Digital twin system for a cooling system

• US 9,881,430 B1
• Filed: 02/22/2017
• Issued: 01/30/2018
• Est. Priority Date: 02/22/2017
• Status: Active Grant

• Current Assignee: GE Global Sourcing LLC (Westinghouse Air Brake Technologies Corporation)
• Original Assignee: General Electric Company
• Inventors: Shah, Tapan, Govindappa, Suresh, Nistler, Paul, Narayanan, Babu
• Primary Examiner(s): Frejd, Russell
• Application Number:
  US15/438,866
• Time in Patent Office: 342 Days
• CPC Class Codes: B60H 1/00585 Means for monitoring, testing or servicing the air-conditioning
• CPC Class Codes: B60H 1/0073 Control systems or circuits characterised by particular algorithms or computational models, e.g. fuzzy logic or dynamic models
• CPC Class Codes: F01P 11/14 Indicating devices; Other safety devices
• CPC Class Codes: F01P 11/16 concerning coolant temperature F01P11/20 takes precedence
• CPC Class Codes: F01P 11/18 concerning coolant pressure, coolant flow, or liquid-coolant level
• CPC Class Codes: F01P 2025/60 Operating parameters
• CPC Class Codes: G01M 15/048 by monitoring temperature
• CPC Class Codes: G01M 15/09 by monitoring pressure in fluid ducts, e.g. in lubrication or cooling parts
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/23 using finite element methods [FEM] or finite difference methods [FDM]
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005

Abstract

A system includes plural, different sensors configured to be operably connected to a first vehicle. The sensors obtain status data indicative of a state of a cooling system of the first vehicle. The system includes a digital twin system having processors configured to modify the status data having sampling rates or resolutions that differ such that the status data that is modified has a common sampling rate resolution as that of other data. The processors create a digital twin matrix of the status data. The digital twin matrix is indicative of the state of the cooling system. The processors also determine a health score of the cooling system or simulate operation of the cooling system based on the digital twin matrix. The digital twin system is configured to change or control actual operation of the cooling system based on the health score or the operation that is simulated.

Claims

1. A system comprising:

plural, different sensors each configured to be operably connected to a first vehicle, the sensors also configured to obtain status data indicative of a state of a cooling system of the first vehicle, wherein at least some of the status data obtained by the different sensors differs in one or more of sampling rates or resolutions for at least two of the different sensors;

a digital twin system having one or more processors configured to modify the at least some of the status data having the one or more of sampling rates or resolutions that differ for at least two of the different sensors such that the at least some of the status data that is modified has one or more of a common sampling rate or a common resolution as that of other data in the status data, wherein the one or more processors are configured to create a digital twin matrix of the status data that is obtained and the at least some of the status data that is modified, the digital twin matrix indicative of the state of the cooling system of the first vehicle, and one or more of;

determine a health score of the cooling system of the first vehicle based on the digital twin matrix;

or

simulate operation of the cooling system of the first vehicle based on the digital twin matrix; and

wherein the digital twin system is configured to change or control actual operation of the cooling system of the first vehicle based on one or more of the health score or the operation of the cooling system that is simulated.

2. The system of claim 1, wherein the one or more processors are configured to predict a likelihood of failure of the cooling system of the first vehicle using the health score of the cooling system.

3. The system of claim 1, wherein the one or more processors are configured to predict a likelihood of failure of the cooling system of the first vehicle based on the operation that is simulated.

4. The system of claim 1, wherein the one or more processors are configured to determine the health score by comparing the digital twin matrix of the cooling system of the first vehicle with reference data of a modeled cooling system.

5. The system of claim 4, wherein the reference data includes one or more of an ambient temperature, altitude, or barometric air pressure.

6. The system of claim 4, wherein the reference data includes one or more of simulated engine oil inlet temperature data, simulated engine water inlet temperature data, or simulated manifold air temperature data.

7. The system of claim 1, wherein the status data of the cooling system of the first vehicle includes one or more of engine oil inlet temperature data, engine water inlet temperature data, or manifold air temperature data.

8. The system of claim 1, wherein the first vehicle is one or more of an automobile, a rail vehicle, a truck, a marine vessel, a mining vehicle, an aerial drone, or another aerial vehicle.

9. The system of claim 1, wherein the digital twin matrix of the cooling system of the first vehicle is a numerical representation of the cooling system of the first vehicle.

10. The system of claim 1, wherein the health score of the cooling system of the first vehicle is determined by linearly combining the digital twin matrix of the cooling system of the first vehicle with an average or median of plural digital twin matrices of additional vehicles.

11. The system of claim 1, the one or more processors configured to compare the health score of the cooling system of the first vehicle with a health score of plural digital twin matrices of additional vehicles in order to value the cooling system of the first vehicle with respect to the cooling systems of a fleet system.

12. The system of claim 11, wherein the fleet system comprises the first vehicle and the additional vehicles.

13. A method comprising:

obtaining, with plural, different sensors operably connected to a first vehicle, status data indicative of a state of a cooling system of the first vehicle, at least some of the status data obtained by the different sensors differing in one or more of sampling rates or resolutions for at least two of the different sensors;

modifying the at least some of the status data having the one or more of sampling rates or resolutions that differ for at least two of the different sensors such that the at least some of the status data that is modified has one or more of a common sampling rate or a common resolution as that of other data in the status data;

creating a digital twin matrix of the status data that is obtained and the at least some of the status data that is modified, the digital twin matrix indicative of the state of the cooling system of the first vehicle; and

one or more of;

determining a health score of the cooling system of the first vehicle based on the digital twin matrix;

or

simulating operation of the cooling system of the first vehicle based on the digital twin matrix; and

changing or controlling actual operation of the cooling system of the first vehicle based on one or more of the health score or the operation of the cooling system that is simulated.

14. The method of claim 13, further comprising predicting a likelihood of failure of the cooling system of the first vehicle using the health score of the cooling system.

15. The method of claim 13, further comprising predicting a likelihood of failure of the cooling system of the first vehicle based on the operation that is simulated.

16. The method of claim 13, wherein determining the health score includes comparing the digital twin matrix of the cooling system of the first vehicle with reference data of a modeled cooling system.

17. The method of claim 16, wherein the reference data includes one or more of an ambient temperature, altitude, or barometric air pressure.

18. A system comprising:

a first sensor configured to be operably connected to a vehicle and configured to obtain first status data indicative of a state of a cooling system of the vehicle;

a different, second sensor configured to be operably connected to the vehicle and configured to obtain different, second status data indicative of the state of the cooling system of the vehicle, wherein the second sensor is configured to obtain the second status data at one or more of a different sampling rate or resolution than the first sensor is configured to obtain the first status data; and

a digital twin system having one or more processors configured to modify the first status data, the second status data, or both the first status data and the second status data to create modified status data such that the first status data and the second status data in the modified status data have one or more of a common sampling rate or a common resolution, the one or more processors also configured to create a digital twin matrix of the modified status data, the digital twin matrix indicative of the state of the cooling system of the vehicle, the one or more processors also configured to one or more of determine a health score of the cooling system of the vehicle based on the digital twin matrix or simulate operation of the cooling system of the vehicle based on the digital twin matrix, wherein the digital twin system is configured to change or control operation of the cooling system of the vehicle based on one or more of the health score or the operation of the cooling system that is simulated.

19. The system of claim 18, wherein the one or more processors are configured to predict a likelihood of failure of the cooling system of the vehicle using the health score of the cooling system.

20. The system of claim 18, wherein the one or more processors are configured to predict a likelihood of failure of the cooling system of the vehicle based on the operation that is simulated.