network.

4. The method of claim 1, wherein identifying the peer group comprises identifying vehicles of the plurality of vehicles that are characterized by a predefined set of characteristics.

5. The method of claim 4, wherein the predefined characteristics include characteristics of a component of the vehicle.

6. The method of claim 1, wherein incorporating the collected vehicle health data from the peer group into the collaborative vehicle health model comprises adjusting a parameter of the collaborative vehicle health model in accordance with the collected health data.

7. The method of claim 6, wherein adjusting the parameter comprises applying a least mean square error technique.

8. The method of claim 1, wherein the collaborative vehicle health model is applicable to a battery of the current vehicle to predict a capacity of the battery.

9. The method of claim 1, wherein the collaborative vehicle health model is applicable to a brake of the current vehicle to predict a wear of a brake pad of the brake.

10. A system comprising a processor to:

collect vehicle health data from a plurality of vehicles;

identify a peer group among the plurality of vehicles;

incorporate the collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.

11. The system of claim 10, comprising a network to enable communication between the processor and said plurality of vehicles.

12. The system of claim 11, wherein the network is a wireless network.

13. The system of claim 11, wherein the current vehicle is configured to communicate with the processor via the network, and wherein the collaborative vehicle health model is applicable by the processor to the component of the current vehicle.

14. The system of claim 11, wherein at least a parameter of the collaborative vehicle health model is distributable to the current vehicle via the network, and wherein a processor of the current vehicle is configured to apply the collaborative vehicle health model to the current vehicle.

15. The system of claim 10, wherein the peer group comprises vehicles of the plurality of vehicles that are characterized by a predefined set of characteristics.

16. The system of claim 15, wherein the predefined characteristics include characteristics of a component of the vehicle.

17. The system of claim 10, wherein the collaborative vehicle health model is parameterized by an adjustable parameter.

18. The system of claim 10, wherein the collaborative vehicle health model is applicable to a battery of the current vehicle to predict a capacity of the battery.

19. The system of claim 10, wherein the collaborative vehicle health model is applicable to a brake of the current vehicle to predict a wear of a brake pad of the brake.

20. A non-transitory computer readable medium having stored thereon instructions that when executed by a processor will cause the processor to perform the method of:

collecting vehicle health data from a plurality of vehicles;

identifying a peer group among the plurality of vehicles; and

incorporating the collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.