ENGINE-OUT NOX VIRTUAL SENSOR USING CYLINDER PRESSURE SENSOR

• US 20100083640A1
• Filed: 10/06/2008
• Published: 04/08/2010
• Est. Priority Date: 10/06/2008
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Wang, Yue-Yun, He, Yongsheng
• Granted Patent: US 8,301,356 B2
• Time in Patent Office: Days
• US Class Current: 60/286
• CPC Class Codes: F01N 2900/14 said parameters being related to the exhaust gas
• CPC Class Codes: F02D 2041/288 for performing a transformation into the frequency domain, e.g. Fourier transformation
• CPC Class Codes: F02D 35/026 using an estimation
• CPC Class Codes: F02D 41/1405 Neural network control
• CPC Class Codes: F02D 41/1462 with determination means using an estimation

Abstract

A Method for estimating NOx creation in a combustion process of a four-stroke internal combustion engine includes monitoring engine sensor inputs, modeling parameters descriptive of said combustion process based upon said engine sensor inputs, and estimating NOx creation with an artificial neural network based upon said parameters.

Claims

1. Method for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, comprising:

monitoring engine sensor inputs;

modeling parameters descriptive of said combustion process based upon said engine sensor inputs; and

estimating NOx creation with an artificial neural network based upon said parameters.

2. The method of claim 1, further comprising controlling aftertreatment devices based upon said estimating NOx creation.

3. The method of claim 1, wherein said monitoring engine sensor inputs comprises monitoring cylinder pressure.

4. The method of claim 3, wherein said modeling parameters descriptive of said combustion process includes determining a mass fraction burn percentage based upon monitored cylinder pressure.

5. The method of claim 3, wherein said modeling parameters descriptive of said combustion process includes determining a mass fraction burn percentage by calculating a total heat released for a given crank angle based upon monitored cylinder pressure.

6. The method of claim 3, wherein said modeling parameters descriptive of said combustion process includes analyzing said monitored cylinder pressure through spectral analysis comprising a Fast Fourier Transform.

7. The method of claim 1, further comprising modifying a result of said estimating NOx creation based upon a dynamic engine factor.

8. The method of claim 7, wherein said dynamic engine factor comprises a filter discriminating NOx estimates generated during transitory engine operation.

9. The method of claim 7, wherein said dynamic engine factor comprises a NOx creation rate estimate utilized to estimate effects of transitory engine operation.

10. The method of claim 1, wherein said modeling parameters descriptive of said combustion process includes monitoring parameters comprising:

a crank angle wherein a predetermined percentage of a fractional pressure rise in said combustion chamber is achieved;

a maximum pressure achieved within said combustion chamber;

a crank angle wherein said maximum pressure is achieved;

an air-fuel ratio; and

a percentage of cylinder intake comprising exhaust gas recirculation flow.

11. The method of claim 1, wherein said modeling parameters descriptive of said combustion process includes monitoring parameters comprising:

an estimated temperature of burned charge within said cylinder;

a crank angle wherein a predetermined percentage of a fractional pressure rise in said combustion chamber is achieved;

a percentage of intake comprising exhaust gas recirculation flow;

an air-fuel ratio; and

a fuel rail pressure.

12. The method of claim 1, wherein said modeling parameters descriptive of said combustion process includes monitoring parameters comprising:

an estimated average temperature within said combustion chamber;

a crank angle wherein a predetermined percentage of a fractional pressure rise in said combustion chamber is achieved;

a percentage of intake comprising exhaust gas recirculation flow;

an air-fuel ratio; and

a fuel rail pressure.

13. The method of claim 1, wherein said modeling parameters descriptive of said combustion process includes monitoring parameters comprising:

an estimated average temperature within said combustion chamber;

a crank angle wherein a predetermined percentage of a fractional pressure rise in said combustion chamber is achieved;

an engine speed;

a fuel energy content;

an oxygen sensor measurement; and

a fuel rail pressure.

14. The method of claim 1, wherein said modeling parameters descriptive of said combustion process includes monitoring parameters comprising:

an estimated average temperature within said combustion chamber;

a crank angle wherein a predetermined percentage of a fractional pressure rise in said combustion chamber is achieved;

an engine speed;

a fuel energy content;

an oxygen sensor measurement; and

a start of fuel injection crank angle.

15. Apparatus for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, said apparatus comprising:

a pressure sensor generating pressure sensor readings describing conditions within said combustion chamber;

a NOx estimation module including logic operations comprising;

monitoring said pressure sensor readings;

modeling parameters descriptive of said combustion process based upon said pressure sensor readings; and

estimating NOx creation with an artificial neural network based upon said parameters; and

an aftertreatment system receiving an exhaust gas flow from said engine and modulating aftertreatment based upon said NOx creation estimate.

16. The apparatus of claim 15, wherein said logic operations further comprise a dynamic engine filter modulating NOx estimates based upon transient operation of said engine.

17. The apparatus of claim 15, wherein said aftertreatment system comprises a lean NOx trap;

and wherein said modulating aftertreatment comprises scheduling regeneration events.

18. The apparatus of claim 15, wherein said aftertreatment system comprises a selective catalytic reduction device;

and wherein said modulating aftertreatment comprises dosing urea injection based upon said NOx creation estimation.