REMOTE VEHICLE NETWORK MONITORING AND FAILURE PREDICTION SYSTEM

• US 20180276913A1
• Filed: 09/29/2017
• Published: 09/27/2018
• Est. Priority Date: 09/30/2016
• Status: Abandoned Application

• Current Assignee: Faraday & Future Inc.
• Original Assignee: Faraday & Future Inc.
• Inventors: Garcia, Mario R., Velev, Omourtag Alexandrov, Lee, Dong Ryeol
• Application Number:
  US15/721,154
• Publication Number:
  US 20180276913A1
• Time in Patent Office: Days
• CPC Class Codes: B60L 2240/70 Interactions with external data bases, e.g. traffic centres
• CPC Class Codes: B60L 3/0046 relating to electric energy storage systems, e.g. batteries or capacitors
• CPC Class Codes: B60L 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 58/16 responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
• CPC Class Codes: B60R 16/023 for transmission of signals between vehicle parts or subsystems
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: H04L 12/40 Bus networks
• CPC Class Codes: H04L 2012/40215 Controller Area Network CAN
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/16 Information or communication technologies improving the operation of electric vehicles

Abstract

Certain embodiments are described that provide a method for remotely monitoring vehicle electronic networks and predicting failures. Electronic module status data is received, remotely from a vehicle, from a plurality of modules on a vehicle electronic network in the vehicle. The status data for a plurality of vehicles is collected. The status data includes information indicative of potential future failure. The status data is correlated from the plurality of modules in the vehicle, for each of the plurality of vehicles, to provide correlated status data for each vehicle. The correlated status data is analyzed for the plurality of vehicles to identify a probable location of a potential failure in the at least one vehicle electronic network.

Claims

1. A method for remotely monitoring electronic networks in vehicles and predicting failures, comprising:

receiving, remotely from a vehicle, electronic module status data from a plurality of modules on at least one vehicle electronic network in the vehicle, wherein the status data includes information indicative of potential future failure;

repeating the receiving step for a plurality of vehicles;

correlating the status data from the plurality of modules in the vehicle, for each of the plurality of vehicles, to provide correlated status data for each vehicle; and

analyzing the correlated status data for the plurality of vehicles to identify a probable location of a potential failure in the at least one vehicle electronic network of one of the vehicles.

2. The method of claim 1 wherein the status data is received for multiple locations in a hierarchy of the at least one vehicle electronic network, the hierarchy including a plurality of a sensor, a module, a connection between modules, a particular controller area network or an Ethernet bus.

3. The method of claim 1 further comprising:

determining an estimated life expectancy for each of the plurality of modules based on analysis of the status data.

4. The method of claim 3 further comprising:

wherein the module is a battery element, determining a remaining capacity of the battery element.

5. The method of claim 3 further comprising:

providing a recommended corrective action based on the estimated life expectancy.

6. The method of claim 3 further comprising:

receiving supplier module failure data;

including the supplier module and component failure data in the determining an estimated life expectancy for each of the plurality of modules.

7. The method of claim 1 further comprising:

receiving sensor data from a plurality of sensors in the vehicle for each of the plurality of vehicles;

determining a subset of the plurality of vehicles with similar sensor data patterns; and

analyzing the correlated status data for the subset of the plurality of vehicles to identify the probable location of the potential failure in the at least one vehicle electronic network.

8. The method of claim 6 further comprising:

providing a recommended corrective action based on probable location.

9. The method of claim 1 wherein analyzing the correlated status data for the plurality of vehicles to identify the probable location of the potential failure in the at least one vehicle electronic network further comprises:

determining a probable location in a hierarchy of a battery system, the hierarchy including a pack, a string, a module and a cell.

10. The method of claim 1 wherein the status data includes packet corruption data for a controller area network.

20. The non-transitory computer readable media of claim 1 wherein the status data includes packet corruption data for a controller area network.

11. A non-transitory computer readable media having computer readable code for remotely monitoring a vehicle electronic network and predicting failures, comprising computer readable instructions for:

receiving, remotely from a vehicle, electronic module status data from a plurality of modules on at least one vehicle electronic network in the vehicle, wherein the status data includes information indicative of potential future failure;

repeating the receiving step for a plurality of vehicles;

correlating the status data from the plurality of modules in the vehicle, for each of the plurality of vehicles, to provide correlated status data for each vehicle; and

analyzing the correlated status data for the plurality of vehicles to identify a probable location of a potential failure in the at least one vehicle electronic network of one of the vehicles.

12. The non-transitory computer readable media of claim 11 wherein the status data is received for multiple locations in a hierarchy of the at least one vehicle electronic network, the hierarchy including a plurality of a sensor, a module, a connection between modules, a particular controller area network or an Ethernet bus.

13. The non-transitory computer readable media of claim 11 further comprising:

determining an estimated life expectancy for each of the plurality of modules based on analysis of the status data.

14. The non-transitory computer readable media of claim 13 further comprising computer readable instructions for:

wherein the module is a battery element, determining a remaining capacity of the battery element.

15. The non-transitory computer readable media of claim 13 further comprising computer readable instructions for:

providing a recommended corrective action based on the estimated life expectancy.

16. The non-transitory computer readable media of claim 13 further comprising instructions for:

receiving supplier module failure data;

including the supplier module and component failure data in the determining an estimated life expectancy for each of the plurality of modules.

17. The non-transitory computer readable media of claim 11 further comprising computer readable instructions for:

receiving sensor data from a plurality of sensors in the vehicle for each of the plurality of vehicles;

determining a subset of the plurality of vehicles with similar sensor data patterns; and

analyzing the correlated status data for the subset of the plurality of vehicles to identify the probable location of the potential failure in the at least one vehicle electronic network.

18. The non-transitory computer readable media of claim 16 further comprising computer readable instructions for:

providing a recommended corrective action based on probable location.

19. The non-transitory computer readable media of claim 11 wherein analyzing the correlated status data for the plurality of vehicles to identify the probable location of the potential failure in the at least one vehicle electronic network further comprises:

determining a probable location in a hierarchy of a battery system, the hierarchy including a pack, a string, a module and a cell.