CORRELATION BASED FUEL TANK LEAK DETECTION

• US 20150219522A1
• Filed: 02/04/2014
• Published: 08/06/2015
• Est. Priority Date: 02/04/2014
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Tseng, Fling, Makki, Imad Hassan, Dudar, Aed M., Jentz, Robert Roy, Filev, Dimitar Petrov
• Granted Patent: US 9,857,266 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: F02D 2041/225 Leakage detection
• CPC Class Codes: F02D 2200/0414 Air temperature
• CPC Class Codes: F02D 2200/0602 Fuel pressure
• CPC Class Codes: F02D 2200/0606 Fuel temperature
• CPC Class Codes: F02D 2200/703 Atmospheric pressure
• CPC Class Codes: F02D 41/22 Safety or indicating devices for abnormal conditions in air/fuel ratio feedback systems F02D41/1495, in electric control linkage F02D11/107, in purge control systems F02M25/0809
• CPC Class Codes: F02D 41/266 the computer being backed-up or assisted by another circuit, e.g. analogue
• CPC Class Codes: F02M 25/0809 Judging failure of purge control system
• CPC Class Codes: G01M 3/025 Details with respect to the testing of engines or engine parts
• CPC Class Codes: G01M 3/3272 for verifying the internal pressure of closed containers
• CPC Class Codes: Y02T 10/40 Engine management systems

Abstract

A method for an engine, comprising: sealing a fuel tank; and indicating fuel system degradation based on a comparison of a first correlation coefficient, determined based on a change in fuel tank pressure and a change in fuel tank temperature, to a second correlation coefficient determined based on a change in ambient pressure and a change in ambient temperature. In this way, leak tests, such as engine-off natural vacuum tests, may be performed without knowledge of the properties of the fuel stored in the fuel tank.

Claims

1. A method for an engine, comprising:

sealing a fuel tank; and

indicating fuel system degradation based on a comparison of a first correlation coefficient, determined based on a change in fuel tank pressure and a change in fuel tank temperature, to a second correlation coefficient determined based on a change in ambient pressure and a change in ambient temperature.

2. The method of claim 1, further comprising:

indicating a fuel system leak if the first correlation coefficient is less than the second correlation coefficient.

3. The method of claim 2, further comprising:

indicating an intact fuel system if the first correlation coefficient is greater than the second correlation coefficient.

4. The method of claim 1, further comprising:

determining a third correlation coefficient based on the change in fuel tank pressure and the change in ambient pressure; and

indicating a fuel system leak if the third correlation coefficient is greater than a correlation threshold.

5. The method of claim 1, where determining the first correlation coefficient includes determining if a fuel tank temperature entropy is greater than an entropy threshold.

6. The method of claim 5, where determining the first correlation coefficient includes retrieving a first correlation model based on one or more previous fuel system degradation tests.

7. The method of claim 6, where determining the second correlation coefficient includes retrieving a second correlation model based on one or more previous fuel system degradation tests.

8. The method of claim 7, where the first and second correlation models are retrieved from a cloud computing system coupled to a plurality of vehicles.

9. A method for testing a vehicle fuel tank for leaks, comprising:

sealing the vehicle fuel tank;

determining whether a fuel tank fill level is between a first fill level limit and a second fill level limit;

monitoring fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure for a duration;

determining entropy levels for fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure over the duration;

determining recursive means and standard deviations for fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure over the duration;

determining a first correlation coefficient based on the recursive means and standard deviations for fuel tank pressure and fuel tank temperature over the duration;

determining a second correlation coefficient based on the recursive means and standard deviations for ambient pressure and ambient temperature over the duration; and

indicating a fuel tank leak if the first correlation coefficient is less than the second correlation coefficient.

10. The method of claim 9, further comprising:

determining a third correlation coefficient based on the recursive means and standard deviations for fuel tank pressure and ambient pressure; and

indicating a fuel tank leak if the third correlation coefficient is greater than a correlation threshold.

11. The method of claim 9, where determining the first correlation coefficient includes determining if the entropy level for fuel tank temperature is greater than an entropy threshold.

12. The method of claim 11, where determining the first correlation coefficient includes retrieving a first correlation model based on one or more previous fuel system degradation tests.

13. The method of claim 12, where determining a second correlation coefficient includes retrieving a second correlation model based on one or more previous fuel system degradation tests.

14. The method of claim 13, where the first and second correlation models are retrieved from a cloud computing system coupled to a plurality of vehicles.

15. The method of claim 9, further comprising:

determining whether a fuel sloshing amount is below a sloshing threshold prior to monitoring fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure for a duration.

16. A system for a vehicle, comprising:

a fuel tank temperature sensor coupled to a fuel tank;

a fuel tank pressure sensor coupled to the fuel tank;

a fuel level sensor coupled within the fuel tank;

an ambient temperature sensor;

an ambient pressure sensor;

one or more valves configured to seal the fuel tank when closed; and

a controller configured with instructions stored in non-transitory memory, that when executed cause the controller to;

seal the fuel tank;

determine whether a fuel tank fill level is between a first fill level limit and a second fill level limit;

monitor fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure for a duration;

determine entropy levels for fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure over the duration;

determine recursive means and standard deviations for fuel tank temperature, fuel tank pressure, ambient temperature, and ambient pressure over the duration;

determine a first correlation coefficient based on the recursive means and standard deviations for fuel tank pressure and fuel tank temperature over the duration;

determine a second correlation coefficient based on the recursive means and standard deviations for ambient pressure and ambient temperature over the duration; and

indicate a fuel tank leak if the first correlation coefficient is less than the second correlation coefficient.

17. The system of claim 16, where the controller is further configured with instructions stored in non-transitory memory, that when executed cause the controller to:

determine a third correlation coefficient based on the recursive means and standard deviations for fuel tank pressure and ambient pressure; and

indicate a fuel tank leak if the third correlation coefficient is greater than a correlation threshold.

18. The system of claim 16, further comprising:

a communications module configured to communicate with a cloud computing system; and

where the controller is further configured with instructions stored in non-transitory memory, that when executed cause the controller to;

retrieve one or more correlation models from the cloud computing system via the communications module;

determine the first correlation coefficient based on the one or more correlation models; and

determine the second correlation coefficient based on the one or more correlation models.

19. The system of claim 18, where the cloud computing system is coupled to two or more vehicles.

20. The system of claim 19, where the one or more correlation models are based on fuel tank leak test results from the two or more vehicles.